research about education quantitative

• Technical Support
• Find My Rep

You are here

Quantitative Research in Education A Primer

• Wayne K. Hoy - Ohio State University, USA
• Curt M. Adams - University of Oklahoma, USA
• Description

“ The book provides a reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research… ”

— Megan Tschannen-Moran, The College of William & Mary

Quantitative Research in Education: A Primer, Second Edition is a brief and practical text designed to allay anxiety about quantitative research. Award-winning authors Wayne K. Hoy and Curt M. Adams first introduce readers to the nature of research and science, and then present the meaning of concepts and research problems as they dispel notions that quantitative research is too difficult, too theoretical, and not practical. Rich with concrete examples and illustrations, the Primer emphasizes conceptual understanding and the practical utility of quantitative methods while teaching strategies and techniques for developing original research hypotheses.

The Second Edition includes suggestions for empirical investigation and features a new section on self-determination theory, examples from the latest research, a concluding chapter illustrating the practical applications of quantitative research, and much more. This accessible Primer is perfect for students and researchers who want a quick understanding of the process of scientific inquiry and who want to learn how to effectively create and test ideas.

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

For assistance with your order: Please email us at [email protected] or connect with your SAGE representative.

SAGE 2455 Teller Road Thousand Oaks, CA 91320 www.sagepub.com

“This text will definitely be useful in providing students with a solid orientation to research design particularly in quantitative research”

“Precision, precision, precision! I think this is a must have companion text for graduate students who have to complete a thesis or dissertation. The author does an outstanding job of cataloging and describing difficult research methods terms in a clear and concise way.”

“Greatest strength is the comprehensiveness of the treatment”

“A reference point for beginning educational researchers to grasp the most pertinent elements of designing and conducting research”

Provides all the essential information for quantitative research in a concise book.

A book on research in education but quite well can be accommodated into other social science areas. A great easy to follow publication especially if someone is new to statistical analysis.

There are two strong chapters in this publication that are clearer and more relevant that the sources presently being used by my students. Chapter 3 is particularly well written and clear and builds a progression in terms of understanding statistics. Chapter 4 is also effective however I would probably place this before Chapter 3. In terms of detail there is probably too much in Chapter 4 on Hypothesis whereas Chapter 3 could be developed perhaps by the inclusion of more examples.

Very helpful book that provides a basis for students undertaking education based research.

For those that are interested in doing research that is quantitative in nature, this book is useful, although we tend to advise a more qualitative approach. Therefore I can see myself dipping in and out of this book as it provides some good explanations and there is follow through. I would have welcomed more working examples as this would have concretised everything a lot more.

This is a good supplement to the research methods module, especially for those students who are entering into the field of education. The quantitative methods discussed are also transferrable to other subjects.

NEW TO THIS EDITION:    

• A new chapter devoted to the practical applications of education research uses the concepts of collective trust, organizational climate, and improvement science to illustrate the utility of a quantitative approach. It also offers guidelines for analyzing and improving the practice of research in education.
• New hypotheses found in a variety of research studies are available for readers to analyze and diagram.
• A new section on self-determination theory has been added to demonstrate the relation between theory and practice.
• A new section on self-regulatory climate gives readers an opportunity to explore an exciting new area that they are likely to encounter in practice.  
• A conceptual description of Hierarchical Linear Modeling (HLM) has been added to help readers understand statistical data organized at more than one level.    

KEY FEATURES:  

• Education-specific concrete examples bring concepts to life and engage readers with relevant, meaningful illustrations.
• Check Your Understanding exercises and questions assess the reader’s ability to understand, value, and apply the content of the chapter.  
• Strat egies and techniques for generating hypotheses help readers understand the process of creating their own hypotheses.
• Key Terms are highlighted in the text when they first appear and then summarized in a list at the end of the chapter to help reinforce key concepts.
• A Glossary concisely and clearly defines all the key terms in the text so readers have immediate access to ideas and concepts needing review.
• Charts throughout the text allow readers to select appropriate statistical techniques for given scenarios.
• The Diagramming Table (in Chapter 4) enables readers to diagram and dissect hypotheses by ensuring the key elements of a hypothesis are considered, analyzed, and understood.
• An Elements of a Proposal section (Appendix A) gives readers directions for developing a quantitative research plan and motivates readers to get started—the most difficult step for many.
• The A Few Writing Tips section (Appendix B) lists a number of salient writing suggestions to help readers avoid common mistakes found in formal writing.

Sample Materials & Chapters

For instructors, select a purchasing option.

Quantitative Research in Research on the Education and Learning of Adults

• First Online: 23 May 2019

Cite this chapter

• Ellen Boeren 13  

Part of the book series: Lifelong Learning Book Series ((LLLB,volume 24))

955 Accesses

7 Citations

This chapter starts from the observation that there is a limited presence of quantitative research published in leading adult education journals such as Adult Education Quarterly , Studies in Continuing Education and International Journal of Lifelong Learning . This observation was also discussed by Fejes and Nylander (2015, see also Chap. 7 ). As an adult education scholar mainly working with large quantitative datasets, I aim to provide more insight on what quantitative methods have to offer to the field. I will do this through a brief discussion of the role of methodologies and methods in empirical research, but also by engaging with examples of quantitative research available in the scholarly literature, including a range of existing quantitative scales, and how these can be taken forward in new research as tools to generate the construction of new knowledge. I will first explore potential reasons why the presence of quantitative research in the leading generic adult education journals is so limited.

This chapter is a revised version of a previousely published article: Boeren, E. (2018) The Methodological Underdog: A Review of Quantitative Research in the Key Adult Education Journals. Adult Education Quarterly , 68(1), 63–79.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Because of the word limit of this book chapter, it will be impossible to discuss each survey and its questionnaire in detail. However, both the OECD’s PIAAC and the Eurostat website contain detailed documentation relating to their surveys and can be consulted for free.

See http://www.h2020enliven.org

For example the Essex Summer School in Social Science Data Analysis (see http://www.essex.ac.uk/summerschool /)

Andres, L. (2014). Designing and doing survey research . London: SAGE.

Google Scholar  

Bath, D., & Smith, C. (2009). The relationship between epistemological beliefs and the propensity for lifelong learning. Studies in Continuing Education, 31 (2), 173–189.

Article   Google Scholar  

Bathmaker, A. M. (2007). The impact of Skills for Life on adult basic skills in England: How should we interpret trends in participation and achievement? International Journal of Lifelong Education, 26 (3), 295–313.

Blunt, A., & Yang, B. (2002). Factor structure of the adult attitudes toward adult and continuing education scale and its capacity to predict participation behaviour: Evidence for adoption of a revised scale. Adult Education Quarterly, 52 (4), 299–314.

