what is quantitative research in social science

USC Libraries
Research Guides

Organizing Your Social Sciences Research Paper

Quantitative Methods
Purpose of Guide
Design Flaws to Avoid
Independent and Dependent Variables
Glossary of Research Terms
Reading Research Effectively
Narrowing a Topic Idea
Broadening a Topic Idea
Extending the Timeliness of a Topic Idea
Academic Writing Style
Applying Critical Thinking
Choosing a Title
Making an Outline
Paragraph Development
Research Process Video Series
Executive Summary
The C.A.R.S. Model
Background Information
The Research Problem/Question
Theoretical Framework
Citation Tracking
Content Alert Services
Evaluating Sources
Primary Sources
Secondary Sources
Tiertiary Sources
Scholarly vs. Popular Publications
Qualitative Methods
Insiderness
Using Non-Textual Elements
Limitations of the Study
Common Grammar Mistakes
Writing Concisely
Avoiding Plagiarism
Footnotes or Endnotes?
Further Readings
Generative AI and Writing
USC Libraries Tutorials and Other Guides
Bibliography

Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Need Help Locating Statistics?

Resources for locating data and statistics can be found here:

Statistics & Data Research Guide

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Things to keep in mind when reporting the results of a study using quantitative methods :

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
Always tell the reader what to look for in tables and figures .

NOTE: When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
You can summarize vast sources of information and make comparisons across categories and over time; and,
Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
Uses a static and rigid approach and so employs an inflexible process of discovery;
The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
Results provide less detail on behavior, attitudes, and motivation;
Researcher may collect a much narrower and sometimes superficial dataset;
Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

<< Previous: Qualitative Methods
Next: Insiderness >>
Last Updated: Aug 13, 2024 12:57 PM
URL: https://libguides.usc.edu/writingguide

A Quick Guide to Quantitative Research in the Social Sciences

(12 reviews)

Christine Davies, Carmarthen, Wales

Last Update: 2021

Publisher: University of Wales Trinity Saint David

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Jennifer Taylor, Assistant Professor, Texas A&M University-Corpus Christi on 4/18/24

This resource is a quick guide to quantitative research in the social sciences and not a comprehensive resource. It provides a VERY general overview of quantitative research but offers a good starting place for students new to research. It... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 4

The content is relatively accurate. The measurement scale section is very sparse. Not all types of research designs or statistical methods are included, but it is a guide, so details are meant to be limited.

Relevance/Longevity rating: 4

The examples were interesting and appropriate. The content is up to date and will be useful for several years.

Clarity rating: 5

The text was clearly written. Tables and figures are not referenced in the text, which would have been nice.

Consistency rating: 5

The framework is consistent across chapters with terminology clearly highlighted and defined.

Modularity rating: 5

The chapters are subdivided into section that can be divided and assigned as reading in a course. Most chapters are brief and concise, unless elaboration is necessary, such as with the data analysis chapter. Again, this is a guide and not a comprehensive text, so sections are shorter and don't always include every subtopic that may be considered.

Organization/Structure/Flow rating: 5

The guide is well organized. I appreciate that the topics are presented in a logical and clear manner. The topics are provided in an order consistent with traditional research methods.

Interface rating: 5

The interface was easy to use and navigate. The images were clear and easy to read.

Grammatical Errors rating: 5

I did not notice any grammatical errors.

Cultural Relevance rating: 5

The materials are not culturally insensitive or offensive in any way.

I teach a Marketing Research course to undergraduates. I would consider using some of the chapters or topics included, especially the overview of the research designs and the analysis of data section.

Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 3/9/24

Comprehensiveness rating: 3 see less

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers references to other resources that can be used to deepen the knowledge. The text does not include a glossary or index. The references in the figures for each chapter are not included in the reference section. It would be helpful to include those.

Overall, the text is accurate. For example, Figure 1 on page 6 provides a clear overview of the research process. It includes general definitions of primary and secondary research. It would be helpful to include more details to explain some of the examples before they are presented. For instance, the example on page 5 was unclear how it pertains to the literature review section.

In general, the text is relevant and up-to-date. The text includes many inferences of moving from qualitative to quantitative analysis. This was surprising to me as a quantitative researcher. The author mentions that moving from a qualitative to quantitative approach should only be done when needed. As a predominantly quantitative researcher, I would not advice those interested in transitioning to using a qualitative approach that qualitative research would enhance their research—not something that should only be done if you have to.

Clarity rating: 4

The text is written in a clear manner. It would be helpful to the reader if there was a description of the tables and figures in the text before they are presented.

Consistency rating: 4

The framework for each chapter and terminology used are consistent.

Modularity rating: 4

The text is clearly divided into sections within each chapter. Overall, the chapters are a similar brief length except for the chapter on data analysis, which is much more comprehensive than others.

Organization/Structure/Flow rating: 4

The topics in the text are presented in a clear and logical order. The order of the text follows the conventional research methodology in social sciences.

I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader.

Grammatical Errors rating: 3

There are some grammatical/typographical errors throughout. Of note, for Section 5 in the table of contents. “The” should be capitalized to start the title. In the title for Table 3, the “t” in typical should be capitalized.

Cultural Relevance rating: 4

The examples are culturally relevant. The text is geared towards learners in the UK, but examples are relevant for use in other countries (i.e., United States). I did not see any examples that may be considered culturally insensitive or offensive in any way.

I teach a course on research methods in a Bachelor of Science in Public Health program. I would consider using some of the text, particularly in the analysis chapter to supplement the current textbook in the future.

Reviewed by Finn Bell, Assistant Professor, University of Michigan, Dearborn on 1/3/24

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary. read more

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary.

Content Accuracy rating: 5

As far as I can tell, the text is accurate, error-free and unbiased.

Relevance/Longevity rating: 5

This text is up-to-date, and given the content, unlikely to become obsolete any time soon.

The text is very clear and accessible.

The text is internally consistent.

Given how short the text is, it seems unnecessary to divide it into smaller readings, nonetheless, it is clearly labelled such that an instructor could do so.

The text is well-organized and brings readers through basic quantitative methods in a logical, clear fashion.

Easy to navigate. Only one table that is split between pages, but not in a way that is confusing.

There were no noticeable grammatical errors.

The examples in this book don't give enough information to rate this effectively.

This text is truly a very quick guide at only 26 double-spaced pages. Nonetheless, Davies packs a lot of information on the basics of quantitative research methods into this text, in an engaging way with many examples of the concepts presented. This guide is more of a brief how-to that takes readers as far as how to select statistical tests. While it would be impossible to fully learn quantitative research from such a short text, of course, this resource provides a great introduction, overview, and refresher for program evaluation courses.

Reviewed by Shari Fedorowicz, Adjunct Professor, Bridgewater State University on 12/16/22

Comprehensiveness rating: 5 see less

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing the reader with the ability to distinguish two terms that frequently get confused. In addition, links and outside resources are provided to deepen the understanding as an option for the reader. The use of these links, coupled with diagrams and examples make this text comprehensive.

The content is mostly accurate. Given that it is a quick guide, the author chose a good selection of which types of research designs to include. However, some are not provided. For example, correlational or cross-correlational research is omitted and is not discussed in Section 3, but is used as a statistical example in the last section.

Examples utilized were appropriate and associated with terms adding value to the learning. The tables that included differentiation between types of statistical tests along with a parametric/nonparametric table were useful and relevant.

The purpose to the text and how to use this guide book is stated clearly and is established up front. The author is also very clear regarding the skill level of the user. Adding to the clarity are the tables with terms, definitions, and examples to help the reader unpack the concepts. The content related to the terms was succinct, direct, and clear. Many times examples or figures were used to supplement the narrative.

The text is consistent throughout from contents to references. Within each section of the text, the introductory paragraph under each section provides a clear understanding regarding what will be discussed in each section. The layout is consistent for each section and easy to follow.

The contents are visible and address each section of the text. A total of seven sections, including a reference section, is in the contents. Each section is outlined by what will be discussed in the contents. In addition, within each section, a heading is provided to direct the reader to the subtopic under each section.

The text is well-organized and segues appropriately. I would have liked to have seen an introductory section giving a narrative overview of what is in each section. This would provide the reader with the ability to get a preliminary glimpse into each upcoming sections and topics that are covered.

The book was easy to navigate and well-organized. Examples are presented in one color, links in another and last, figures and tables. The visuals supplemented the reading and placed appropriately. This provides an opportunity for the reader to unpack the reading by use of visuals and examples.

No significant grammatical errors.

The text is not offensive or culturally insensitive. Examples were inclusive of various races, ethnicities, and backgrounds.

This quick guide is a beneficial text to assist in unpacking the learning related to quantitative statistics. I would use this book to complement my instruction and lessons, or use this book as a main text with supplemental statistical problems and formulas. References to statistical programs were appropriate and were useful. The text did exactly what was stated up front in that it is a direct guide to quantitative statistics. It is well-written and to the point with content areas easy to locate by topic.

Reviewed by Sarah Capello, Assistant Professor, Radford University on 1/18/22

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text. read more

The content is mostly accurate. I would have preferred a few nuances to be hashed out a bit further to avoid potential reader confusion or misunderstanding of the concepts presented.

The content is current; however, some of the references cited in the text are outdated. Newer editions of those texts exist.

The text is very accessible and readable for a variety of audiences. Key terms are well-defined.

There are no content discrepancies within the text. The author even uses similarly shaped graphics for recurring purposes throughout the text (e.g., arrow call outs for further reading, rectangle call outs for examples).

The content is chunked nicely by topics and sections. If it were used for a course, it would be easy to assign different sections of the text for homework, etc. without confusing the reader if the instructor chose to present the content in a different order.

The author follows the structure of the research process. The organization of the text is easy to follow and comprehend.

All of the supplementary images (e.g., tables and figures) were beneficial to the reader and enhanced the text.

There are no significant grammatical errors.

I did not find any culturally offensive or insensitive references in the text.

This text does the difficult job of introducing the complicated concepts and processes of quantitative research in a quick and easy reference guide fairly well. I would not depend solely on this text to teach students about quantitative research, but it could be a good jumping off point for those who have no prior knowledge on this subject or those who need a gentle introduction before diving in to more advanced and complex readings of quantitative research methods.

Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 12/9/21

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of thought. There is no glossary but, for a guide of this length, a glossary does not seem like it would enhance the guide significantly.

The content is relatively accurate. Expanding the content a bit more or explaining that the methods and designs presented are not entirely inclusive would help. As there are different schools of thought regarding what should/should not be included in terms of these designs and methods, simply bringing attention to that and explaining a bit more would help.

Relevance/Longevity rating: 3

This content needs to be updated. Most of the sources cited are seven or more years old. Even more, it would be helpful to see more currently relevant examples. Some of the source authors such as Andy Field provide very interesting and dynamic instruction in general, but they have much more current information available.

The language used is clear and appropriate. Unnecessary jargon is not used. The intent is clear- to communicate simply in a straightforward manner.

The guide seems to be internally consistent in terms of terminology and framework. There do not seem to be issues in this area. Terminology is internally consistent.

For a guide of this length, the author structured this logically into sections. This guide could be adopted in whole or by section with limited modifications. Courses with fewer than seven modules could also logically group some of the sections.

This guide does present with logical organization. The topics presented are conceptually sequenced in a manner that helps learners build logically on prior conceptualization. This also provides a simple conceptual framework for instructors to guide learners through the process.

Interface rating: 4

The visuals themselves are simple, but they are clear and understandable without distracting the learner. The purpose is clear- that of learning rather than visuals for the sake of visuals. Likewise, navigation is clear and without issues beyond a broken link (the last source noted in the references).

This guide seems to be free of grammatical errors.

It would be interesting to see more cultural integration in a guide of this nature, but the guide is not culturally insensitive or offensive in any way. The language used seems to be consistent with APA's guidelines for unbiased language.

Reviewed by Heng Yu-Ku, Professor, University of Northern Colorado on 5/13/21

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive... read more

For the most part, the content is accurate and unbiased. However, the author only includes four types of research designs used on the social sciences that contain quantitative elements: 1. Mixed method, 2) Case study, 3) Quasi-experiment, and 3) Action research. I wonder why the correlational research is not included as another type of quantitative research design as it has been introduced and emphasized in section 6 by the author.

I believe the content is up-to-date and that necessary updates will be relatively easy and straightforward to implement.

The text is easy to read and provides adequate context for any technical terminology used. However, the author could provide more detailed information about estimating the minimum sample size but not just refer the readers to use the online sample calculators at a different website.

The text is internally consistent in terms of terminology and framework. The author provides the right amount of information with additional information or resources for the readers.

The text includes seven sections. Therefore, it is easier for the instructor to allocate or divide the content into different weeks of instruction within the course.

Yes, the topics in the text are presented in a logical and clear fashion. The author provides clear and precise terminologies, summarizes important content in Table or Figure forms, and offers examples in each section for readers to check their understanding.

The interface of the book is consistent and clear, and all the images and charts provided in the book are appropriate. However, I did encounter some navigation problems as a couple of links are not working or requires permission to access those (pages 10 and 27).

No grammatical errors were found.

No culturally incentive or offensive in its language and the examples provided were found.

As the book title stated, this book provides “A Quick Guide to Quantitative Research in Social Science. It offers easy-to-read information and introduces the readers to the research process, such as research questions, research paradigms, research process, research designs, research methods, data collection, data analysis, and data discussion. However, some links are not working or need permissions to access them (pages 10 and 27).

Reviewed by Hsiao-Chin Kuo, Assistant Professor, Northeastern Illinois University on 4/26/21, updated 4/28/21

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and process, discusses methods, data collection and analysis, and ends with writing a research report. It also identifies its target readers/users as those begins to explore quantitative research. It would be helpful to include more examples for readers/users who are new to quantitative research.