Boeren, E. (2011). Gender differences in formal, non-formal and informal adult learning. Studies in Continuing Education, 33 (3), 333–346.

Boeren, E. (2016). Lifelong learning participation in a changing policy context, an interdisciplinary theory . Baskingstoke: Palgrave-Macmillan.

Boeren, E., & Holford, J. (2016). Vocationalism varies (a lot): A 12-country multivariate analysis of participation in formal adult learning. Adult Education Quarterly, 66 (2), 120–142.

Boshier, R., Huang, Y., Song, Q., & Song, L. (2006). Market socialism meets the lost generation: Motivational orientations of adult learners in Shanghai. Adult Education Quarterly, 56 (3), 201–222.

Boshier, R. W. (1971). Motivational orientations of adult education participants: A factor analytic exploration of Houle’s typology. Adult Education, 21 , 3–26.

Boyadjieva, P., & Ilieva-Trichkova, P. (2017). Between inclusion and fairness: Social justice perspective to participation in adult education. Adult Education Quarterly, 67 (2), 97–117.

Brinkmann, S., & Kvale, S. (2014). Interviews: Learning the craft of qualitative research interviewing . London: SAGE.

Broek, S., & Hake, B. (2012). Increasing participation of adults in higher education: Factors for successful policies. International Journal of Lifelong Education, 31 (4), 397–417.

Bryman, A. (2012). Social research methods . Oxford: Oxford University Press.

Carney-Crompton, S., & Tan, J. (2002). Support systems, psychological functioning, and academic performance of non-traditional female students. Adult Education Quarterly, 52 (2), 140–154.

Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education . London: Routledge.

Creswell, J. (2003). Research design: Qualitative, quantitative, and mixed methods approaches . Thousand Oaks: SAGE.

Daley, B., Martin, L., & Roessger, K. (2018). A call for methodological plurality: Reconsidering research approaches in adult education. Adult Education Quarterly, 68 (2), 157–169.

Denzin, N. K., & Lincoln, Y. S. (2003). Handbook of qualitative research . London: SAGE.

Desjardins, R., Rubenson, K., & Milana, M. (2006). Unequal chances to participate in adult learning, international perspectives . Paris: UNESCO.

Desrosières, A. (1998). The politics of large numbers: A history ofstatistical reasoning . Cambridge, MA: Harvard University Press.

Ercikan, K., & Roth, W. (2006). What good is polarizing research into qualitative and quantitative? Educational Researcher, 35 (5), 14–23.

Evers, A., Kreijns, K., & Van der Heijden, B. (2016). The design and validation of an instrument to measure teachers’ professional development at work. Studies in Continuing Education, 38 (2), 162–178.

Fejes, A., & Nylander, E. (2015). How pluralistic is the research field on adult education? Dominating bibliometrical trends, 2005–2012. European Journal for Research on the Education and Learning of Adults, 6 (2), 103–123.

Fink, A. (1995). How to ask survey questions, the survey kit . London: SAGE.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour . Redding, MA: Addison-Wesley.

Gage, N. (1989). The paradigm wars and their aftermath. Teachers College Record, 91 (2), 135–150.

Giancola, J., Munz, D., & Trares, S. (2008). First- versus continuing-generation adult students on college perceptions: Are differences actually because of demographic variance? Adult Education Quarterly, 58 (3), 214–228.

Guglielmino, L. (1977). Development of the self-directed learning readiness scale – Doctoral dissertation . Athens: University of Georgia.

Harvey, B., Rothman, A., & Frecker, R. (2006). A confirmatory factor analysis of the Oddi Continuing Learning Inventory (OCLI). Adult Education Quarterly, 56 (3), 188–200.

Hendricks, S. (2001). Contextual and individual factors and the use of influencing tactics in adult education program planning. Adult Education Quarterly, 51 (3), 219–235.

Holford, J., & Mohorcic-Spolar, V. (2012). Neoliberal and inclusive themes in European lifelong learning policy. In S. Riddell, J. Markowitsch, & E. Weedon (Eds.), Lifelong learning in Europe: Equity and efficiency in the balance (pp. 39–62). Bristol: Policy Press.

Chapter   Google Scholar  

Houle, C. O. (1961). The inquiring mind . Wisconsin-Madisson: University of Wisconsin.

Isaac, E., Guy, T., & Valentine, T. (2001). Understanding African American learners’ motivations to learn in church-based adult education. Adult Education Quarterly, 52 (1), 23–38.

Jameson, M., & Fusco, B. (2014). Math anxiety, math self-concept, and math self-efficacy in adult learners compared to traditional undergraduate students. Adult Education Quarterly, 64 (4), 306–322.

Johnson, R., Onwuegbuzie, A., & Turner, A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1 (2), 122–133.

Justice, E., & Dornan, T. (2001). Metacognitive differences between traditional-age and non-traditional-age college students. Adult Education Quarterly, 51 (3), 236–249.

Krupar, A., Horvatek, R., & Byun, S. (2017). Does nonformal education matter? Nonformal education, immigration, and skills in Canada. Adult Education Quarterly, 67 (3), 186–208.

Lavrijsen, J., & Nicaise, I. (2017). Systemic obstacles to lifelong learning: The influence of the educational system design on learning attitudes. Studies in Continuing Education, 39 (2), 176–196.

Lee, S. (2014a). Korean mature women students’ various subjectivities in relation to their motivation for higher education: Generational differences amongst women. International Journal of Lifelong Education, 33 (6), 791–810.

Lee, W. (2014b). Opening up a road to somewhere: Development of associate degree students in Hong Kong. International Journal of Lifelong Education, 33 (5), 607–624.

Likert, R. (1929). A technique for the measurement of attitudes . New York: Columbia University.

Lizzio, A., Stokes, L., & Wilson, K. (2005). Approaches to learning in professional supervision: Supervisee perceptions of processes and outcome. Studies in Continuing Education, 27 (3), 239–256.

McFarland, D. A., Lewis, K., & Goldberg, A. (2016). Sociology in the era of big data: The ascent of forensic social science. The American Sociologist, 47 (12), 9291–9298.

Mulenga, D., & Liang, J.-S. (2008). Motivations for older adults’ participation in distance education: A study at the National Open University of Taiwan. International Journal of Lifelong Education, 27 (3), 289–314.

Piirainen, A., & Viitanen, E. (2010). Transforming expertise from individual to regional community expertise: A four-year study of an education intervention. International Journal of Lifelong Education, 29 (5), 581–596.

Porras-Hernandez, L. H., & Salinas-Amescua, B. (2012). Nonparticipation in adult education: From self-perceptions to alternative explanations. Adult Education Quarterly, 62 (4), 311–331.

Robson, C. (2011). Real world research . Chichester: Wiley.

Roosmaa, E. L., & Saar, E. (2012). Participation in non-formal learning in EU-15 and EU-8 countries: Demand and supply side factors. International Journal of Lifelong Education, 31 (4), 477–501.

Rothes, A., Lemos, M., & Gonçalves, T. (2017). Motivational profiles of adult learners. Adult Education Quarterly, 67 (1), 3–29.

Rubenson, K., & Desjardins, R. (2009). The impact of welfare state regimes on constraints to participation in adult education. A bounded agency model. Adult Education Quarterly, 59 (3), 187–207.

Sellitz, C., Wrightsman, L. S., & Cook, S. W. (1976). Research methods in social relations . New York: Holt, Rinehart & Winston.

Smith, E. (2008). Using secondary data in educational and social research . New York: McGraw-Hill Education.

Steele, B. (1984). The motivational orientations of persisting older learners in the university setting . University of Arkansas. Unpublished doctoral dissertation.

Stockdale, S., & Brockett, R. (2011). Development of the PRO-SDLS: A measurement of self-direction in learning based on the personal responsibility orientation model. Adult Education Quarterly, 61 (2), 161–180.

Tam, M. (2016). Later life learning experiences: Listening to the voices of Chinese elders in Hong Kong. International Journal of Lifelong Education, 35 (5), 569–585.

Tam, M., & Chui, E. (2016). Ageing and learning: What do they mean to elders themselves? Studies in Continuing Education, 38 (2), 195–212.

Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research . Thousand Oaks: SAGE.

Thomas, G. (2009). How to do your research project . London: SAGE.

Vainikainen, M., Wüstenberg, S., Kupiainen, S., Hotulainen, R., & Hautamäki, J. (2015). Development of learning to learn skills in primary school. International Journal of Lifelong Education, 34 (4), 376–392.

van Rhijn, T., & Lero, D. (2014). The influence of self-efficacy beliefs for student parents attending university. International Journal of Lifelong Education, 33 (4), 541–555.

Download references

Author information

Authors and affiliations.

Moray House School of Education, University of Edinburgh, Edinburgh, Scotland, UK

Ellen Boeren

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ellen Boeren .

Editor information

Editors and affiliations.

Department of Behavioural Sciences & Learning, Linköping University, Linköping, Sweden

Andreas Fejes  & Erik Nylander  & 

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Boeren, E. (2019). Quantitative Research in Research on the Education and Learning of Adults. In: Fejes, A., Nylander, E. (eds) Mapping out the Research Field of Adult Education and Learning. Lifelong Learning Book Series, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-030-10946-2_8

Download citation

DOI : https://doi.org/10.1007/978-3-030-10946-2_8

Published : 23 May 2019

Publisher Name : Springer, Cham

Print ISBN : 978-3-030-10945-5

Online ISBN : 978-3-030-10946-2

eBook Packages : Education Education (R0)

Share this chapter

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

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Subject List
• Take a Tour
• For Authors
• Subscriber Services
• Publications
• African American Studies
• African Studies
• American Literature
• Anthropology
• Architecture Planning and Preservation
• Art History
• Atlantic History
• Biblical Studies
• British and Irish Literature
• Childhood Studies
• Chinese Studies
• Cinema and Media Studies
• Communication
• Criminology
• Environmental Science
• Evolutionary Biology
• International Law
• International Relations
• Islamic Studies
• Jewish Studies
• Latin American Studies
• Latino Studies
• Linguistics
• Literary and Critical Theory
• Medieval Studies
• Military History
• Political Science
• Public Health
• Renaissance and Reformation
• Social Work
• Urban Studies
• Victorian Literature
• Browse All Subjects

How to Subscribe

• Free Trials

In This Article Expand or collapse the "in this article" section Data Collection in Educational Research

Introduction, general overviews.

• General Quantitative Overviews
• Questionnaires
• Quantitative Interviewing
• Quantitative Observation
• Technical Properties
• General Qualitative Overviews
• In-Depth Interviewing
• Focus Groups
• Qualitative Observation
• Qualitative Document Analysis
• Visual Analysis

Related Articles Expand or collapse the "related articles" section about

About related articles close popup.

Lorem Ipsum Sit Dolor Amet

Vestibulum ante ipsum primis in faucibus orci luctus et ultrices posuere cubilia Curae; Aliquam ligula odio, euismod ut aliquam et, vestibulum nec risus. Nulla viverra, arcu et iaculis consequat, justo diam ornare tellus, semper ultrices tellus nunc eu tellus.

• Case Study in Education Research
• Grounded Theory
• Methodologies for Conducting Education Research
• Mixed Methods Research
• Qualitative Research Design
• Statistical Assumptions
• Using Ethnography in Educational Research

Other Subject Areas

Forthcoming articles expand or collapse the "forthcoming articles" section.

• Gender, Power, and Politics in the Academy
• Girls' Education in the Developing World
• Non-Formal & Informal Environmental Education
• Find more forthcoming articles...
• Export Citations
• Share This Facebook LinkedIn Twitter

Data Collection in Educational Research by James H. McMillan , Laura P. Gogia LAST REVIEWED: 05 August 2020 LAST MODIFIED: 30 June 2014 DOI: 10.1093/obo/9780199756810-0087

Data collection methods in educational research are used to gather information that is then analyzed and interpreted. As such, data collection is a very important step in conducting research and can influence results significantly. Once the research question and sources of data are identified, appropriate methods of data collection are determined. Data collection includes a broad range of more specific techniques. Historically, much of the data collection performed in educational research depended on methods developed for studies in the field of psychology, a discipline which took what is termed a “quantitative” approach. This involves using instruments, scales, Tests , and structured observation and interviewing. By the mid- to late twentieth centuries, other disciplines such as anthropology and sociology began to influence educational researchers. Forms of data collection broadened to include what is now called “qualitative” methods, with an emphasis on narratives, participant perspectives, and less structured observation and interviewing. As contemporary educational researchers also draw from fields such as business, political science, and medicine, data collection in education has become a multidisciplinary phenomenon. Because data collection is such a broad topic, General Overviews that attempt to cover all or most techniques tend to offer introductory treatments. Few texts, however, provide comprehensive coverage of every data collection technique. Instead, some cover techniques appropriate for either quantitative or qualitative research approaches. Even more focus on one or two data collection methods within those two research contexts. Consequently, after presenting general overviews, this entry is categorized by data collection appropriate for quantitative and Qualitative Data Collection . These sections, in turn, are subdivided into the major types of quantitative and qualitative data collection techniques. While there are some data collection techniques specific to mixed method research design, which implies a combination of qualitative and quantitative research methodologies, these specific procedures are not emphasized in the present article—readers are referred to the Oxford Bibliography article Mixed Methods Research by Nancy Leech for a comprehensive treatment of mixed method data collection techniques. To locate sources for this article, extensive searches were performed using general-use Internet search engines and educational, psychological, and social science research databases. These searches included keywords around data collection and research methods, as well as specific data collection techniques such as surveys, Tests , Focus Groups , and observation. Frequently cited texts and articles, most recent editions at the time, and sources specific to educational research were given priority. Once these sources were identified, their suggested readings and reference lists were mined for other potential sources. Works or scholars found in multiple reference lists were investigated. When applicable, book reviews in peer-reviewed journals were located and taken into account when curating sources. Sources that demonstrated a high level of impact or offered unique coverage of the topic were included.