Its content is mostly accurate and no bias given its nature as a quick guide. Yet, it is also quite simplified, such as its explanations of mixed methods, case study, quasi-experimental research, and action research. It provides resources for extended reading, yet more recent works will be helpful.

The book is relevant given its nature as a quick guide. It would be helpful to provide more recent works in its resources for extended reading, such as the section for Survey Research (p. 12). It would also be helpful to include more information to introduce common tools and software for statistical analysis.

The book is written with clear and understandable language. Important terms and concepts are presented with plain explanations and examples. Figures and tables are also presented to support its clarity. For example, Table 4 (p. 20) gives an easy-to-follow overview of different statistical tests.

The framework is very consistent with key points, further explanations, examples, and resources for extended reading. The sample studies are presented following the layout of the content, such as research questions, design and methods, and analysis. These examples help reinforce readers' understanding of these common research elements.

The book is divided into seven chapters. Each chapter clearly discusses an aspect of quantitative research. It can be easily divided into modules for a class or for a theme in a research method class. Chapters are short and provides additional resources for extended reading.

The topics in the chapters are presented in a logical and clear structure. It is easy to follow to a degree. Though, it would be also helpful to include the chapter number and title in the header next to its page number.

The text is easy to navigate. Most of the figures and tables are displayed clearly. Yet, there are several sections with empty space that is a bit confusing in the beginning. Again, it can be helpful to include the chapter number/title next to its page number.

Grammatical Errors rating: 4

No major grammatical errors were found.

There are no cultural insensitivities noted.

Given the nature and purpose of this book, as a quick guide, it provides readers a quick reference for important concepts and terms related to quantitative research. Because this book is quite short (27 pages), it can be used as an overview/preview about quantitative research. Teacher's facilitation/input and extended readings will be needed for a deeper learning and discussion about aspects of quantitative research.

Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 1/6/21

It covers the most important topics such as research progress, resources, measurement, and analysis of the data. read more

It covers the most important topics such as research progress, resources, measurement, and analysis of the data.

The book accurately describes the types of research methods such as mixed-method, quasi-experiment, and case study. It talks about the research proposal and key differences between statistical analyses as well.

The book pinpointed the significance of running a quantitative research method and its relevance to the field of social science.

The book clearly tells us the differences between types of quantitative methods and the steps of running quantitative research for students.

The book is consistent in terms of terminologies such as research methods or types of statistical analysis.

It addresses the headlines and subheadlines very well and each subheading should be necessary for readers.

The book was organized very well to illustrate the topic of quantitative methods in the field of social science.

The pictures within the book could be further developed to describe the key concepts vividly.

The textbook contains no grammatical errors.

It is not culturally offensive in any way.

Overall, this is a simple and quick guide for this important topic. It should be valuable for undergraduate students who would like to learn more about research methods.

Reviewed by Pierre Lu, Associate Professor, University of Texas Rio Grande Valley on 11/20/20

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas. read more

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas.

Mostly accurate content.

As a quick guide, content is highly relevant.

Succinct and clear.

Internally, the text is consistent in terms of terminology used.

The text is easily and readily divisible into smaller sections that can be used as assignments.

I like that there are examples throughout the book.

Easy to read. No interface/ navigation problems.

No grammatical errors detected.

I am not aware of the culturally insensitive description. After all, this is a methodology book.

I think the book has potential to be adopted as a foundation for quantitative research courses, or as a review in the first weeks in advanced quantitative course.

Reviewed by Sarah Fischer, Assistant Professor, Marymount University on 7/31/20

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable). read more

Content Accuracy rating: 1

Contains VERY significant errors, such as saying that one can "accept" a hypothesis. (One of the key aspect of hypothesis testing is that one either rejects or fails to reject a hypothesis, but NEVER accepts a hypothesis.)

Very relevant to those experiencing the research process for the first time. However, it is written by someone working in the natural sciences but is a text for social sciences. This does not explain the errors, but does explain why sometimes the author assumes things about the readers ("hail from more subjectivist territory") that are likely not true.

Clarity rating: 3

Some statistical terminology not explained clearly (or accurately), although the author has made attempts to do both.

Very consistently laid out.

Chapters are very short yet also point readers to outside texts for additional information. Easy to follow.

Generally logically organized.

Easy to navigate, images clear. The additional sources included need to linked to.

Minor grammatical and usage errors throughout the text.

Makes efforts to be inclusive.

The idea of this book is strong--short guides like this are needed. However, this book would likely be strengthened by a revision to reduce inaccuracies and improve the definitions and technical explanations of statistical concepts. Since the book is specifically aimed at the social sciences, it would also improve the text to have more examples that are based in the social sciences (rather than the health sciences or the arts).

Reviewed by Michelle Page, Assistant Professor, Worcester State University on 5/30/20

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new researcher would not be able to use this as a stand alone guide for quantitative pursuits without having a supplemental text that explains the steps in the process more comprehensively. The introduction does provide this caveat.

Content Accuracy rating: 3

There are no biases or errors that could be distinguished; however, it’s simplicity in content, although accurate for an outline of process, may lack a conveyance of the deeper meanings behind the specific processes explained about qualitative research.

The content is outlined in traditional format to highlight quantitative considerations for formatting research foundational pieces. The resources/references used to point the reader to literature sources can be easily updated with future editions.

The jargon in the text is simple to follow and provides adequate context for its purpose. It is simplified for its intention as a guide which is appropriate.

Each section of the text follows a consistent flow. Explanation of the research content or concept is defined and then a connection to literature is provided to expand the readers understanding of the section’s content. Terminology is consistent with the qualitative process.

As an “outline” and guide, this text can be used to quickly identify the critical parts of the quantitative process. Although each section does not provide deeper content for meaningful use as a stand alone text, it’s utility would be excellent as a reference for a course and can be used as an content guide for specific research courses.

The text’s outline and content are aligned and are in a logical flow in terms of the research considerations for quantitative research.

The only issue that the format was not able to provide was linkable articles. These would have to be cut and pasted into a browser. Functional clickable links in a text are very successful at leading the reader to the supplemental material.

No grammatical errors were noted.

This is a very good outline “guide” to help a new or student researcher to demystify the quantitative process. A successful outline of any process helps to guide work in a logical and systematic way. I think this simple guide is a great adjunct to more substantial research context.

Section 1: What will this resource do for you?
Section 2: Why are you thinking about numbers? A discussion of the research question and paradigms.
Section 3: An overview of the Research Process and Research Designs
Section 4: Quantitative Research Methods
Section 5: the data obtained from quantitative research
Section 6: Analysis of data
Section 7: Discussing your Results

Ancillary Material

About the book.

This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real help.

The booklet was amended in 2022 to take into account previous review comments.

About the Contributors

Christine Davies , Ph.D

Contribute to this Page

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

Knowledge Base

Methodology

What Is Quantitative Research? | Definition, Uses & Methods

What Is Quantitative Research? | Definition, Uses & Methods

Published on June 12, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research is the opposite of qualitative research , which involves collecting and analyzing non-numerical data (e.g., text, video, or audio).

Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.

What is the demographic makeup of Singapore in 2020?
How has the average temperature changed globally over the last century?
Does environmental pollution affect the prevalence of honey bees?
Does working from home increase productivity for people with long commutes?

Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, other interesting articles, frequently asked questions about quantitative research.

You can use quantitative research methods for descriptive, correlational or experimental research.

In descriptive research , you simply seek an overall summary of your study variables.
In correlational research , you investigate relationships between your study variables.
In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.

Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalized to broader populations based on the sampling method used.

To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).

Quantitative research methods
Research method	How to use	Example
	Control or manipulate an to measure its effect on a dependent variable.	To test whether an intervention can reduce procrastination in college students, you give equal-sized groups either a procrastination intervention or a comparable task. You compare self-ratings of procrastination behaviors between the groups after the intervention.
	Ask questions of a group of people in-person, over-the-phone or online.	You distribute with rating scales to first-year international college students to investigate their experiences of culture shock.
(Systematic) observation	Identify a behavior or occurrence of interest and monitor it in its natural setting.	To study college classroom participation, you sit in on classes to observe them, counting and recording the prevalence of active and passive behaviors by students from different backgrounds.
Secondary research	Collect data that has been gathered for other purposes e.g., national surveys or historical records.	To assess whether attitudes towards climate change have changed since the 1980s, you collect relevant questionnaire data from widely available .

Note that quantitative research is at risk for certain research biases , including information bias , omitted variable bias , sampling bias , or selection bias . Be sure that you’re aware of potential biases as you collect and analyze your data to prevent them from impacting your work too much.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Once data is collected, you may need to process it before it can be analyzed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .

Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualize your data and check for any trends or outliers.

Using inferential statistics , you can make predictions or generalizations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .

First, you use descriptive statistics to get a summary of the data. You find the mean (average) and the mode (most frequent rating) of procrastination of the two groups, and plot the data to see if there are any outliers.

You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.

Quantitative research is often used to standardize data collection and generalize findings . Strengths of this approach include:

Replication

Repeating the study is possible because of standardized data collection protocols and tangible definitions of abstract concepts.

Direct comparisons of results

The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.

Large samples

Data from large samples can be processed and analyzed using reliable and consistent procedures through quantitative data analysis.

Hypothesis testing

Using formalized and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.

Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:

Superficiality

Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.

Narrow focus

Predetermined variables and measurement procedures can mean that you ignore other relevant observations.

Structural bias

Despite standardized procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.

Lack of context

Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

Reliability and validity are both about how well a method measures something:

Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Bhandari, P. (2023, June 22). What Is Quantitative Research? | Definition, Uses & Methods. Scribbr. Retrieved August 18, 2024, from https://www.scribbr.com/methodology/quantitative-research/

Is this article helpful?

Pritha Bhandari

Other students also liked, descriptive statistics | definitions, types, examples, inferential statistics | an easy introduction & examples, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

S371 Social Work Research - Jill Chonody: What is Quantitative Research?

Choosing a Topic
Choosing Search Terms
What is Quantitative Research?
Requesting Materials

Quantitative Research in the Social Sciences

This page is courtesy of University of Southern California: http://libguides.usc.edu/content.php?pid=83009&sid=615867

Characteristics of Quantitative Research

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numberic and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

The data is usually gathered using structured research instruments.
The results are based on larger sample sizes that are representative of the population.
The research study can usually be replicated or repeated, given its high reliability.
Researcher has a clearly defined research question to which objective answers are sought.
All aspects of the study are carefully designed before data is collected.
Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

Things to keep in mind when reporting the results of a study using quantiative methods :

Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
Explain the techniques you used to "clean" your data set.
Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
Always tell the reader what to look for in tables and figures .

NOTE: When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing datat does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods . Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Designs for Quantitative Studies

Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Compostion and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); A Strategy for Writing Up Research Results . The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

<< Previous: Finding Quantitative Research
Next: Databases >>
Last Updated: Jul 11, 2023 1:03 PM
URL: https://libguides.iun.edu/S371socialworkresearch

Quantitative and Qualitative Research

I NEED TO . . .

What is Quantitative Research?

What is Qualitative Research?
Quantitative vs Qualitative
Step 1: Accessing CINAHL
Step 2: Create a Keyword Search
Step 3: Create a Subject Heading Search
Step 4: Repeat Steps 1-3 for Second Concept
Step 5: Repeat Steps 1-3 for Quantitative Terms
Step 6: Combining All Searches
Step 7: Adding Limiters
Step 8: Save Your Search!
What Kind of Article is This?
More Research Help This link opens in a new window

Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014). The SAGE encyclopedia of action research (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017). The SAGE encyclopedia of communication research methods (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design? What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used. You will need to know how to decipher which design type is used. The following video will help you determine the quantitative design type.

<< Previous: I NEED TO . . .
Next: What is Qualitative Research? >>
Last Updated: Aug 14, 2024 3:26 PM
URL: https://libguides.uta.edu/quantitative_and_qualitative_research

University of Texas Arlington Libraries 702 Planetarium Place · Arlington, TX 76019 · 817-272-3000

Internet Privacy
Accessibility
Problems with a guide? Contact Us.

What is social science?

Quantitative research.

Quantitative research can measure and describe whole societies, or institutions, organisations or groups of individuals that are part of them. The strength of quantitative methods is that they can provide vital information about a society or community, through surveys, examinations, records or censuses, that no individual could obtain by observation.

Quantitative methodologies

Some of the most common quantitative research methodologies are described here. These methodologies are widely used in research funded by the Economic and Social Research Council (ESRC).

Cross-sectional studies

Cross-sectional studies are surveys undertaken at one point in time, rather like a photo taken by a camera. If the same or similar survey is repeated, we can get good measures of how society is changing.

Longitudinal studies

Longitudinal studies follow the same respondents over an extended period of time. They can employ both qualitative and quantitative research methods, and they follow the same group of people over time. For example, the Millennium Cohort Study has been keeping track of more than 11,000 children born between 2000 and 2002. Some of its many findings have shown how childhood factors such as poverty and birth weight can affect health and success at school as children get older.

Opinion polls

An opinion poll is a form of survey designed to measure the opinions of a target population about an issue, such as support for political parties and views about crime and justice, the economy or the environment.

Questionnaires

Questionnaires collect data in a standardised way, so that useful summaries can be made about large groups of respondents, such as the proportion of all young people of a given age who are bullied. Usually most questions are ‘closed response’, where respondents are given a range of options to choose from. Researchers have to be careful that the questions are not ‘leading’, that the options are comprehensive (they cover every possible answer) and are mutually exclusive, so that only one answer is correct for any respondent.

Social attitude surveys

Social attitude surveys ask more general questions about beliefs and behaviour, for example, how often people go to church, how much trust they have in the police force, whether they think children need a strict upbringing, how content they are with their life, how often they see other family members, and whether they are in employment.