General educational research overviews typically include several chapters on data collection, organized into qualitative and quantitative approaches. As a rule they are updated frequently so that they offer timely discussions of methodological trends. Most of them are introductory in nature, written for student researchers. Because of the influence of psychology and other social sciences on the development of data collection in educational research, representative works of psychology ( Trochim 2006 ) and of general social sciences ( Robson 2011 ) are included. Available online, Trochim 2006 is a reader-friendly introduction that provides succinct explanations of most quantitative and qualitative approaches. Olsen 2012 is helpful in showing how data collection techniques used in other disciplines have implications for educational studies. Specific to education, Gall, et al. 2007 is a frequently cited text that contains most educational data collection techniques, although it tends to emphasize more traditional quantitative approaches. Johnson and Christensen 2014 offers a more balanced treatment meant for novice researchers and educational research consumers. Cohen, et al. 2011 also provides a balanced approach, but from a British perspective. Fielding, et al. 2008 offer practical advice on recently developed forms of online data collection, with special attention given to the ethical ramifications of Internet-based data collection. Finally, Arthur, et al. 2012 is unique in this section in that it is an edited work offering short overviews of data collection techniques authored by contemporary leading experts.

Arthur, James, Michael Waring, Robert Coe, and Larry Hedges, eds. 2012. Research methods and methodologies in education . London: SAGE.

A diverse edited text discussing trends in study designs, data collection, and data analysis. It includes twelve chapters devoted to different forms of data collection, written by authors who have recently published extensively on the topic. Annotated bibliographies found at the end of each chapter provide guidance for further reading.

Cohen, Louis, Lawrence Manion, and Keith Morrison. 2011. Research methods in education . 7th ed. London: Routledge.

This long-running, bestselling, comprehensive source offers practical advice with clear theoretical foundations. The newest edition has undergone significant revision. Specific to data collection, revisions include new chapters devoted to data collection via the Internet and visual media. Slides highlighting main points are available on a supplementary website.

Fielding, Nigel, Raymond Lee, and Grant Blank. 2008. The SAGE handbook of online research methods . Thousand Oaks, CA: SAGE.

This extensive handbook presents chapters on Internet research design and data collection written by leading scholars in the field. It discusses using the Internet as an archival resource and a research tool, focusing on the most recent trends in multidisciplinary Internet research.

Gall, Meredith, Joyce Gall, and Walter Borg. 2007. Educational research: An introduction . 8th ed. White Plains, NY: Pearson.

A long-standing, well-respected, nuts-and-bolts perspective on data collection meant to prepare students for conducting original research. Although it tends to emphasize quantitative research methodologies, it has a uniquely rich chapter on historical document analysis.

Johnson, Burke, and Larry Christensen. 2014. Educational research: Quantitative, qualitative, and mixed approaches . 5th ed. Thousand Oaks, CA: SAGE.

A comprehensive introductory text for the consumer and the would-be researcher, with extensive lists of additional resources for gathering all types of data. It discusses quantitative and qualitative research methodologies and data collection evenly but provides extended coverage of questionnaire construction.

Olsen, Wendy. 2012. Data collection: Key debates and methods in social research . London: SAGE.

This recently published toolkit of quantitative, qualitative, and mixed method approaches to data collection provides a more contemporary introduction for both students and research professionals. It offers a helpful overview of data collection as an integral part of research in several different fields of study.

Robson, Colin. 2011. Real world research: A resource for users of social research methods in applied settings . West Sussex, UK: Wiley

This introductory text is intended for all social science. There is an applied, integrated emphasis on contemporary quantitative and qualitative data collection techniques in a separate section of the book, including individual and focus group observations, surveys, unstructured and structured interviewing, and tests.

Trochim, William. 2006. Research methods knowledge base

A free online hypertext textbook on applied social research methods. Data collection techniques associated with qualitative and quantitative research are covered comprehensively. Foundational information appropriate for undergraduates and early graduate students is presented through a series of easy-to-navigate and intuitively ordered webpages. Printed editions are available for purchase in an edition written with James Donnelly (Atomic Dog/Cengage Learning, 2008).

back to top

Users without a subscription are not able to see the full content on this page. Please subscribe or login .

Oxford Bibliographies Online is available by subscription and perpetual access to institutions. For more information or to contact an Oxford Sales Representative click here .