Surveys and censuses

A census is a survey of everyone in the population. Because of the vast number of respondents, they are very expensive to organise. Governments now depend much more on sample surveys and administrative records, for example those created by a stay in hospital or tax returns. Surveys use a questionnaire to investigate respondents in a sample. Samples are chosen in such a way that they can represent a much larger population. A precise calculation can be made of how accurate the information from any sample is likely to be.

Further information

See our social science for schools resource page on the UK Government Web Archive for more information on social science methodologies.

Last updated: 31 March 2022

This is the website for UKRI: our seven research councils, Research England and Innovate UK. Let us know if you have feedback or would like to help improve our online products and services .

Social Sciences Research: Qualitative vs. Quantitative Research

What is Social Science?

Qualitative vs. Quantitative Research

Scholarly vs. Popular Sources This link opens in a new window
Evaluating Sources This link opens in a new window
Social Research Organizations
Anatomy of an APA Article
Social Sciences Databases
Sociology This link opens in a new window

Focus Groups

Social science research, or social research as it is sometimes called, stems from the natural sciences, and similar to its precursory field, it uses empirical, measurable outcomes to arrive at a conclusion. While natural scientists use the scientific method, social scientists often use quantitative research to go about their method of discovery.

Quantitative research "is the systematic examination of social phenomena, using statistical models and mathematical theories to develop, accumulate, and refine the scientific knowledge base" (" Quantitative Research," 2008 ). Quantitative research also provides "generalizable" findings, and according to Marlow (1993), is "characterized by hypothesis testing, using large samples, standardized measures, a deductive approach, and rigorously structured data collection instruments" (cited in "Quantitative Research").

As an alternative to quantitative research, qualitative research is also employed in social science research and is contrasted with quantitative research as such:

Insider rather than outsider
Person-centered rather than variable-centered
Holistic rather than particularistic
Depth rather than breadth

(" Qualitative Research, " 2008)

Trochim (2006), however, warns that researchers should not become so caught up in the polarizing differences between qualitative and quantiative research. He writes, "All quantitative data is based upon qualitative judgments; and all qualitative data can be described and manipulated numerically" (para. 3).

<< Previous: What is Social Science?
Next: Scholarly vs. Popular Sources >>
Last Updated: Jan 2, 2024 11:55 AM
URL: https://spcollege.libguides.com/ssresearch

Find My Rep

Doing Quantitative Research in the Social Sciences An Integrated Approach to Research Design, Measurement and Statistics

Thomas R Black - University of Surrey, Guildford, UK
Description

Focusing on the design and execution of research, key topics such as planning, sampling, the design of measuring instruments, choice of statistical text and interpretation of results are examined within the context of the research process.

In a lively and accessible style, the student is introduced to researc design issues alongside statistical procedures and encouraged to develop analytical and decision-making skills.

PART ONE: INTRODUCTION TO RESEARCH DESIGN The Nature of Enquiry Beginning the Design Process Initial Sources of Invalidity and Confounding Basic Designs Identifying Populations and Samples Additional Sources of Confounding by the Measurement Process and Interactions Refining the Designs PART TWO: MEASUREMENT DESIGN Principles of Measurement and Collecting Factual Data Measuring Attitudes, Opinions and Views Measuring Achievement Evaluating Data Quality Determining Instrument Reliability and Validity

`There is much that is excellent about this book. If all educational researchers had studied it thoroughly, especially the sections on research design, representative samples and confounding variables, then there might be less publication of sweeping statements based on insufficient evidence' - British Educational Research Journal

Very nice and readable book. I recommend it to all my students and refer to it frequently in my teaching

Not an easy read for novices

I personally found this book a very interesting read, but unfortunately this is not pitched at an appropriate level for our students. This is not a comment on the book, rather the structure of our course(s) and the outputs that our students are expected to produce. Many thanks.

Doing quantitative research in the social sciences an integrated approach to research design, measurement and statistics contains 22 chapters which are divided into six main parts. Part one introduction to research design consists of seven chapters which introduce the reader to the nature of data in terms of its multiple sources and discusses the differences between empirical and non-empirical approaches to gathering data, as well as the advantage of using a scientific approach to conducting research with respect to using rigorous and methodical processes and techniques. Also, covered in part one are the issues researchers face when planning and designing research with regards to answering research questions and providing evidence of the validity of hypotheses being tested, in addition to working with and measuring variables. This section concludes with what the researcher should consider when identifying population(s) from which to sample from and part one presents a summary of the techniques which can be employed when selecting a sampling strategy, as well as key issues to consider associated with each sample strategy. Part two measurement design consists of four chapters which focus mainly on attitude surveys measuring attitudes, opinions and views in relation to what the results from these types of instruments indicate and reveal about a given area or phenomena. Also covered in this section is the importance of construct validity with respect to enhancing the reliability of research designed instruments for gathering and measuring data, in addition to, checking the reliability and validity of instruments. Part three turning data into information using statistics consists of three chapters which discuss the advantages of using a spreadsheet to generate frequency tables, graphs and charts, as well as how to prepare data for comparing different groups of data. The theory discussed within this section relate to probability and statistical significance with respect to the types of data which can be analysed and the effect the distribution of the data can have on the results in relation to the degree which statistical inference can be inferred. The effect that power and errors can have on data with regards to setting up significance levels and testing hypotheses are also covered in this section. Part four ex post facto, experimental and quasi-experimental designs: parametric tests consists of four chapters and discuss the differences between experimental and quasi-experimental research designs and the types of parametric tests which can be applied when analysing and interpreting data generated from making comparisons between groups when comparing means differences. Part five nonparametric tests: nominal and ordinal variables consists of two chapters which present an alternative to using parametric tests and discusses when to use nonparametric tests and the types of tests that can be used as a nonparametric equivalent to parametric tests for comparing medians as apposed to means differences. Part six describing non-causal relationships consists of two chapters which cover correlation and the differences between experimental and nonexperimental research and when correlation should be used, as well as the benefits of using scatter diagrams to aid in the interpretation of correlations by representing the results graphically to determine the strength of the relationship between two variables. Regression and linear regression equations are discussed in relation to mathematical theory, a well as using two dimensional and three dimensional scatter diagrams to display frequencies and standard deviations. Appendix provides a useful introduction to using spreadsheets for presenting data analysed diagrammatically and how to amend or update information to a completed spreadsheet of data. The appendix also presents a helpful set of statistical tables showing: (1) areas under the normal distribution; (2) critical values for significance for a one-tailed test; (3) critical values for the F-distribution; (4) critical values for F-distribution as well as other useful tables. A glossary of mathematical symbols, equations and excel functions along with a definition and description of their function are provided, as well as a bibliography of helpful references. Helpful check lists are provided within chapters for the reader to check their knowledge and understanding of the information being presented in chapters. This text covers the theory behind conducting quantitative research in the social sciences. The main focus of this book is on the theory underpinning research design and analysis using statistical techniques to test data gathered from survey questionnaires. The reading level of this text is accessible for undergraduate, postgraduate and doctorial students, as well as researchers working with quantitative data on research projects. This book is recommended as essential reading and reference material for anyone using a quantitative approach to research within the social science.

A well written text-book that gives learners and teachers of quantitative research an in-depth understanding of the quantitative paradigm.

Provides a good overview of all statistical methods

This book has met my expectations, additionaly I would be happy if it has SPSS applications, but excel applications are also fine. Thanks for sending it. I'll benefit it for my course.

Budget cuts have forced us to not adopt a BSN program at this time.

this text is recommended for student much further in their masters degree study. it is very detailed and includes some intense statistical tests. I have made my students aware of it to consult as they progress through the masters level programme

Preview this book

For instructors.

Please select a format:

Select a Purchasing Option

Electronic Order Options VitalSource Amazon Kindle Google Play eBooks.com Kobo

Related Products

Home » Quantitative Research – Methods, Types and Analysis

Quantitative Research – Methods, Types and Analysis

Table of Contents

Quantitative Research

Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.

Quantitative Research Methods

Quantitative Research Methods are as follows:

Descriptive Research Design

Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.

Correlational Research Design

Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.

Quasi-experimental Research Design

Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.

Survey Research

Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.

Quantitative Research Analysis Methods

Here are some commonly used quantitative research analysis methods:

Statistical Analysis

Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.

Regression Analysis

Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.

Factor Analysis

Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.

Structural Equation Modeling

Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.

Time Series Analysis

Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.

Multilevel Modeling

Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.

Applications of Quantitative Research

Quantitative research has many applications across a wide range of fields. Here are some common examples:

Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.

Characteristics of Quantitative Research

Here are some key characteristics of quantitative research:

Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.

Examples of Quantitative Research

Here are some examples of quantitative research in different fields:

Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.

How to Conduct Quantitative Research

Here is a general overview of how to conduct quantitative research:

Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.

When to use Quantitative Research

Here are some situations when quantitative research can be appropriate:

To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.

Purpose of Quantitative Research

The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:

Description : To provide a detailed and accurate description of a particular phenomenon or population.
Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.

Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.

Advantages of Quantitative Research

There are several advantages of quantitative research, including:

Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.

Limitations of Quantitative Research

There are several limitations of quantitative research, including:

Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Explanatory Research – Types, Methods, Guide

Ethnographic Research -Types, Methods and Guide

Textual Analysis – Types, Examples and Guide

Applied Research – Types, Methods and Examples

Correlational Research – Methods, Types and...

Triangulation in Research – Types, Methods and...

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
J Korean Med Sci
v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Quantitative research questions	Quantitative research hypotheses
Descriptive research questions	Simple hypothesis
Comparative research questions	Complex hypothesis
Relationship research questions	Directional hypothesis
	Non-directional hypothesis
	Associative hypothesis
	Causal hypothesis
	Null hypothesis
	Alternative hypothesis
	Working hypothesis
	Statistical hypothesis
	Logical hypothesis
	Hypothesis-testing
Qualitative research questions	Qualitative research hypotheses
Contextual research questions	Hypothesis-generating
Descriptive research questions
Evaluation research questions
Explanatory research questions
Exploratory research questions
Generative research questions
Ideological research questions
Ethnographic research questions
Phenomenological research questions
Grounded theory questions
Qualitative case study questions

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Quantitative research questions
Descriptive research question
	- Measures responses of subjects to variables
	- Presents variables to measure, analyze, or assess
	What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training?
Comparative research question
	- Clarifies difference between one group with outcome variable and another group without outcome variable
	Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)?
	- Compares the effects of variables
	How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells?
Relationship research question
	- Defines trends, association, relationships, or interactions between dependent variable and independent variable
	Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic?

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Quantitative research hypotheses
Simple hypothesis
	- Predicts relationship between single dependent variable and single independent variable
	If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered.
Complex hypothesis
	- Foretells relationship between two or more independent and dependent variables
	The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable).
Directional hypothesis
	- Identifies study direction based on theory towards particular outcome to clarify relationship between variables
	Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects.
Non-directional hypothesis
	- Nature of relationship between two variables or exact study direction is not identified
	- Does not involve a theory
	Women and men are different in terms of helpfulness. (Exact study direction is not identified)
Associative hypothesis
	- Describes variable interdependency
	- Change in one variable causes change in another variable
	A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable).
Causal hypothesis
	- An effect on dependent variable is predicted from manipulation of independent variable
	A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient.
Null hypothesis
	- A negative statement indicating no relationship or difference between 2 variables
	There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2).
Alternative hypothesis
	- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables
	The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2).
Working hypothesis
	- A hypothesis that is initially accepted for further research to produce a feasible theory
	Dairy cows fed with concentrates of different formulations will produce different amounts of milk.
Statistical hypothesis
	- Assumption about the value of population parameter or relationship among several population characteristics
	- Validity tested by a statistical experiment or analysis
	The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2.
	There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan.
Logical hypothesis
	- Offers or proposes an explanation with limited or no extensive evidence
	If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less.
Hypothesis-testing (Quantitative hypothesis-testing research)
	- Quantitative research uses deductive reasoning.
	- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses.

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative research questions
Contextual research question
	- Ask the nature of what already exists
	- Individuals or groups function to further clarify and understand the natural context of real-world problems
	What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems)
Descriptive research question
	- Aims to describe a phenomenon
	What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities?
Evaluation research question
	- Examines the effectiveness of existing practice or accepted frameworks
	How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility?
Explanatory research question
	- Clarifies a previously studied phenomenon and explains why it occurs
	Why is there an increase in teenage pregnancy (phenomenon) in Tanzania?
Exploratory research question
	- Explores areas that have not been fully investigated to have a deeper understanding of the research problem
	What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic?
Generative research question
	- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions
	How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative?
Ideological research question
	- Aims to advance specific ideas or ideologies of a position
	Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care?
Ethnographic research question
	- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings
	What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis?
Phenomenological research question
	- Knows more about the phenomena that have impacted an individual
	What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual)
Grounded theory question
	- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups
	What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed?
Qualitative case study question
	- Assesses a phenomenon using different sources of data to answer “why” and “how” questions
	- Considers how the phenomenon is influenced by its contextual situation.
	How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan?

Qualitative research hypotheses
Hypothesis-generating (Qualitative hypothesis-generating research)
	- Qualitative research uses inductive reasoning.
	- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis.
	- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach.

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Which is more effective between smoke moxibustion and smokeless moxibustion?	“Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.”	1) Vague and unfocused questions
			2) Closed questions simply answerable by yes or no
			3) Questions requiring a simple choice
Hypothesis	The smoke moxibustion group will have higher cephalic presentation.	“Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group.	1) Unverifiable hypotheses
		Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group.	2) Incompletely stated groups of comparison
		Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.”	3) Insufficiently described variables or outcomes
Research objective	To determine which is more effective between smoke moxibustion and smokeless moxibustion.	“The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.”	1) Poor understanding of the research question and hypotheses
Research objective			2) Insufficient description of population, variables, or study outcomes

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

Variables	Unclear and weak statement (Statement 1)	Clear and good statement (Statement 2)	Points to avoid
Research question	Does disrespect and abuse (D&A) occur in childbirth in Tanzania?	How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania?	1) Ambiguous or oversimplistic questions
Research question			2) Questions unverifiable by data collection and analysis
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania.	1) Statements simply expressing facts
Hypothesis	Disrespect and abuse (D&A) occur in childbirth in Tanzania.	Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania.	2) Insufficiently described concepts or variables
Research objective	To describe disrespect and abuse (D&A) in childbirth in Tanzania.	“This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.”	1) Statements unrelated to the research question and hypotheses
Research objective			2) Unattainable or unexplorable objectives

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g001.jpg

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g002.jpg

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

Study Postgraduate

Quantitative social research (msc) (2020 entry).

How to apply
Get a prospectus
Course Code
Course Type
Postgraduate Taught
Qualification
Full-time: 1 year
Part-time: 2 years
Department of Study
Location of Study
University of Warwick

Quantitative Social Research MSc will equip you with a range of advanced skills in data management. The University of Warwick's Sociology Department, ranked 4th in the UK, is home to leading experts who will train you to use quantitative methods to examine societal trends and social behaviours.

Course Overview

Offered by the Department of Sociology in conjunction with the Warwick Q-step Centre, this course will equip you with a range of advanced skills in data management and analysis, alongside a thorough grounding in key theoretical and substantive sociological topics. You’ll develop a comprehensive understanding of methodological and analytical aspects of social research, and the ability to put them into practice in a variety of work settings.

This course consists of core modules on data management and analysis, and a research dissertation on a topic of your own interest. You’ll be able to explore particular specialist areas in more depth by choosing optional sociological modules.

We are making some exciting changes to our Quantitative Social Research (MSc) for 2020 entry. The core and optional modules for this degree are currently undergoing approval through the University's rigorous academic processes. As modules are approved, they will be included in the module list on this webpage. It is therefore very important that you check this webpage for the latest information before you apply and prior to accepting an offer.

Please check this webpage for the latest information before you apply and prior to accepting an offer.

Teaching and Assessment

Each of our MA courses has specified core modules which will be studied alongside a range of optional modules. You’ll be required to choose three optional modules from our departmental list. All our MA courses follow a consistent structure meaning that you will follow a programme of taught modules, followed by a 15,000 word dissertation.

Contact Hours

Typically, each module will contain twenty hours of teaching. But you will also receive support, such as dissertation supervision, etc.

Class Sizes

Class sizes can range between 6 to 30 students

If you’re a full-time student you’ll undertake taught modules, and submit assessed essays for these, during the academic terms: autumn, spring and summer terms. You will also begin planning your dissertation and generally you will undertake your supervision sessions for this with your agreed supervisor during the summer term. As long as you pass your taught components, you will then focus on completion of your MSc dissertation in the summer months of July and August.

Entry Requirements

Minimum requirements 2:i undergraduate degree (or equivalent) in a related subject

English language requirements Band B IELTS overall score of 7.0, minimum component scores of two at 6.0/6.5 and the rest at 7.0 or above

International Students We welcome applications from students with other internationally recognised qualifications. For more information please visit the international entry requirements page .

Fees, Funding and Scholarships

For up-to-date information concerning fees, funding and scholarships for Home/EU and Overseas students please visit Warwick's Fees and Funding webpage .

Scholarships

Commonwealth Shared Scholarships - full overseas tuition, maintenance and other expenses for students applying for this course only. Sociology Departmental Scholarship - £5,000 for full-time applicants and £2,500 over 2 years for part-time applicants. 10 awards available: 5 for Home and EU candidates, 5 for Overseas candidates.

Additional Course Costs

This course may also include additional course costs.

Graduates from these courses have gone on to work for employers including: Coventry University, KPMG, Oxfam and Waitrose. They have pursued roles such as: business and financial project management professionals; higher education teaching professionals; IT project and programme managers; legal professionals and research and development managers.

Our department has a dedicated professionally qualified Senior Careers Consultant offering impartial advice and guidance together with workshops and events throughout the year. Previous examples of workshops and events include:

Make Your Mark - Careers with a degree in Sociology
Working for More than Profit
Warwick careers fairs throughout the year
Your Sociological future: Sociology Alumni Evening
My Sociological Future- What next? Career planning for undecided Sociology finalists

There are a number of different ways to visit the University of Warwick throughout the year. We host bespoke PG visits, where you can talk directly with your chosen department and explore our campus through a personalised tour. Some departments also host their own events and open days, where you can learn more about your department or course of study. To find out more about all of these opportunities, visit our Postgraduate Visits page.

Related Taught Courses

Social Research (MA)

Sociology (MA)

Social and Political Thought (MA)

Gender and International Development (MA)

Ph.D. Program

Ph.d. research design and methods courses, this is a list of current and projected annual courses at the jackson school and other departments at uw. the list is updated at the start of each academic quarter by the ph.d. program. for more information, please contact us at [email protected]., projected courses 2024-25.

In addition to the Jackson School courses listed below, you will find relevant courses in a number of departments and schools such as American Ethnic Studies, Anthropology, Communications, Geography, History, Law, Marine and Environmental Affairs, Political Science, Public Health, Sociology, Social Work and others. Contact the JSIS Ph.D. Program GPC for approval to take a class that is not listed in the handbook as a course requirement. See Time Schedule for a complete list of course offerings.

Approved Methods Courses

Qualitative methods courses.

A comprehensive list of qualitative research methods classes offered at UW is on the Qualitative Multi-Method Research Initiative site . Check this site to find a relevant methods class and to learn more about the optional QUAL Concentration track this is available for graduate students.

Quantitative Methods Courses

A list of quantitative research methods classes offered at UW is on the Center for Statistics and Social Sciences site . You can also find quantitative methods classes in other departments .

The Center for Social Science Computation and Research

A list of methods workshops offered through CSSCR is online: http://csscr.washington.edu/courses.html.

Center for Studies in Demography & Ecology

The CSDE Demographic Methods Graduate Certificate Program is the academic pathway to advanced population research at UW. See the website for course listings and certificate requirements.

Student Resources

Writing Center
Study Abroad Office

JSIS Ph.D. Program

Jesús hidalgo.

Graduate Programs Manager Box 353650 Seattle, WA 98195

[email protected]

Meet an Adviser

Graduate Program Information Request

Let us know what program you are interested in and we will email you more information directly.

Information Request Form

The Student Experience
Financial Aid
Degree Finder
Undergraduate Arts & Sciences
Departments and Programs
Research, Scholarship & Creativity
Centers & Institutes
Geisel School of Medicine
Guarini School of Graduate & Advanced Studies
Thayer School of Engineering
Tuck School of Business

Campus Life

Diversity & Inclusion
Athletics & Recreation
Student Groups & Activities
Residential Life

Quantitative Social Science

Program in quantitative social science.

[email protected] Contact & Department Info Mail
Undergraduate
What is it like to write a QSS thesis?
Questions about the curriculum
What is it like to complete a one quarter QSS research project?
What can I do with a QSS degree?
Wisdom from alumni
Course Schedule by Term
QSS student prize
Class of 2024
Class of 2023
Class of 2022
Class of 2021
Class of 2020
Class of 2019
Class of 2018
Selected theses 2022-23
Selected theses 2021-22
Selected theses 2020-21
Selected theses 2019-20
Selected theses 2018-19
Selected theses 2017-18
Selected theses 2016-17
Selected theses 2015-16
Selected 2018-19 Projects
Selected 2017-18 projects
Selected 2016-17 projects
Faculty-Student Collaborations
About the Program
General questions
Questions about research
Student perspectives on QSS
News & Events
News & Events
Dartmouth Interdisciplinary Network Research Group
Past Events
Faculty, Fellows, Affiliates & Staff
Alumni Stories
Tell Us Your Story

Search form

Qss 82 one quarter research projects, spring 2024.

Top Left: Alexander Gu, Bottom Left: Alexander Wojcik, Right: Andy Feng

Left: Sade Francis, Top Right: Vikram Strander, Bottom Right: Grace Faulkner

On Wednesday, May 29, students majoring and minoring in Quantitative Social Science (QSS) showcased their research at a poster session, presenting the results of one-quarter projects completed in QSS 82 . This course, led by Senior Lecturer Robert Cooper in Spring 2024, culminated in the presentation of seven diverse posters.

The QSS 82 poster session offered seniors a platform to exhibit their hard work. Throughout the quarter, each student formulated a research question, developed theoretical expectations, and tested these using statistical methods. The topics they chose spanned a wide array of social science issues, all analyzed through the lens of quantitative data.

This spring's presentations covered a broad spectrum of subjects, from the dynamics of NIL deals in collegiate sports to the impact of COVID-19 on the luxury industry. Other topics included the influence of audience ratings on movie box office performance, the role of abortion policy in political realignment, and the effects of seeding, tournament format, and serving differences on match success in professional tennis. The range of research topics highlights the emphasis QSS on the diverse application of quantitative and computational methods in social science.


Grace Faulkner	Unveiling the Dynamics of NIL Deals in Collegiate Sports
Andy Feng	The Impact of Audience Ratings on Box Office: A CinemaScore Analysis
Sade Francis	A Climate for Better Mental Health: Does Climate Change Increase Suicide Risk in Marginalized Populations?
Alexander Gu	Analyzing the Impacts of Global Temperature Climate Change on Migration Patterns in States of India
Vikram Strander	The Impact of Seeding, Tournament Format, and Serving Differences on Match Success in Professional Tennis
Alexander Wojcik	Left, Right, and Center: Abortion Policy as Motivation for Realignment Towards the Political Left
Avery Yan	Analysis of the Impact of COVID-19 on the Luxury Industry

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Book Title: Graduate research methods in social work

Subtitle: A project-based approach

Authors: Matthew DeCarlo; Cory Cummings; and Kate Agnelli

Cover image for Graduate research methods in social work

Book Description: Our textbook guides graduate social work students step by step through the research process from conceptualization to dissemination. We center cultural humility, information literacy, pragmatism, and ethics and values as core components of social work research.

Book Information

Graduate research methods in social work Copyright © 2021 by Matthew DeCarlo, Cory Cummings, Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Social work

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts
Open access
Published: 12 August 2024

Evaluation of didactic units on historical thinking and active methods

Pedro Miralles-Sánchez ORCID: orcid.org/0000-0002-2436-3012 1 ,
Jairo Rodríguez-Medina ORCID: orcid.org/0000-0002-6466-5525 2 &
Raquel Sánchez-Ibáñez 1

Humanities and Social Sciences Communications volume 11 , Article number: 1032 ( 2024 ) Cite this article

225 Accesses

Metrics details

The purpose of this study is to evaluate the effects of an implementation of eight didactic units on historical thinking and active methods as part of a teacher training programme. All this with four specific objectives that try to find out changes in the methodology, motivation, satisfaction and learning of the students. To this end, the research is carried out by means of a mixed method using quantitative data, obtained from a pretest/posttest, and qualitative data, obtained from a focus group and interviews. The target groups of the teaching units are secondary and high school students aged between 13 and 18 years. A total of 114 students of these students participated in the data collection with a pretest/posttest, six master students in the focus group, and three teachers and three secondary and high school students were interviewed. The results obtained indicated that significant differences of medium effect were found in the pre and post phase factor in learning and satisfaction, and of large effect in methodology and motivation. As for the gender factor, significant differences of small effect were found in motivation and satisfaction, with higher values for women. The positive statements of both master’s students and high school students and teachers were quite striking, although the limitations and difficulties must be highlighted. It is concluded that the design of this type of didactic units has meant a significant improvement, achieving that the students have developed a notorious improvement in their perception of the objectives studied.

Concepts for historical and geographical thinking in Sweden’s and Spain’s Primary Education curricula

The impact of content knowledge on the adoption of a critical curriculum model by history teachers-in-training.

Primary and secondary school teachers’ perceptions of their social science training needs

Introduction.

Research in history didactics has distinguished two types of historical content. On the one hand, substantive or first-order content. These are those which refer both to concepts or principles and to specific historical dates and events. On the other hand, strategic, second-order content or historical meta-concepts as methodological concepts. These are related to the historian’s skills, the search for, selection and treatment of historical sources, empathy or historical perspective, related to the definition of historical thinking (Sáiz and Gómez, 2016 ). This didactic approach aims for students to learn to think historically by deploying different strategies and competences to analyse and respond to different historical questions and to understand the past in a more complex way. These competences and strategies are related to the search for, selection and treatment of historical sources, empathy, multi-causal explanation, or historical perspective; in short, the functions of a historian (Peck and Seixas, 2008 ; Seixas and Morton, 2013 ). These concepts are variable and do not form a closed and invariable list, but each author gives greater importance to certain aspects (Gómez Carrasco et al., ( 2017 )).

Since the late 1980s, an effort has been made in the British field to analyse second-order concepts in students’ argumentation. Here the Concepts of History and Teaching Approaches project (Lee et al. 1996 ) stands out, which investigated the historical concepts that students should acquire. At the same time, in the USA, through Wineburg ( 2001 ), work began with cognitive psychology techniques (experts and novices) to investigate the skills that students should acquire, with the well-known historical thinking and its competences finally being developed by mainly Canadian and American authors (Ercikan and Seixas, 2015 ; Seixas and Morton, 2013 ; VanSledright, 2014 ; Wineburg et al., 2013 ). For their part, the work of Chapman ( 2011 ) and the Constructing History 11–19 project (Cooper and Chapman, 2009 ) delve deeper into this line of reasoning in the use of sources, a thematic field also addressed in other countries such as the Netherlands (Van Drie and Van Boxtel, 2008 ) and Chile (Henríquez and Ruíz, 2014 ).