• About Education »
• Meet the Editorial Board »
• Academic Achievement
• Academic Audit for Universities
• Academic Freedom and Tenure in the United States
• Action Research in Education
• Adjuncts in Higher Education in the United States
• Administrator Preparation
• Adolescence
• Advanced Placement and International Baccalaureate Courses
• Advocacy and Activism in Early Childhood
• African American Racial Identity and Learning
• Alaska Native Education
• Alternative Certification Programs for Educators
• Alternative Schools
• American Indian Education
• Animals in Environmental Education
• Art Education
• Artificial Intelligence and Learning
• Assessing School Leader Effectiveness
• Assessment, Behavioral
• Assessment, Educational
• Assessment in Early Childhood Education
• Assistive Technology
• Augmented Reality in Education
• Beginning-Teacher Induction
• Bilingual Education and Bilingualism
• Black Undergraduate Women: Critical Race and Gender Perspe...
• Blended Learning
• Changing Professional and Academic Identities
• Character Education
• Children’s and Young Adult Literature
• Children's Beliefs about Intelligence
• Children's Rights in Early Childhood Education
• Citizenship Education
• Civic and Social Engagement of Higher Education
• Classroom Learning Environments: Assessing and Investigati...
• Classroom Management
• Coherent Instructional Systems at the School and School Sy...
• College Admissions in the United States
• College Athletics in the United States
• Community Relations
• Comparative Education
• Computer-Assisted Language Learning
• Computer-Based Testing
• Conceptualizing, Measuring, and Evaluating Improvement Net...
• Continuous Improvement and "High Leverage" Educational Pro...
• Counseling in Schools
• Critical Approaches to Gender in Higher Education
• Critical Perspectives on Educational Innovation and Improv...
• Critical Race Theory
• Crossborder and Transnational Higher Education
• Cross-National Research on Continuous Improvement
• Cross-Sector Research on Continuous Learning and Improveme...
• Cultural Diversity in Early Childhood Education
• Culturally Responsive Leadership
• Culturally Responsive Pedagogies
• Culturally Responsive Teacher Education in the United Stat...
• Curriculum Design
• Data Collection in Educational Research
• Data-driven Decision Making in the United States
• Deaf Education
• Desegregation and Integration
• Design Thinking and the Learning Sciences: Theoretical, Pr...
• Development, Moral
• Dialogic Pedagogy
• Digital Age Teacher, The
• Digital Citizenship
• Digital Divides
• Disabilities
• Distance Learning
• Distributed Leadership
• Doctoral Education and Training
• Early Childhood Education and Care (ECEC) in Denmark
• Early Childhood Education and Development in Mexico
• Early Childhood Education in Aotearoa New Zealand
• Early Childhood Education in Australia
• Early Childhood Education in China
• Early Childhood Education in Europe
• Early Childhood Education in Sub-Saharan Africa
• Early Childhood Education in Sweden
• Early Childhood Education Pedagogy
• Early Childhood Education Policy
• Early Childhood Education, The Arts in
• Early Childhood Mathematics
• Early Childhood Science
• Early Childhood Teacher Education
• Early Childhood Teachers in Aotearoa New Zealand
• Early Years Professionalism and Professionalization Polici...
• Economics of Education
• Education For Children with Autism
• Education for Sustainable Development
• Education Leadership, Empirical Perspectives in
• Education of Native Hawaiian Students
• Education Reform and School Change
• Educational Statistics for Longitudinal Research
• Educator Partnerships with Parents and Families with a Foc...
• Emotional and Affective Issues in Environmental and Sustai...
• Emotional and Behavioral Disorders
• Environmental and Science Education: Overlaps and Issues
• Environmental Education
• Environmental Education in Brazil
• Epistemic Beliefs
• Equity and Improvement: Engaging Communities in Educationa...
• Equity, Ethnicity, Diversity, and Excellence in Education
• Ethical Research with Young Children
• Ethics and Education
• Ethics of Teaching
• Ethnic Studies
• Evidence-Based Communication Assessment and Intervention
• Family and Community Partnerships in Education
• Family Day Care
• Federal Government Programs and Issues
• Feminization of Labor in Academia
• Finance, Education
• Financial Aid
• Formative Assessment
• Future-Focused Education
• Gender and Achievement
• Gender and Alternative Education
• Gender-Based Violence on University Campuses
• Gifted Education
• Global Mindedness and Global Citizenship Education
• Global University Rankings
• Governance, Education
• Growth of Effective Mental Health Services in Schools in t...
• Higher Education and Globalization
• Higher Education and the Developing World
• Higher Education Faculty Characteristics and Trends in the...
• Higher Education Finance
• Higher Education Governance
• Higher Education Graduate Outcomes and Destinations
• Higher Education in Africa
• Higher Education in China
• Higher Education in Latin America
• Higher Education in the United States, Historical Evolutio...
• Higher Education, International Issues in
• Higher Education Management
• Higher Education Policy
• Higher Education Research
• Higher Education Student Assessment
• High-stakes Testing
• History of Early Childhood Education in the United States
• History of Education in the United States
• History of Technology Integration in Education
• Homeschooling
• Inclusion in Early Childhood: Difference, Disability, and ...
• Inclusive Education
• Indigenous Education in a Global Context
• Indigenous Learning Environments
• Indigenous Students in Higher Education in the United Stat...
• Infant and Toddler Pedagogy
• Inservice Teacher Education
• Integrating Art across the Curriculum
• Intelligence
• Intensive Interventions for Children and Adolescents with ...
• International Perspectives on Academic Freedom
• Intersectionality and Education
• Knowledge Development in Early Childhood
• Leadership Development, Coaching and Feedback for
• Leadership in Early Childhood Education
• Leadership Training with an Emphasis on the United States
• Learning Analytics in Higher Education
• Learning Difficulties
• Learning, Lifelong
• Learning, Multimedia
• Learning Strategies
• Legal Matters and Education Law
• LGBT Youth in Schools
• Linguistic Diversity
• Linguistically Inclusive Pedagogy
• Literacy Development and Language Acquisition
• Literature Reviews
• Mathematics Identity
• Mathematics Instruction and Interventions for Students wit...
• Mathematics Teacher Education
• Measurement for Improvement in Education
• Measurement in Education in the United States
• Meta-Analysis and Research Synthesis in Education
• Methodological Approaches for Impact Evaluation in Educati...
• Mindfulness, Learning, and Education
• Motherscholars
• Multiliteracies in Early Childhood Education
• Multiple Documents Literacy: Theory, Research, and Applica...
• Multivariate Research Methodology
• Museums, Education, and Curriculum
• Music Education
• Narrative Research in Education
• Native American Studies
• Note-Taking
• Numeracy Education
• One-to-One Technology in the K-12 Classroom
• Online Education
• Open Education
• Organizing for Continuous Improvement in Education
• Organizing Schools for the Inclusion of Students with Disa...
• Outdoor Play and Learning
• Outdoor Play and Learning in Early Childhood Education
• Pedagogical Leadership
• Pedagogy of Teacher Education, A
• Performance Objectives and Measurement
• Performance-based Research Assessment in Higher Education
• Performance-based Research Funding
• Phenomenology in Educational Research
• Philosophy of Education
• Physical Education
• Podcasts in Education
• Policy Context of United States Educational Innovation and...
• Politics of Education
• Portable Technology Use in Special Education Programs and ...
• Post-humanism and Environmental Education
• Pre-Service Teacher Education
• Problem Solving
• Productivity and Higher Education
• Professional Development
• Professional Learning Communities
• Program Evaluation
• Programs and Services for Students with Emotional or Behav...
• Psychology Learning and Teaching
• Psychometric Issues in the Assessment of English Language ...
• Qualitative Data Analysis Techniques
• Qualitative, Quantitative, and Mixed Methods Research Samp...
• Quantitative Research Designs in Educational Research
• Queering the English Language Arts (ELA) Writing Classroom
• Race and Affirmative Action in Higher Education
• Reading Education
• Refugee and New Immigrant Learners
• Relational and Developmental Trauma and Schools
• Relational Pedagogies in Early Childhood Education
• Reliability in Educational Assessments
• Religion in Elementary and Secondary Education in the Unit...
• Researcher Development and Skills Training within the Cont...
• Research-Practice Partnerships in Education within the Uni...
• Response to Intervention
• Restorative Practices
• Risky Play in Early Childhood Education
• Scale and Sustainability of Education Innovation and Impro...
• Scaling Up Research-based Educational Practices
• School Accreditation
• School Choice
• School Culture
• School District Budgeting and Financial Management in the ...
• School Improvement through Inclusive Education
• School Reform
• Schools, Private and Independent
• School-Wide Positive Behavior Support
• Science Education
• Secondary to Postsecondary Transition Issues
• Self-Regulated Learning
• Self-Study of Teacher Education Practices
• Service-Learning
• Severe Disabilities
• Single Salary Schedule
• Single-sex Education
• Single-Subject Research Design
• Social Context of Education
• Social Justice
• Social Network Analysis
• Social Pedagogy
• Social Science and Education Research
• Social Studies Education
• Sociology of Education
• Standards-Based Education
• Student Access, Equity, and Diversity in Higher Education
• Student Assignment Policy
• Student Engagement in Tertiary Education
• Student Learning, Development, Engagement, and Motivation ...
• Student Participation
• Student Voice in Teacher Development
• Sustainability Education in Early Childhood Education
• Sustainability in Early Childhood Education
• Sustainability in Higher Education
• Teacher Beliefs and Epistemologies
• Teacher Collaboration in School Improvement
• Teacher Evaluation and Teacher Effectiveness
• Teacher Preparation
• Teacher Training and Development
• Teacher Unions and Associations
• Teacher-Student Relationships
• Teaching Critical Thinking
• Technologies, Teaching, and Learning in Higher Education
• Technology Education in Early Childhood
• Technology, Educational
• Technology-based Assessment
• The Bologna Process
• The Regulation of Standards in Higher Education
• Theories of Educational Leadership
• Three Conceptions of Literacy: Media, Narrative, and Gamin...
• Tracking and Detracking
• Traditions of Quality Improvement in Education
• Transformative Learning
• Transitions in Early Childhood Education
• Tribally Controlled Colleges and Universities in the Unite...
• Understanding the Psycho-Social Dimensions of Schools and ...
• University Faculty Roles and Responsibilities in the Unite...
• Value of Higher Education for Students and Other Stakehold...
• Virtual Learning Environments
• Vocational and Technical Education
• Wellness and Well-Being in Education
• Women's and Gender Studies
• Young Children and Spirituality
• Young Children's Learning Dispositions
• Young Children's Working Theories
• Privacy Policy
• Cookie Policy
• Legal Notice
• Accessibility