The importance of teaching historical thinking in the classroom lies in the fact that historical thinking does not develop naturally, but needs explicit teaching (Wineburg, 2001 ). To develop these competences, the introduction of the historian’s method and techniques and historical awareness are key elements, with appropriate techniques and instruments to assess them (Domínguez, 2015 ). To develop them, a methodological change in the classroom is necessary, as is already being proposed and discussed in countries such as Portugal (Gago, 2018 ), Spain (Navarro and De Alba, 2015 ) or the United Kingdom (Smith, 2019 ). This change implies moving from the current dominance of expository teaching strategies to a greater presence of enquiry strategies that help to promote the development of independence, critical thinking, and autonomous learning in students.

Working with historical sources, which can begin even earlier, is valued positively by students in upper secondary education, as it promotes a research experience in which students construct their knowledge about the past (Prieto, Gómez and Miralles, 2013 ), however, this type of experience is not usually abundant in classrooms at this stage in Spain. The abuse of the lecture and the passive role reserved for students ends up making them, for the most part, limit themselves to studying what is offered in class by not seeking information from other sources and memorising the information they receive (Sáiz and López-Facal, 2015 ). Consequently, it is very difficult to create critical citizenship in students, as they may believe everything the teacher tells them, as they are not familiar with enquiry (Guirao, 2013 ).

When it comes to identifying teaching models, it is worth highlighting the line of research developed by Trigwell and Prosser ( 2004 ) based on interviews with teachers and a questionnaire called Approaches to Teaching Inventory (ATI) (Trigwell et al., 2005 ). They identified four different conceptions of teaching and three methodologies, establishing five approaches which can be grouped into three broad models or ways of teaching. In the first model, the role of the teacher is greater, since the importance lies in the transmission of content, students assume a passive role, limiting themselves to receiving and memorising the knowledge transmitted by teachers, thus establishing a unidirectional relationship, without considering their experience, previous knowledge, characteristics or context. The most used methodological strategy is the master class and the main resources used are the textbook and class notes. In addition, a final examination of the learning contents is usually established (Hernández et al., 2012 ; Guerrero-Romera et al., 2022 ).

On the other hand, there is learner-centred teaching which differs from the previous one in that the teacher’s intention is to provoke conceptual change and intellectual growth in the learner. Thus, the teacher acts as a guide, guiding students in the process of constructing their own knowledge, encouraging their conceptions, and providing them with opportunities to interact, debate, investigate and reflect. The aim of this model is for students to learn content by questioning and reflecting on it. The strategies employed are active and inquiry based. In contrast to the previous model, which encourages competitiveness and individualism, this approach favours interaction and cooperation between the individuals involved in the teaching and learning process and prioritises continuous assessment (Vermunt and Verloop, 1999 ; Kember and Kwan, 2000 ; Trigwell et al., 2005 ; Henze and van Driel, 2011 ). Finally, there is a third, intermediate model based on teacher-student interaction, although it should be noted that there is a hierarchical relationship between the different approaches, with each including elements of the previous one (Guerrero-Romera et al., 2022 ).

Evaluative studies of formative processes such as this one are seeing an increase in the field of history education especially in terms of changing the conceptual model of history teaching (Carretero et al., 2017 ; Metzger and Harris, 2018 ). Some work, such as that being carried out in the Netherlands, focuses on evaluative research that is more focused on teaching practice (De Groot-Reuvekamp et al., 2018 ; Van Straaten et al., 2018 ). Regarding the evaluation of historical thinking effects, we can recently highlight Tirado-Olivares et al. ( 2024 ) relating it to academic performance, or Bartelds et al. ( 2020 ) highlighting the importance of historical empathy. It is also worth highlighting the research carried out by the University of Murcia (Gómez et al., 2021a ; Gómez et al., 2021b ; Rodríguez et al., 2020 ), which implemented training units focused on historical thinking skills and changes in the way of teaching. This research therefore seeks to be a significant improvement compared to traditional methods used in the teaching of social sciences, as it seeks to develop essential skills for critical thinking and citizenship training, and to evaluate its effectiveness through rigorous methods and a scientific approach. All this to encourage a critical spirit and autonomous learning and therefore the formation of critical and independent citizens who know how to judge for themselves the vicissitudes that civic life in democracy demands of them.

The main objective of this article is to detect if there are significant changes in students after the design and implementation of eight didactic units (DU from now on) to promote the learning of historical thinking skills through active teaching methods. To achieve the objective, it has been divided into the following specific objectives:

O1. To analyse whether there are differences in the students’ perception of the methodology of teaching history, after the implementation of the DU that promotes historical thinking through active methods Table 1 .

O2. To identify if there are differences in the students’ perception of motivation during the teaching process, after the implementation of the DU that promote historical thinking through active methods Table 2 .

O3. To find out if there are differences in the students’ perception in relation to the level of satisfaction with the teaching process, after the implementation of the DU that promote historical thinking through active methods Table 3 .

O4. To find out if there are differences in the students’ perception in relation to the level of effectiveness and transfer of the learning achieved, after the implementation of the DU that promote historical thinking through active methods.

Research design

This is an evaluative type of DU research of historical thinking and active methods with a mixed explanatory approach and a quasi-experimental A-B design. The research method is therefore mixed, qualitative, and quantitative data have been collected and analysed in a rigorous way in response to the research objective, organising them into specific research objectives and integrating the two forms of data and their results into conclusions framed in the theory and scientific production studied (Creswell & Plano Clark, 2017 ). The selection of the eight DU was made at random, as we have worked with the students who have been tutored by us during the internship period. On one hand, a quantitative analysis of the data obtained by means of a Likert-type questionnaire (1–5) was carried out. Questionnaire designs are extremely common in the field of education, as they can be applied to a multitude of problems and allow data to be collected on many variables and outcomes to be measured (Sapsford & Jupp, 2006 ). On the other hand, the decision was to apply a qualitative exploratory method through a focus group with master’s students who applied the DU and interviews with practising teachers and students who witnessed these units (supplementary material, Figs. 1 – 3 ). Interviews are useful when you want subjects to describe complex phenomena and facts that are the object of study (Pérez-Juste et al., 2012 ), as well as focus groups. The focus group was recorded via an online Zoom meeting (Archibald et al., 2019 ) and then transcribed using artificial intelligence (Notta AI), while the interviews were answered on the spot individually in writing.

The quantitative analysis (R Core Team, 2023 ), a repeated measures mixed factorial design with one within-subjects factor (the time of assessment) and one between-subjects factor (gender) was used. The within-subject factor has two levels (pretest and posttest) and the between-subject factor has three levels (female and male). The dependent variables were the scores obtained in each of the subscales of the questionnaires Secondary school students’ assessment of History teaching and Secondary school students’ opinion of the implementation of the History training unit (supplementary material Figs. 4 and 5 ). For the qualitative analysis, a descriptive analysis was carried out using the qualitative research software Atlas.Ti 23, which is widely used in research in the field of Social Science Didactics (Rüssen, 1997 ; Sánchez-Ibáñez, Martínez-Nieto ( 2015 )). As a complement to this software, the ChatGPT tool has also been used to improve the accuracy of the codes and data analysis, as an aid both in designing the codes of the transcripts, organising the main conclusions obtained from the coding of the participants’ responses (Lopezosa & Codina, 2023 ), and finding out the percentage of occurrence of words. All codes are open and non-exclusive, so that the same response can be associated with more than one code.

Participants

This is a non-probabilistic convenience sample composed in the quantitative analysis of 114 young people aged between 12 and 20 years (M = 15.63, SD = 1.54). Fifty-one males (44%) and 65 females (56%) participated in the pre-test. In the post-test 50 males (44%) and 64 females (56%) participated. Of these, 14 men and 10 women were from the first year of high school, 5 men and 18 women were from the second year of high school, 11 men and 8 women were from the second year of ESO, 14 men and 21 women from the third year of ESO and 7 men and 10 women from the fourth year of ESO (Fig. 1 ). As for the focus group, 6 students of the master’s degree in teaching, 2 men and 4 women aged between 22–45 years, participated. The interviews were conducted with 3 secondary school teachers, 2 men and 1 woman aged 40–60 and 3 pupils aged 13–17 respectively.

Distribution by Gender and Grade.

Instruments

For the collection of quantitative data, two closed-response questionnaires based on a Likert-type scale (1–5) were used. The questionnaires given to pupils were entitled Assessment of Secondary School pupils on the teaching of History (pretest) and Opinion of Secondary School pupils on the implementation of the History unit (posttest). The questionnaires have 37 items divided into four categories corresponding to each of the specific research objectives: Assessment of the implementation of the DU in the teaching/learning process; Assessment of student motivation in an innovative DU; Analysis of student satisfaction with an innovative DU; Analysis of student learning and its results to check whether the DU has been effective (supplementary material Figs. 4 and 5 ). For its part, the qualitative analysis was used to complement the quantitative research by relating its questions to the objectives and thus elucidating the impact of the OD. It consists of both a focus group with trainee teachers consisting of nine questions and interviews with classroom tutors and students with a total of sixteen questions (supplementary material Figs. 1 – 3 ).

Validation of these instruments has been essential to ensure that the data collected are accurate and reliable, through peer review and pilot testing on a small group of participants to assess the effectiveness and relevance of the questions and observation procedures (Gómez et al., 2021 a; Rodríguez et al., 2020 ; Miralles-Sánchez et al., 2023 ).

This research is based on a research project consisting of four phases: prior observation of the classroom (December 2022-February 2023), design of training units (March-April 2023), implementation of training units (May-July 2023) and evaluation of results (September 2023-July 2024). The design of the DU and the data collection were thanks to a training programme implemented during the academic year 2022/23 in a Spanish university for students of the Master’s degree in teacher training in the speciality of Geography, History and History of Art. Held from 10 January to 17 March 2023, the duration of the activity involved a total of 18 face-to-face hours where students attended a series of lectures given by expert lecturers in Didactics of Social Sciences with the aim of helping students to carry out a Master’s Final Project (MFP) based on the implementation and evaluation of a didactic DU on historical thinking and active methods during the internship period of the Master’s. The activity consisted of 6 sessions: presentation and approach of the MFP, concepts of historical thinking, teaching methods and active evaluation processes, quantitative and qualitative analysis of data in educational research, and guidelines for the presentation and bibliography of the MFP.

O1. To analyse whether there are differences in the students’ perception of the methodology of teaching history, after the implementation of the DU that promotes historical thinking through active methods

In relation to this objective, the data obtained from the quantitative instruments show an approximately normal distribution of methodology scores. No significant differences were observed between sexes (MH = 35.93, SD = 5.60; MM = 36.43, SD = 5.83) in the initial (pre) assessment (F (1,112 = 5.83). 83) at baseline (pre) assessment (F (1,112) = 0.21, p = 0.64) and no gender differences between groups (MH = 43.32, SD = 6.91; MM = 44.53, SD = 7.58) were observed at posttest (F (1,112) = 0.77, p = 0.38).

The repeated measures analysis of variance did not produce a significant interaction effect result between sex (Female, Male) and phase (Pre vs Post) (F (1,108) = 0.08, p = 0.77). However, a significant effect of the phase (Pre vs Post) factor was observed (F (1,108) = 91.88, p < 0.01) with a large effect size (partial η2 = 0.26). Figure 2 shows the result graphically.

Differences in Methodology Scores by Gender and Phase.

The master’s students emphasise that none of them were previously familiar with the theory of historical thinking, having recently learned it in class, although some had experience of teaching with active methods. They emphasise the importance of interactive and participatory methods, as well as the crucial role of the teacher in the educational experience, recognising positive changes in current teaching, although with divergent opinions on the influence of students on methodology. The positive experience with students and the inclusion of relevant points in teaching are highlighted, but the persistence of traditional methods that are not very active and the resistance of some students to participatory methods are criticised, representing a challenge in contemporary teaching Fig. 3 .

Changes and improvements in DU according to master’s students.

Significant statements

“So I think that the figure of the teacher will always be…. All that helps, all the technique, everything we learn and all that, but I think that the figure of the teacher is fundamental, it is important.” - He emphasises the importance of the role of the teacher and the relationship that the teacher establishes with the students.

“I think it’s changing a lot because before you went to class and the teacher would give you a lecture or whatever and the students were very dispersed, but I think that is changing now, and as we bring in new generations, I think it’s going to change a bit more.” - He sees a positive change in the way history teaching is approached.

“No, I think so, in a certain sense it has changed, because it is true that at secondary school, when you are a teenager you see two types of teachers, a teacher who practically limits himself to lecturing you and that’s it, and others who question you more.” - He expresses that teaching has not changed completely, suggesting that there are still teachers who adopt fewer interactive approaches.

“I’ve had bad history teachers all my life, you know, the kind that came in and talked to me unfunnily about things that had happened and that was it.” - Reflects a past negative experience with less committed history teachers.

“So, it’s true that when I was a student, I felt that sometimes history classes were very theoretical and so on, but it’s true that when I came to class as a non-student, I saw that sometimes teachers have to adopt this methodology because otherwise it’s impossible.” - She acknowledges that sometimes teachers are forced to adopt fewer interactive methods due to student resistance.

“My internship tutor said that students are not used to any of this and that in reality many are comfortable in this role of going to the institute like someone who goes to the cinema, to see the teacher or tell the story and then I’ll study and do the exam and that’s it.” - He points to the resistance of some students to more participatory methods as a challenge in today’s teaching.

On the other hand, they stress the crucial role of an active and engaging methodology to enhance the learning experience, with the consideration that there is no single methodology effective for all groups. However, they also mention the importance of dosing or reducing content to avoid information overload, as well as the need for continuous observation and analysis to determine the most effective methods, with a willingness to adapt according to the results. While some participants emphasise the relevance of methodology over content, others argue that both are crucial and should be tailored to each group. In general, there is convergence on the difficulty in achieving active student participation, attributing this to a lack of empathy or resistance towards interactive activities, recognising the importance of adapting methodologies to the needs of each group and constantly evaluating their effectiveness. The need to simplify teaching and focus on relevant aspects of the curriculum is mentioned, as well as the need to face technological challenges with alternative plans. Their commitment to quality teaching, willingness to learn and adapt is also highlighted, although areas for improvement such as more detailed planning, time and classroom management are mentioned.

Literal and derived mentions of relevant words in the code “Changes and improvements in interventions”: Methodology: 34 times (5.53%), Activities: 21 times (3.43%), Technology: 21 times (3.43%), Content: 18 times (2.94%), Plan: 10 times (1.63%), Topic: 6 times (0.98%), Participate: 6 times (0.98%), Exam: 5 times (0.82%), Adapt: 5 times (0.82%).

As far as secondary school students are concerned, in general, there is a diversity of opinions among students regarding the methodology of teaching history. Some prefer more dynamic and visual approaches, while others are happy with the traditional way of teaching. The perception of motivation also highlights the importance of active participation and discussion in the learning process. This variability may be attributable to personal experiences, levels of interest in the subject or perceptions about the purpose of history education. To gain a deeper understanding, it would be useful to further explore the reasons behind students’ responses. Students’ ratings of the current teacher’s experience suggest that teaching experience and ability are considered important factors in teaching effectiveness.

While Teacher 1 and Teacher 3 recognise aspects of the competence-based approach to historical thinking in teaching practice, Teacher 2 is not familiar with the specific term. Regarding the development of historical competences in pupils, Teacher 1 highlights the importance of adapting materials to children’s understanding from an early age, while Teacher 2 suggests interdepartmental collaboration and family involvement to improve outcomes. Teacher 3 recognises the need for continuous improvement and stresses the importance of learning from mistakes. In relation to teaching perspectives and approaches, Teacher 3 emphasises the connection between historical events and social, economic and political contexts over time, highlighting the importance of ‘historical empathy’. Finally, teachers agree on the challenges and complexities of teaching historical competences, highlighting the need to make them understandable for students and to avoid reducing them to mere memorisation.

Regarding active learning methodologies such as project or problem-based learning, there are differences in its implementation between Teacher 1, who uses it more in lower grades due to exam preparation, and Teacher 2, who offers a short answer. Teacher 3 shows experience in educational innovation projects, indicating a predisposition towards more innovative approaches. The commitment and dedication required is highlighted, as well as the lack of detail on implementation by Teacher 1, which may limit its wider application due to the associated stress and workload. Several challenges and limitations in the implementation of active teaching methodologies are highlighted. These challenges include existing workload, loneliness among colleagues, lack of digital resources both at school and at home for students, limited time in the classroom, language barrier in understanding concepts, lack of teacher training, distrust of new methodologies, and the complexity of catering for diversity in the classroom. In addition, it is stressed that the impact of the methodology on student learning requires adequate assessment and collaborative work to generate significant changes.

Finally, it should be noted that the three teachers agree that active methodologies and historical thinking are not widespread in secondary classrooms. The reasons mainly point to lack of training, time constraints, lack of resources and mistrust on the part of teachers. Inertia in the education system, resistance to changing traditional pedagogical practices and a preference for safe and rote approaches are also mentioned. We can see that resistance to change seems to be a significant barrier. Lack of training and institutional support is highlighted as a key problem. The importance of satisfying studious learners through traditional methods is mentioned as a potential barrier to adopting more creative and reflective approaches.

O2. To identify if there are differences in the students’ perception of motivation during the teaching process, after the implementation of the DU that promote historical thinking through active methods

In relation to this objective, the data obtained from the quantitative instruments show an approximately normal distribution of the motivation scores. No significant differences were observed between sexes (MH = 22.45, SD = 4.86; MM = 23.33 SD = 5.40) in the initial (pre) assessment (F (1,112) = 0.82, p = 0.36). However, significant differences were observed at the posttest as a function of gender (MH = 25.94, SD = 5.85; MM = 28.33, SD = 5.27) (F (1,112) = 5.26, p < 0.05) with a small effect size (partial η2 = . Significant differences were observed in the posttest as a function of gender (MH = 23.94, SD = 3.95; MM = 25.75, SD = 3.24) (F (1,112) = 7.23, p < 0.05) with a small effect size (partial η2 = 0.06).

Repeated measures analysis of variance did not produce a significant interaction effect result between sex (Female, Male) and phase (Pre vs Post) (F (1,108) = 1.08, p = 0.30). However, a significant effect of the phase (Pre vs Post) factor was observed (F (1,108) = 48.83, p < 0.01) with a large effect size (η2 = 0.144). Similarly, a significant effect of the Sex factor (F (1,108) = 4.63, p = 0.30) with a small effect size (partial η2 = 0.026) was observed. Figure 4 shows the result graphically. Therefore, motivation increased in both groups after the intervention, but especially in the female group.

Differences in Motivation Scores by Gender and Phase.

Master students highlight a higher motivation (8 positive occurrences in the code “Improvements and difficulties in the DU” 1.23%) and satisfaction (4 positive occurrences in this code 0.61%) among students despite facing difficulties. Some participants noted an improvement in their teaching skills after applying the DU, highlighting the importance of practical experience and the application of theoretical concepts in lesson planning and execution. The implementation of gamification and flipped classroom was mentioned to make teaching more attractive, showing the ability to adapt to challenging situations and look for alternative solutions. The importance of the teacher in the learning experience was highlighted and difficulties related to the implementation of technology in the classroom and the resistance of some students to participate in interactive activities were pointed out.

“Overall it did increase a lot of satisfaction and their motivation regarding the subject.”

“In general what I planned worked and it worked more than anything else in the time I had planned.”

“Well, I think that yes, it worked for them, that it was something they had never given before and it was totally different and they liked it.”

“I mean, yes there are digital whiteboards, yes there are projectors, but it’s complicated, especially to apply, in this case, a didactic unit.”

“So, the cooperative work part is fine, the inverted classroom, fatal.”

“But I also think that it was more or less the same as what they were doing with their teacher.”

“But yes, on the days when they were in the classroom, it was more or less the same as what they were doing with their teacher.”

“But yes, on the days when it was two hours, it was noticeable because just before break time I was already tired”.

On the other hand, in general, the perception of the secondary school students interviewed on the effectiveness of the trainee teachers’ teaching method is ambiguous and could benefit from more specific details on the perceived changes. As an analysis we can indicate that the introduction of these DU seems to have had a positive impact on students’ attention and motivation, the use of audio-visual methods and interactivity are prominent aspects of the new methodology that students appreciate. The relationship between the way of teaching and the retention of information for exams is highlighted as an important point for student satisfaction, and resources such as slides, and short videos are specific elements that students find useful. Therefore, the new way of working of the trainee teacher seems to have generated a positive experience for the students, improving participation, motivation, and information retention.

Teachers in this regard highlight positive results, such as improved motivation and reduced student boredom, as well as increased class participation. However, they recognise that the effectiveness of techniques may vary and that training in new active learning methodologies is needed to address student diversity and to keep up to date. In addition, they highlight a shift towards a more active and participatory approach to learning, which can benefit the development of critical skills and student engagement. The importance of adaptability of methodologies is emphasised, as their effectiveness depends on factors such as the subject matter, the group of learners and the resources available. It is pointed out that student motivation can influence their adaptation to the methodologies, and the use of visual and playful techniques to engage less motivated students is suggested. In addition, it is emphasised that the aim of teaching history is to enable students to interpret the world today, thus encouraging critical thinking. The effectiveness of diversity intervention programmes is acknowledged, highlighting the importance of making the content relevant to each learner.

O3. To find out if there are differences in the students’ perception in relation to the level of satisfaction with the teaching process, after the implementation of the DU that promote historical thinking through active methods

An approximately normal distribution of satisfaction scores is observed. No significant differences were observed between sexes (MH = 21.98, SD = 3.72; MM = 22.13 SD = 3.43) in the initial (pre) assessment (F (1,112) = 0.05, p = 0.83). However, significant differences were observed at the posttest as a function of gender (MH = 23.94, SD = 3.95; MM = 25.75, SD = 3.24) (F (1,112) = 7.23, p < 0.05) with a small effect size (partial η2 = 0.06).

The repeated measures analysis of variance did not produce a significant interaction effect result between sex (Female, Male) and phase (Pre vs Post) (F (1,108) = 3.04, p = 0.08). However, a significant effect of the phase (Pre vs Post) factor was observed (F (1,108) = 51.6, p < 0.01) with a medium effect size (η2 = 0.13). That is, the intervention had a significant effect on students’ satisfaction with the subject. Figure 5 shows the result graphically.

Differences in Satisfaction Scores by Gender and Stage.

As a general observation we can indicate that all three secondary school pupils interviewed have positive perceptions of the usefulness of history. The definitions of history are varied, but they share the central idea of past events, and the pupils’ responses show a basic understanding of the importance of history in understanding the present and developing critical skills. Their interest in learning about the past is highlighted and it is noted that the content of lessons and the amount of work for exams are important considerations for some students. Students’ comments suggest that there are aspects of history teaching that could be improved, such as the presentation of information, the length of language and the possible lack of connection between memorisation and understanding of content. Diversifying teaching methods and incorporating more dynamic approaches could help to address these concerns and improve student motivation. It would be beneficial to delve deeper into the responses to better understand the underlying reasons behind their perceptions and to gain a more complete picture of their experience with the subject.

O4. To find out if there are differences in the students’ perception in relation to the level of effectiveness and transfer of the learning achieved, after the implementation of the DU that promote historical thinking through active methods

An approximately normal distribution of perceived learning scores is observed. Table 4 presents the results for perceived learning on a scale of 13 to 65. No significant gender differences were observed (MH = 40.27, SD = 5.40; MM = 40.67, SD = 5.14) at the initial (pre) assessment (F (1,112) = 0.16, p = 0.69). There were also no significant sex differences at posttest (MH = 43.94, SD = 6.32; MM = 45.39, SD = 6.38) (F (1,112) = 1.46, p = 0.23).

The repeated measures analysis of variance did not produce a significant interaction effect result between sex (Female, Male) and phase (Pre vs Post) (F (1,108) = 0.82, p = 0.37). However, a significant effect of the phase (Pre vs Post) factor was observed (F (1,108) = 52.71 p < 0.01) with a medium effect size (η2 = 0.12). That is, the intervention had a significant effect on students’ perception of learning. Fig. 6 shows the result graphically.

Differences in Perceived Learning Scores by Gender and Stage.

Master’s students recognise the usefulness of the theory of historical thinking in the planning and execution of classes, as well as the importance of the ethical dimension of history and the need to connect history with citizenship education. The use of primary sources and active methodology to involve students in historical analysis is highlighted. Furthermore, the importance of contextualising history teaching in the immediate environment and addressing social, cultural, and political issues to develop critical thinking in students is emphasised. However, there are divergences among the participants in terms of the perceived novelty of the theory of historical thinking, the depth of ethical exploration in the historical context and the inclusion of themes. Finally, the importance of connecting history with current affairs is mentioned, although this may present challenges in the handling of sensitivities and emotions during the teaching of certain historical topics.

For their part, teachers seem to agree that history teaching should not be limited to the transmission of historical facts, but should also encourage critical thinking, reflection and active participation in social problems. Citizenship education is seen as a process that goes beyond the acquisition of knowledge, including the development of analytical skills and the ability to question and criticise social and political reality.

Discussion and conclusions

If we look at the first objective, we can see that a significant effect of the phase factor (Pre vs Post) was observed in the methodology (F (1,108) = 91.88, p < 0.01) with a large effect size (partial η2 = 0.26). In turn, we can see corroboration of this change as master’s students highlight in their statements the importance of interactive and participatory methods, as well as the role of the teacher in the educational experience. They recognise positive changes in current teaching, highlighting the positive experience with children and the inclusion of relevant points, but they criticise the persistence of traditional methods that are not very active and the resistance of some students to participatory methods. This represents a challenge in contemporary teaching, with difficulties in achieving active student participation attributed to a lack of empathy or resistance to interactive activities. The importance of adapting methodologies to the needs of each group and constantly evaluating their effectiveness is therefore highlighted, although some also point out the need to dose the content and adapt according to the results.

For their part, high school students emphasise the importance of visual resources, discussions and the connection between past and present in history teaching, as well as teaching experience and skill, reflecting diversity in preferences and learning styles. The effectiveness of the trainee teachers’ teaching methods is ambiguously perceived and may need more specific details on perceived changes. On the other hand, high school teachers recognise the need for training in new methodologies to address student diversity and to keep up to date, highlighting a shift towards a more active and participatory approach to learning. This coincides with the results of Sánchez et al. ( 2020 ) where they note an advance in teachers’ perception of a methodology oriented towards fostering historical and critical thinking in students. However, these teachers face various difficulties and limitations in the implementation of these methodologies, such as workload, lack of digital resources and the language barrier. The impact of the methodologies on learning requires adequate assessment and collaborative work to generate significant changes, being one of the main challenges for education in the future. Consequently, we believe it is crucial that educational administrations encourage the motivation and training of both new and old teachers in order to achieve the necessary methodological improvement in the teaching of history. Teachers suggested that the use of visual and playful techniques engage less motivated students, and the aim of fostering critical thinking through history teaching is highlighted, so the effectiveness of the intervention programmes for diversity is recognised, emphasising the relevance of the content for each student.