Powered by:

• [66.249.64.20|81.177.182.136]
• 81.177.182.136

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Quantitative Research in Education

2023, Interdisciplinary Research: Collaborative Insights

In the past few decades, educational practices have changed drastically, particularly regarding how information and learning are delivered and processed. Education research frequently employs quantitative methods. Quantitative education research provides numerical data that can prove or disprove a theory, and administrators can easily share the quantitative findings with other academics and districts. While the study may be based on relative sample size, educators and researchers can extrapolate the results from quantitative data to predict outcomes for larger student populations and groups. Educational research has a long history of utilising measurement and statistical methods. Commonly quantitative methods encompass a variety of statistical tests and instruments. Educators and students could transition to the digital era and research-based knowledge, including quantitative research in advanced higher education, as the technology has advanced. The quantitative research methods in education emphasise basic group designs for research and evaluation, analytic methods for exploring relationships between categorical and continuous measures, and statistical analysis procedures for group design data. The essential is to evaluate quantitative analysis and provide the research process, sampling techniques, the advantages and disadvantages of quantitative research in the article.

RELATED PAPERS

Felipe Muñoz

2014 Third European Workshop on Software Defined Networks

sachin sharma

André Bueno

Psychopharmacology

America Tirado

Qurrotu Ayun

Signa: Revista de la Asociación Española de Semiótica

Mario Alonso González

Claudio Ruy Vasconcelos da Fonseca

Antonija Mežnarić

Penélope Cruzado Caballero

Journal of Electronic Imaging

David Gustafson

JURNAL USM LAW REVIEW

bambang sadono

The Eighteenth Century

Angewandte Chemie

Chan ho Park

Cecilia Garavito

Critique d'art

Richard Leeman

Advanced Energy Materials

Bhargav Bhamwala

yyyijuj klklk,l

CHEMICAL & PHARMACEUTICAL BULLETIN

Manabu Matsumura

Journal of Economic Theory

Ana Mauleon

PLOS Neglected Tropical Diseases

Fentaw Tadese

ghfkfg fdgdsf

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

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?

Table of contents

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).

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 April 9, 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”

College of Education and Human Development

Department of Educational Psychology

Quantitative methods in education

Solve problems in education through research.

Students in Quantitative Methods in Education engage in the science and practice of educational measurement and statistics, primarily through the development and application of statistical and psychometric methods. All QME students will engage in coursework addressing fundamental topics related to statistics, educational measurement, research methods, and foundations in education (e.g., learning and cognition, social development). Students will also undertake additional coursework and complete a set of milestones that will specialize their knowledge and scholarship in educational measurement or statistics. Upon matriculation, graduates will be equipped to help inform educational policy, practice, and curriculum and—most importantly—help schools and students succeed.

• Test publishing firms
• Teaching and research at colleges and universities (PhD only)
• Research and evaluation centers
• Public school systems
• State departments of instruction
• Private industry

Quote from V.N. Vimal Rao, PhD '23

The strong theoretical and methodological foundation I developed in QME and EPSY supports my research and my mentoring of student researchers, while the teaching experience and knowledge of educational psychology I gained supports my teaching and mentoring of teaching assistants. V.N. Vimal Rao, PhD '23 Teaching Assistant Professor in the Department of Statistics University of Illinois Urbana Champaign

Submit your MA or PhD application for the fall semester following the deadlines below.

To be considered for fellowships and departmental financial assistance, you must submit all application materials to the program and the Graduate School by the December 1 deadline.

If you're not seeking a fellowship or departmental financial aid, you have until March 1 to submit your application materials.

MA curriculum (33 credits)

PhD curriculum (72 credits)

The QME program strives to provide funding opportunities to all incoming students. While we can’t typically guarantee funding, over the last five years, we have been able to fund over 95% of our students that were looking for funding (including our MA students)!

Visit the College of Education and Human Development's Finance and Funding page for information on tuition.