This may lead us to see that the generalised perception of students in the pre-test denotes the persistence of the traditional teaching model with the absence of active methods, digital resources, and historical thinking skills. Monteagudo-Fernández et al. ( 2020 ) obtain similar results in a study with secondary education and baccalaureate students, confirming the existence of a traditional model in the teaching of history that excludes cooperative and inquiry-based methodologies. This reality must point towards a didactic model that prioritises competence learning and student activism in their learning process, highlighting advocates such as Carretero et al., ( 2017 ) or Metzger & Harris, ( 2018 ), who are committed to a methodological change that moves away from the predominant conceptual model for teaching history.

In terms of motivation, we can see that a significant effect of the phase factor (Pre vs Post) was observed (F (1,108) = 48.83, p < 0.01) with a large effect size (η2 = 0.144). Similarly, a significant effect of the Sex factor (F (1,108) = 4.63, p = 0.30) with a small effect size (partial η2 = 0.026) was observed. Thus, motivation increased in both groups after the intervention, but especially in the female group. The master’s students corroborate this by highlighting a higher motivation and satisfaction among students despite facing difficulties, while for high school students, in general, the new way of working of the trainee teacher seems to have generated a positive experience, improving participation, motivation and retention of information. The importance of active participation and discussion in the learning process is particularly emphasised by the high school students. Teachers highlight positive results, such as improved motivation and reduced student boredom, as well as increased participation in class. However, there is no significant statement regarding a difference in motivation with respect to gender, which may suggest that this is a change that is little perceived by teachers and students, but which is present and should be considered when applying these active and historical thinking methods.

These results are similar to those presented by several authors (Gómez et al., 2021a ; Gómez et al., 2021b ; Rodríguez et al., 2020 ), who also highlight as the most important factor that motivation is due to the use of resources other than the school textbook, which is very good news for continuing to take steps towards methodological complementarity, so that the students themselves are aware that by using all kinds of resources to learn, they can and should be more motivated. In these studies (Gómez et al., 2021a ; Gómez et al., 2021b ), they also found that the item with the lowest score in their pretest is the one that states that students are motivated because they can contribute their points of view and knowledge, something that clearly does not occur in traditional classes where the students’ role as receivers predominates. For his part, Singer ( 1996 ) considers gender to be one of the most significant predictors in relation to teaching approaches. In this sense, Maquilón, Sánchez and Cuesta ( 2016 ), in their study of active Primary School teachers, point out that men tend to opt for an approach based on the transmission and reproduction of information, while women are inclined towards a more student-centred approach.

In satisfaction, significant differences were also observed in the posttest as a function of gender (MH = 23.94, SD = 3.95; MM = 25.75, SD = 3.24) (F (1,112) = 7.23, p < 0.05) with a small effect size (partial η2 = 0.06), as for motivation (MH = 25.94, SD = 5.85; MM = 28.33, SD = 5.27) (F (1,112) = 5.26, p < 0.05) (partial η2 = 0.04). However, repeated measures analysis of variance did not produce a significant result of interaction effect between sex and phase (F (1,108) = 3.04, p = 0.08). A significant effect of the phase factor (Pre vs Post) was observed (F (1,108) = 51.6, p < 0.01) with a medium effect size (η2 = 0.13). In other words, the intervention had a significant effect on students’ satisfaction with the subject, in agreement with what was stated by the master’s students and teaching staff on the improvement of student motivation and satisfaction. They highlight the relationship between the way of teaching and the retention of information for the exams as an important point for their satisfaction. High school students highlight that there are aspects of history teaching that could be improved, such as the presentation of information, the length of language and the possible lack of connection between memorisation and comprehension of content. Diversifying teaching methods and incorporating more dynamic approaches could help to address these concerns and improve pupils’ motivation.

Finally, on learning, a significant effect of the phase factor (Pre vs Post) was observed (F (1,108) = 52.71 p < 0.01) with a medium effect size (η2 = 0.12). That is, the intervention had a significant effect on students’ perception of learning. Master’s students highlight the importance of the teacher in the learning experience and difficulties related to the implementation of technology in the classroom and the reluctance of some students to participate in interactive activities were noted, although the crucial role of this methodology in enhancing the learning experience is highlighted, with the consideration that there is no single methodology effective for all groups. Students suggest that there are aspects of history teaching that could be improved, such as the presentation of information, the length of language and the possible lack of connection between memorisation and understanding of content. Diversifying teaching methods and incorporating more dynamic approaches could help to address these concerns. Teachers for their part highlight the shift towards a more active and participatory approach to learning, which can benefit the development of critical skills and student engagement. However, this requires adequate assessments and collaborative work to generate significant changes, as well as continuous training in active learning methodologies and strategies, considered essential nowadays.

There is still an overuse of textbooks and the expository strategy by teachers who teach History (Carretero and Van Alphen, 2014 ; Colomer et al., 2018 ). However, more and more teachers in Spain are in favour of a teaching model in which the student acquires a greater role through the implementation of innovative resources (heritage, written and oral sources, new technologies) and educational strategies that encourage the active participation of students in the teaching and learning process (project-based learning, gamification, flipped classroom) (Gómez et al., 2018 ; Gómez et al., 2021a ; Sánchez et al., 2020 ). It is therefore important to be aware of developments in the incorporation of competence-based social sciences teaching and a learner-centred model at all levels of education.

We can conclude from the above that the programme was quite effective in the objectives studied. In the quantitative data we observed an improvement in the students’ perception of all the variables studied after the intervention, especially the change in methodology and the improvement in motivation had a large effect size. Moreover, it can be noted that the DOMs applied most of the methods, techniques, and resources we proposed in the training programme (supplementary material Fig. 6 ). On the other hand, we found quite positive statements about the programme from both master’s students and high school students and teachers as we have seen in the different points. However, it is important to point out the limitations and difficulties reported by teachers and students when implementing this type of unit, as well as the fact that there were some weaknesses in this study, such as the small quantitative and qualitative sample group. As a possible future improvement when carrying out the interviews and organising the focus group, it is possible to point out that it could be organised with more time and written commitment from the participants, as the initial intention was for 8 teachers, secondary school students and Master’s students to participate, respectively, one for each unit applied. The limitations of their availability played a negative role in the collection of more qualitative data, as participation was voluntary and, in the case of high school students, parental approval was required.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Archibald MM, Ambagtsheer RC, Casey MG, Lawless M (2019) Using Zoom Videoconferencing for Qualitative Data Collection: Perceptions and Experiences of Researchers and Participants. International Journal of Qualitative Methods 18. https://doi.org/10.1177/1609406919874596

Bartelds H, Savenije GM, Van Boxtel C (2020) Students’ and teachers’ beliefs about historical empathy in secondary history education. J. Theory Res. Soc. Educ. 48(4):529–551. https://doi.org/10.1080/00933104.2020.1808131

Article Google Scholar

Carretero M, Van Alphen F (2014) Do master narratives change among high school students? A characterization of how national history is represented. J. Cognition Instr. 32(3):290–312. https://doi.org/10.1080/07370008.2014.919298

Carretero M, Berger S, Grever X (eds) (2017) Palgrave Handbook of Research in Historical Culture and Education. Palgrave McMillan, London

Chapman A (2011) Understanding Historical Knowing: Evidence and Accounts. In: Perikleous, L, Shemilt, D (eds) The Future of the Past: Why History Education matters. Association for Historical Dialogue and Research, Kailas Printers, Nicosia, p 169–216

Colomer JC, Sáiz J, Valls R (2018) Competencias históricas y actividades con recursos tecnológicos en libros de texto de Historia: nuevos materiales y viejas rutinas. J Ensayos Rev de La Fac. de Alb 33 (1). https://doi.org/10.18239/ensayos.v33i1.1740

Cooper H, Chapman A (eds) (2009) Constructing History. Sage, London

Creswell JW, Plano Clark VL (2017) Designing and conducting mixed methods research, 3rd edn. Sage, London

De Groot-Reuvekamp M, Ros A, Van Boxtel C (2018) A successful professional development program in history: what matters? J. Teach. Teach. Educ. 75:290–301. https://doi.org/10.1016/j.tate.2018.07.005

Domínguez Castillo J (2015) Pensamiento histórico y evaluación de competencias. Graó, Barcelona

Ercikan K, Seixas P (2015) Issues in designing assessment of historical thinking. Theory into Pract. 54:255–262

Gago M (2018) Consciência histórica e narrativa na aula de História-concepções de professores. Edições Afrontamento, Porto

Gómez Carrasco CJ, Rodríguez Pérez RA, Monteagudo Fernández J (2017) Las competencias históricas en los procesos de evaluación: libros de texto y exámenes. In: López R, Miralles P, Prats J, Gómez CJ (eds) Enseñanza de la historia y competencias educativas. Graó, Barcelona, p 141–165

Gómez CJ, Monteagudo Fernández J, Miralles Martínez P (2018) Conocimiento histórico y evaluación de competencias en los exámenes de Educación Secundaria. Un análisis comparativo España-Inglaterra. J. Educatio 36:85–106. https://doi.org/10.6018/j/324181

Gómez Carrasco CJ, Rodríguez Medina J, Miralles Martínez P, Arias González VB (2021a) Effects of a teacher training program on the motivation and satisfaction of History secondary students. J. Rev. de. Psicodidáctica 26(6):45–52. https://doi.org/10.1016/j.psicod.2020.07.002

Gómez Carrasco CJ, Rodríguez-Medina J, Miralles-Martínez P, López-Facal R (2021b) Motivation and Perceived Learning of Secondary Education History Students. Analysis of a Programme on Initial Teacher Training. J Frontiers in Psychology 12. https://doi.org/10.3389/fpsyg.2021.661780

Guerrero-Romera C, Sánchez-Ibáñez R, Miralles-Martínez P (2022) Approaches to History Teaching According to a Structural Equation Model. J Frontiers in Education 7. https://doi.org/10.3389/feduc.2022.842977

Guirao P (2013) Técnicas y hábitos de estudio de la asignatura de Historia en Secundaria y Bachillerato. J GeoGraphos 4(42)):238–263

Henríquez R, Ruíz M (2014) Chilean students learn to think historically: Construction of historical causation through the use of evidence in writing. J. Linguist. Educ. 25:145–167

Henze I, van Driel JH (2011) Toward a More Comprehensive Way to Capture PCK in its Complexity. In: Berry A, Friedrichsen P, Loughran J (eds) Re-Examining Pedagogical Content Knowledge. Routlegde, New York, p 120–134

Hernández F, Maquilón JJ, Monroy F (2012) Estudio de los enfoques de enseñanza en profesorado de educación primaria. J. Prof. 16:61–77. http://www.ugr.es/~recfpro/rev161ART5.pdf

Google Scholar

Kember D, Kwan KP (2000) Lecturers’ Approaches to Teaching and Their Relationship to Conceptions of Good Teaching. J. Instr. Sci. 28:469–490. https://doi.org/10.1023/A:1026569608656

Lee P, Dickinson A, Ashby R (1996) Project Chata: Concepts of History and Teaching Approaches at Key Stages 2 and 3 Children’s Understanding of “Because” and the Status of Explanation in History. J. Teach. Hist. 82:6–11. http://www.jstor.org/stable/43260097

Lopezosa C, Codina L (2023) ChatGPT y software CAQDAS para el análisis cualitativo de entrevistas: Pasos para combinar la inteligencia artificial de OpenAI con ATLAS. ti, Nvivo y MAXQDA. Universitat Pompeu Fabra, Barcelona

Maquilón JJ, Sánchez M, Cuesta JD (2016) Enseñar y aprender en las aulas de Educación Primaria. J. Rev. Electr.ónica de. Investigación Educativa 18(2):144–155. https://cutt.ly/Ou5H9AQ

Metzger SA, Harris LM (2018) The Wiley International Handbook of History Teaching and Learning. Wiley, Arizona

Book Google Scholar

Miralles-Sánchez P, Gómez-Carrasco CJ, Rodríguez-Medina J (2023) Design and validation of two tools to observe and analyze history lessons in secondary education. J Front Educ 8. https://doi.org/10.3389/feduc.2023.1213358

Monteagudo-Fernández J, Rodríguez-Pérez RA, Escribano-Miralles A, Rodríguez-García AM (2020) Percepciones de los estudiantes de Educación Secundaria sobre la enseñanza de la historia, a través del uso de las TIC y recursos digitales. J. REIFOP 23(2):67–79. https://doi.org/10.6018/reifop.417611

Navarro E, De Alba N (2015) Citizenship education in the European curricula. J. Procedia Soc. Behav. Sci. 197:45–49

Peck C, Seixas P (2008) Benchmarks of Historical Thinking. First Steps. Can. J. Educ. 31(4):1015–1038

Pérez-Juste R, Galán Rodríguez A, Quintanal Díaz J (2012) Métodos y diseños de investigación en educación. UNED, Madrid

Prieto JA, Gómez CJ, Miralles P (2013) El uso de fuentes primarias en el aula y el desarrollo de pensamiento histórico y social. Una experiencia en Bachillerato. J Clío History and Teaching 39

R Core Team (2023). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/

Rodríguez J, Gómez CJ, Miralles P, Aznar I (2020) An Evaluation of an Intervention Programme in Teacher Training for Geography and History. A Reliability and Validity Analysis. J Sustainability 12 (8). https://doi.org/10.3390/su12083124

Rüssen J (1997) El libro de texto ideal. Reflexiones en torno a los medios para guiar las clases de historia. J. Íber. Didáctica de. las Cienc. Soc., Geogr.ía e historia 12:79–93