Fellowships and awards

Submit your application materials by the December 1 deadline, and you’ll automatically be considered for Graduate School fellowships and departmental awards based on scholastic achievement. Notification of awards will be sent in March.

Note: Spring, summer, and fall (March deadline) applicants will not qualify for fellowships.

Graduate assistantships

Get paid to work as a teaching assistant, graduate instructor or research assistant. Graduate assistantships are available through the department, College of Education and Human Development, and the University.

• John P. Yackel/Pearson Graduate Internship
• Jack Merwin Graduate Assistantship
• All University of Minnesota graduate assistantships

Note: Applicants who complete their applications by the March 1 deadline will be less likely to receive graduate assistantships than students who meet the December 1 deadline.

Additional funding

Visit the College of Education and Human Development's Finance and Funding page for more information on funding.

Financial aid

Visit OneStop Student Services for more information on available financial aid.

The Department of Educational Psychology offers a minor in educational psychology with an emphasis in quantitative methods in education.

Quote from Rik Lamm, PhD '23

My background in the QME program has equipped me with the skills necessary for my current role as a Research, Evaluation, and Assessment Scientist for Bloomington Public Schools. These include developing non-cognitive surveys such as student climate surveys and parent engagement surveys, as well as analyzing data from academic assessments such as the MCAs. Additionally, QME has equipped me with the skills to interpret complex data in order to predict longitudinal trends. This ability leads to the development of research-driven strategies that benefit both students and teachers. Rik Lamm, PhD '23 Research, Evaluation, and Assessment Scientist Bloomington Public Schools

Faculty and staff

Chia-yi chiu.

Yackel Professor of Educational Measurement and Assessment

Assistant professor

Nidhi Kohli

Royal and Virginia Anderson Professor of Quantitative Methods in Education; Program Coordinator

Chelsey Legacy

Teaching assistant professor

Assistant Professor

Suzanne Loch

Senior teaching specialist

Michael Rodriguez

CEHD Dean; Campbell Leadership Chair in Education and Human Development; co-founding director of Educational Equity Resource Center

Andrew Zieffler

Teaching professor

Adjunct faculty and program affiliates

Adjunct faculty, claudio violato.

Assistant dean, Medical School

Program affiliates

Adam rothman.

Associate professor, School of Statistics  

Quote from José Palma, PhD '21

It is the combination of psychometric research and applied focus, in addition to knowledge gained from my academic journey, that makes me a competitive and atypical educational measurement researcher today. José Palma, PhD '21 ACES Faculty Fellow and Assistant Professor Texas A&M University

Corissa Rohloff, PhD student in Ed Psych, awarded Russell W. Burris Memorial Fellowship

Corissa Rohloff, PhD candidate in the quantitative methods in education program, has been awarded the Russell W. Burris Memorial Fellowship.

QME recognizes students in year end celebration

Students in the Department of Educational Psychology’s quantitative methods in education (QME) program were recognized for their contributions to the program during the 2022-23 academic year.

Kohli speaks at two international conferences

Dr. Nidhi Kohli, Royal and Virginia Anderson Professor of Quantitative Methods in Education (QME) and Program Coordinator for the QME program in the Department of Educational Psychology, was invited to present at two conferences this summer: the International Meeting of Psychometric Society and the International Indian Statistical Association.

Qualitative vs. Quantitative Research: Comparing the Methods and Strategies for Education Research

No matter the field of study, all research can be divided into two distinct methodologies: qualitative and quantitative research. Both methodologies offer education researchers important insights.

Education research assesses problems in policy, practices, and curriculum design, and it helps administrators identify solutions. Researchers can conduct small-scale studies to learn more about topics related to instruction or larger-scale ones to gain insight into school systems and investigate how to improve student outcomes.

Education research often relies on the quantitative methodology. Quantitative research in education provides numerical data that can prove or disprove a theory, and administrators can easily share the number-based results with other schools and districts. And while the research may speak to a relatively small sample size, educators and researchers can scale the results from quantifiable data to predict outcomes in larger student populations and groups.

Qualitative vs. Quantitative Research in Education: Definitions

Although there are many overlaps in the objectives of qualitative and quantitative research in education, researchers must understand the fundamental functions of each methodology in order to design and carry out an impactful research study. In addition, they must understand the differences that set qualitative and quantitative research apart in order to determine which methodology is better suited to specific education research topics.

Generate Hypotheses with Qualitative Research

Qualitative research focuses on thoughts, concepts, or experiences. The data collected often comes in narrative form and concentrates on unearthing insights that can lead to testable hypotheses. Educators use qualitative research in a study’s exploratory stages to uncover patterns or new angles.

Form Strong Conclusions with Quantitative Research

Quantitative research in education and other fields of inquiry is expressed in numbers and measurements. This type of research aims to find data to confirm or test a hypothesis.

Differences in Data Collection Methods

Keeping in mind the main distinction in qualitative vs. quantitative research—gathering descriptive information as opposed to numerical data—it stands to reason that there are different ways to acquire data for each research methodology. While certain approaches do overlap, the way researchers apply these collection techniques depends on their goal.

Interviews, for example, are common in both modes of research. An interview with students that features open-ended questions intended to reveal ideas and beliefs around attendance will provide qualitative data. This data may reveal a problem among students, such as a lack of access to transportation, that schools can help address.

An interview can also include questions posed to receive numerical answers. A case in point: how many days a week do students have trouble getting to school, and of those days, how often is a transportation-related issue the cause? In this example, qualitative and quantitative methodologies can lead to similar conclusions, but the research will differ in intent, design, and form.

Taking a look at behavioral observation, another common method used for both qualitative and quantitative research, qualitative data may consider a variety of factors, such as facial expressions, verbal responses, and body language.

On the other hand, a quantitative approach will create a coding scheme for certain predetermined behaviors and observe these in a quantifiable manner.

Qualitative Research Methods

• Case Studies : Researchers conduct in-depth investigations into an individual, group, event, or community, typically gathering data through observation and interviews.
• Focus Groups : A moderator (or researcher) guides conversation around a specific topic among a group of participants.
• Ethnography : Researchers interact with and observe a specific societal or ethnic group in their real-life environment.
• Interviews : Researchers ask participants questions to learn about their perspectives on a particular subject.

Quantitative Research Methods

• Questionnaires and Surveys : Participants receive a list of questions, either closed-ended or multiple choice, which are directed around a particular topic.
• Experiments : Researchers control and test variables to demonstrate cause-and-effect relationships.
• Observations : Researchers look at quantifiable patterns and behavior.
• Structured Interviews : Using a predetermined structure, researchers ask participants a fixed set of questions to acquire numerical data.

Choosing a Research Strategy

When choosing which research strategy to employ for a project or study, a number of considerations apply. One key piece of information to help determine whether to use a qualitative vs. quantitative research method is which phase of development the study is in.

For example, if a project is in its early stages and requires more research to find a testable hypothesis, qualitative research methods might prove most helpful. On the other hand, if the research team has already established a hypothesis or theory, quantitative research methods will provide data that can validate the theory or refine it for further testing.

It’s also important to understand a project’s research goals. For instance, do researchers aim to produce findings that reveal how to best encourage student engagement in math? Or is the goal to determine how many students are passing geometry? These two scenarios require distinct sets of data, which will determine the best methodology to employ.

In some situations, studies will benefit from a mixed-methods approach. Using the goals in the above example, one set of data could find the percentage of students passing geometry, which would be quantitative. The research team could also lead a focus group with the students achieving success to discuss which techniques and teaching practices they find most helpful, which would produce qualitative data.

Learn How to Put Education Research into Action

Those with an interest in learning how to harness research to develop innovative ideas to improve education systems may want to consider pursuing a doctoral degree. American University’s School of Education Online offers a Doctor of Education (EdD) in Education Policy and Leadership that prepares future educators, school administrators, and other education professionals to become leaders who effect positive changes in schools. Courses such as Applied Research Methods I: Enacting Critical Research provides students with the techniques and research skills needed to begin conducting research exploring new ways to enhance education. Learn more about American’ University’s EdD in Education Policy and Leadership .

What’s the Difference Between Educational Equity and Equality?

EdD vs. PhD in Education: Requirements, Career Outlook, and Salary

Top Education Technology Jobs for Doctorate in Education Graduates

American University, EdD in Education Policy and Leadership

Edutopia, “2019 Education Research Highlights”

Formplus, “Qualitative vs. Quantitative Data: 15 Key Differences and Similarities”

iMotion, “Qualitative vs. Quantitative Research: What Is What?”

Scribbr, “Qualitative vs. Quantitative Research”

Simply Psychology, “What’s the Difference Between Quantitative and Qualitative Research?”

Typeform, “A Simple Guide to Qualitative and Quantitative Research”

Request Information

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 .

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 .

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 .

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 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.

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

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

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 .

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.

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.

2024 Theses Doctoral

Public-Private Partnerships in Education & Education Reform: A New Theoretical & Applied Approach

MacQuarrie-Tomey, Ashley

Over the last four decades, there has been a significant increase in public-private education partnerships (PPPs). However, rather than reflecting the traditional PPP model where the private sector contributes resources to fulfill public policy agendas, businesses and philanthropies are partnering with urban schools to pursue their goals for reforming public education policy. With billions of dollars being spent by organizations like Microsoft, Meta, the Broad Foundation, and Bloomberg philanthropies on major initiatives to reform public education through teacher training and core curricular Changes, there has been surprisingly little research on the public-private partnership model itself and its impact on education policy. This dissertation intends to address this research gap by considering how public-private partnerships have been traditionally defined and explained in public policy and political science; what has Changed in the structure and purpose of public-private partnerships in education; how do we define and understand an educational public-private partnership in the current context; how do we determine what makes public-private partnerships successful; and based on this new definition, how do we understand their impact on educational public policy priorities? The dissertation aims to accomplish the following: 1) Discuss the existing public policy and political science literature on public-private partnerships. 2) Use anecdotal evidence, research literature, and news reporting to propose a framework for what public-private partnerships in education entail now and what their outcomes appear to be. 3) Identify key performance indicators (KPIs) of success from that literature and test their relevance to the success of current educational PPPs – towards formalizing a new theoretical definition and future guide for applied research. 4) Use both quantitative and qualitative research methods on a sample of partnerships which have already been documented either through original research or third party analytical and narrative reports to analyze and define those key performance indicators which are relevant to current educational PPPs. 5) Through analysis of the intended and actual outcomes of those PPP cases used in previous analysis, demonstrate how current educational PPPs are now both formulating and implementing policy. The importance of this finding is related to debates about the purpose of public education, the definition of public goods, and democratic accountability. 6) Identify the gap between the existing theoretical definition of PPPs and the derived newly proposed framework and the implications for theory, practice and policy. 7) Through a synthesis of the above items, construct an original method and tool for how to form and assess these partnerships for successful outcomes, as well as effective policy.  Applied Qualitative Research The third paper utilizes data from the quantitative research of paper 2 and builds and expands on the findings by using a qualitative methodology to analyze cases which have a more robust narrative. The cases I consider are Bloomberg philanthropies Global Scholars and Mark Zuckerberg’s Newark public schools. I document the functional, political, and financial differences between the cases, as well as how the PPPs were implemented. This applied research considers the indicators which proved relevant in the prior quantitative research through a qualitative analysis of materials, reports, and interviews. Applied Quantitative Research This second paper is applied quantitative research and serves as the bridge between the literature and theory to current applications and directs the focus of the subsequent applied qualitative research in this dissertation. I take the elements identified as standard KPIs from literature and prior research studies and using the documentation from the united way portfolio I test the relevance of those existing KPIs to the current theoretical framework. The Detroit cases are ideal for this portion of the research as those cases were created as PPPs and concluded (at least as far as an initial MOU agreement) within a specific timeframe. I collected all the documentation on those partnerships and their elements using a measurement system I developed. I use a quantitative method of binary logic regression to consider, given the documented outcomes of those cases, whether there is simple significance of an indicator as it relates to a quantitative definition of success. My metric is whether more than 50% of the objectives outlined in the MOUs were successfully completed. The quantitative methodology is important, because it allows us to determine which indicators remain relevant and warrant further study. At the end of this paper the advantages and limitations of quantitative analysis will be discussed, as well as thoughts about how qualitative analysis may help further the research going forward. This serves as a bridge to the next section/chapter. The purpose of this paper is to move beyond simply identifying components of the PPPs, as was done in the second paper, to more fully articulate and define them. I also identify the variance in PPP outcomes which may come from leadership structure, organizational occupation (for profit, nonprofit, public) and other operational and political variables. This section draws heavily on my research which uses a qualitative comparative frame to analyze the BP and Zuckerberg cases. The importance of these findings, as well as the advantages and limitations of this methodology are also be discussed. Toward a Theoretical Framework for PPPs & a New Tool for Evaluation Research The third paper of the dissertation synthesizes the analysis from the previous two papers in order to integrate both sets of findings and limitations in order to better define and understand current educational PPPs. This will lead to a new proposed theory of PPPs in education, to be followed by an analytic discussion, which will rely on research I have already done. The new proposed theory will be compared to the existing theory. The empirical