Sánchez-Ibáñez R, Martínez-Nieto A (2015) Patrimonio e identidad de la Región de Murcia: una aproximación a través del currículo y los libros de texto de Ciencias Sociales de Secundaria. J. Cl.ío Hist. Hist. Teach. 41:1–34

Sánchez R, Campillo JM, Guerrero C (2020) Percepciones del profesorado de primaria y secundaria sobre la enseñanza de la historia. J. Rifop 34:57–76. https://doi.org/10.47553/rifop.v34i3.83247

Sáiz J, Gómez CJ (2016) Investigar el pensamiento histórico y narrativo en la formación del profesorado: fundamentos teóricos y metodológicos. J. Reifop 19(1):175–190. https://doi.org/10.6018/reifop.19.1.206701

Sáiz J, López-Facal R (2015) Competencias y narrativas históricas: el pensamiento histórico de estudiantes y futuros profesores españoles de educación secundaria. J. Rev. de. Estudios Soc. 52:87–101

Sapsford R, Jupp V (eds) (2006) Data collection and analysis. Sage, London. https://doi.org/10.4135/9781849208802

Seixas P, Morton T (2013) The Big Six Historical Thinking Concepts. Nelson College Indigenous, Toronto

Singer ER (1996) Espoused teaching paradigms of college faculty. J. Res. High. Educ. 37(6):659–679

Article ADS Google Scholar

Smith J (2019) Curriculum coherence and teachers’ decision-making in Scottish high school history syllabi. Curric. J. 30(4):441–463

Tirado-Olivares S, López-Fernández C, González-Calero JA, Cózar-Gutiérrez R (2024) Enhancing historical thinking through learning analytics in Primary Education: A bridge to formative assessment. J Education and Information Technologies https://doi.org/10.1007/s10639-023-12425-w

Trigwell K, Prosser M (2004) Development and Use of the Approaches to Teaching Inventory. J. Educ. Psychol. Rev. 16:409–424. https://doi.org/10.1007/s10648-004-0007-9

Trigwell K, Prosser M, Ginns P (2005) Phenomenographic Pedagogy and a revised Approaches to Teaching Inventory. J. High. Edu Res Dev. 24:349–360. https://doi.org/10.1080/07294360500284730

Van Drie J, Van Boxtel C (2008) Historical reasoning: towards a framework for analyzing student´s reasoning about the past. J. Educ. Psychol. Rev. 20:87–110

VanSledright BA (2014) Assessing Historical Thinking and Understanding. Innovation Design for New Standards. Routledge, New York

Van Straaten D, Wilschut A, Oostdam R (2018) Measuring students’ appraisals of the relevance of history: the construction and validation of the Relevance of History Measurement Scale (RHMS). J. Stud. Educ. Eval. 56:102–111. https://doi.org/10.1016/j.stueduc.2017.12.002

Vermunt JD, Verloop N (1999) Congruence and Friction between Learning and Teaching. Learn. J. Instr. 9(3):257–280. https://doi.org/10.1016/j.stueduc.2017.12.002

Wineburg S (2001) Historical thinking and other unnatural acts. Charting the future of teaching the past. Temple University Press, Philadelphia

Wineburg S, Martin D Monte-Sano C (2013) Reading like a Historian. Teaching Literacy in Middle & High School History Classrooms. Teachers College, New York

Download references

Author information

Authors and affiliations.

Universidad de Murcia, Murcia, Spain

Pedro Miralles-Sánchez & Raquel Sánchez-Ibáñez

Universidad de Valladolid, Valladolid, Spain

Jairo Rodríguez-Medina

You can also search for this author in PubMed Google Scholar

Contributions

RSI and JR-M: conceived and designed the project and doctoral thesis of which this study is part. PMS and JR-M.: have made methodology, data collection and formal analysis. PM-S and JR-M have co-written the manuscript and RSI contributed to revisions, having read and approved the submitted manuscript. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Pedro Miralles-Sánchez .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

This study was performed in line with the principles of the Declaration of Helsinki. It is part of grant PRE2021-097619, funded by MCIN/AEI/10.13039/501100011033 and ESF + . It is part of the research project “La enseñanza y el aprendizaje de competencias históricas en bachillerato: un reto para lograr una ciudadanía crítica y democrática” (PID2020-113453RB-I00), funded by the Agencia Estatal de Investigación (AEI/10.13039/501100011033). This project was granted favourable by Ethics Research Committee of the University of Murcia 8/03/2021.

Informed consent

Informed consent was obtained from all participants and/or their legal guardians during data collection (April–May 2023). Participants were informed about the objectives and procedures of the study and how their rights were going to be protected. Participation in the research was voluntary and anonymous.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Cualitative data students, cualitative data focus group, cualitative data teachers, student interview 1, student interview 2, student interview 3, teacher interview 1, transcription of focal group, teacher interview 2, teacher interview 3, cuantitative data, instruments and du, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Miralles-Sánchez, P., Rodríguez-Medina, J. & Sánchez-Ibáñez, R. Evaluation of didactic units on historical thinking and active methods. Humanit Soc Sci Commun 11 , 1032 (2024). https://doi.org/10.1057/s41599-024-03546-9

Download citation

Received : 19 April 2024

Accepted : 31 July 2024

Published : 12 August 2024

DOI : https://doi.org/10.1057/s41599-024-03546-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

Explore articles by subject
Guide to authors
Editorial policies

DOI: 10.22397/wlri.2024.40.2.109
Corpus ID: 271118227

Is this legal research method any good?: The need to introduce quantitative research methods

Kiseok Park , Kyuho Lee
Published in Wonkwang University Legal… 30 June 2024

Related Papers

Showing 1 through 3 of 0 Related Papers

IMAGES

Quantitative Research in Social Sciences-PhdScholars
PPT
Purpose of a Quantitative Methodology (With images)
Quantitative Social Science
What is the purpose of the quantitative method in social science?
PPT

COMMENTS

Quantitative Methods
As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant. Some specific limitations associated with using quantitative methods to study research problems in the social sciences include: Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
A Quick Guide to Quantitative Research in the Social Sciences
About the Book. This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed ...
What Is Quantitative Research?
Quantitative research is the opposite of qualitative research, which involves collecting and analyzing non-numerical data (e.g., text, video, or audio). Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.
Quantitative Research
Along with this division, there is an unwritten hierarchy in research circles, and quantitative research is considered to be more rigorous, more reliable, and more precise (Berg, 2009, p. 2). In the social sciences, qualitative methods often take a back seat to quantitative approaches.
What Is Quantitative Research? An Overview and Guidelines
Abstract. In an era of data-driven decision-making, a comprehensive understanding of quantitative research is indispensable. Current guides often provide fragmented insights, failing to offer a holistic view, while more comprehensive sources remain lengthy and less accessible, hindered by physical and proprietary barriers.
What is Quantitative Research?
Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques.Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.
PDF A Quick Guide to Quantitative Research in the Social Sciences
advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you are a qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real ...
Quantitative and Qualitative Research
What is Quantitative Research? Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns.Quantitative research gathers a range of numeric data.
Quantitative research
Quantitative research. Quantitative research can measure and describe whole societies, or institutions, organisations or groups of individuals that are part of them. The strength of quantitative methods is that they can provide vital information about a society or community, through surveys, examinations, records or censuses, that no individual ...
Quantitative research
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. [1] It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies. [1]Associated with the natural, applied, formal, and social sciences this research strategy promotes the objective empirical investigation of ...
A Quick Guide to Quantitative Research in the Social Sciences A Quick
Adherents to the quantitative paradigm align with a positivistic philosophy in which social phenomena should be observable and measurable in a similar manner to those studied in the physical ...
PDF Quantitative Social Science: An Introduction
Quantitative social science is an interdisciplinary field encompassing a large number of disciplines, including economics, education, political science, public policy, psy-chology, and sociology. In quantitative social science research, scholars analyze data to understand and solve problems about society and human behavior.
Social Sciences Research: Qualitative vs. Quantitative Research
Social science research, or social research as it is sometimes called, stems from the natural sciences, and similar to its precursory field, it uses empirical, measurable outcomes to arrive at a conclusion. While natural scientists use the scientific method, social scientists often use quantitative research to go about their method of discovery.
Quantitative Methods in the Social Sciences
The Quantitative Methods in the Social Sciences (QMSS) program is an innovative, flexible, interdisciplinary course of study that focuses on quantitative research techniques and strategies. The program integrates the perspectives and research methods of six social-science disciplines: economics, history, political science, psychology, sociology ...
Doing Quantitative Research in the Social Sciences
This text covers the theory behind conducting quantitative research in the social sciences. The main focus of this book is on the theory underpinning research design and analysis using statistical techniques to test data gathered from survey questionnaires. The reading level of this text is accessible for undergraduate, postgraduate and ...
Quantitative Research
Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions. ...
Quantitative Social Science
Quantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. ... Quantitative Social Science engages directly with empirical ...
Quantitative Research: A Successful Investigation in Natural and Social
Quantitative research explains phenomena by collecting numerical unchanging d etailed data t hat. are analyzed using mathematically based methods, in particular statistics that pose questions of ...
Quantitative Analysis in Social Sciences: An Brief ...
Abstract and Figures. In this paper, I present an introduction to quantitative research methods in social sciences. The paper is intended for non-Economics undergraduate students, development ...
A Practical Guide to Writing Quantitative and Qualitative Research
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
Quantitative Research in Sociology
Quantitative research is a type of research that analyzes numerical and quantifiable things that can be used in statistical analysis in order to be applied to a population. In sociological ...
Methods and Statistics in Social Sciences Specialization
This course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity.
Interpretive Quantitative Methods for the Social Sciences
Abstract. Quantitative social science has long been dominated by self-consciously positivist approaches to the philosophy, rhetoric and methodology of research. This article outlines an alternative approach based on interpretive research methods. Interpretative approaches are usually associated with qualitative social science but are equally ...
Quantitative Social Research (MSc)
Quantitative Social Research MSc will equip you with a range of advanced skills in data management. The University of Warwick's Sociology Department, ranked 4th in the UK, is home to leading experts who will train you to use quantitative methods to examine societal trends and social behaviours.
Ph.D. Research Design and Methods Courses
Quantitative Methods Courses. A list of quantitative research methods classes offered at UW is on the Center for Statistics and Social Sciences site. You can also find quantitative methods classes in other departments. The Center for Social Science Computation and Research.
QSS 82 one quarter research projects, Spring 2024
On Wednesday, May 29, students majoring and minoring in Quantitative Social Science (QSS) showcased their research at a poster session, presenting the results of one-quarter projects completed in QSS 82.This course, led by Senior Lecturer Robert Cooper in Spring 2024, culminated in the presentation of seven diverse posters. The QSS 82 poster session offered seniors a platform to exhibit their ...
Book Title: Graduate research methods in social work
Book Description: Our textbook guides graduate social work students step by step through the research process from conceptualization to dissemination. We center cultural humility, information literacy, pragmatism, and ethics and values as core components of social work research.
Evaluation of didactic units on historical thinking and active methods
For the qualitative analysis, a descriptive analysis was carried out using the qualitative research software Atlas.Ti 23, which is widely used in research in the field of Social Science Didactics ...
Is this legal research method any good?: The need to introduce
Law is one of the social sciences and a field that citizens most frequently encounter in their daily lives. Despite this, legal research methods are primarily limited to literature reviews, and it is challenging to find quantitative research methods such as surveys that meticulously capture and reflect the thoughts, opinions, and intentions of the public.

Organizing Your Social Sciences Research Paper

Need Help Locating Statistics?

Characteristics of Quantitative Research

Basic Research Design for Quantitative Studies

Strengths of Using Quantitative Methods

Limitations of Using Quantitative Methods

Research Tip

A Quick Guide to Quantitative Research in the Social Sciences

Formats Available

Table of Contents

Ancillary Material

About the Contributors

Contribute to this Page

Have a language expert improve your writing

What Is Quantitative Research? | Definition, Uses & Methods

Table of contents

Here's why students love Scribbr's proofreading services

Cite this Scribbr article

Is this article helpful?

Pritha Bhandari

S371 Social Work Research - Jill Chonody: What is Quantitative Research?

Quantitative Research in the Social Sciences

Characteristics of Quantitative Research

Basic Research Designs for Quantitative Studies

Quantitative and Qualitative Research

What is Quantitative Research?

What is social science?

Quantitative methodologies

Cross-sectional studies

Longitudinal studies

Opinion polls

Questionnaires

Social attitude surveys

Surveys and censuses

Further information

Social Sciences Research: Qualitative vs. Quantitative Research

Focus Groups

You are here

Doing Quantitative Research in the Social Sciences An Integrated Approach to Research Design, Measurement and Statistics

Preview this book

Select a Purchasing Option

Related Products

Quantitative Research – Methods, Types and Analysis

Quantitative Research

Quantitative Research Methods

Descriptive Research Design

Correlational Research Design

Quasi-experimental Research Design

Experimental Research Design

Survey Research

Quantitative Research Analysis Methods

Statistical Analysis

Regression Analysis

Factor Analysis

Structural Equation Modeling

Time Series Analysis

Multilevel Modeling

Applications of Quantitative Research

Characteristics of Quantitative Research

Examples of Quantitative Research

How to Conduct Quantitative Research

When to use Quantitative Research

Purpose of Quantitative Research

Advantages of Quantitative Research

Limitations of Quantitative Research

About the author

Muhammad Hassan

You may also like

Explanatory Research – Types, Methods, Guide

Ethnographic Research -Types, Methods and Guide

Textual Analysis – Types, Examples and Guide

Applied Research – Types, Methods and Examples

Correlational Research – Methods, Types and...

Triangulation in Research – Types, Methods and...

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Glafera Janet Matanguihan

INTRODUCTION

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES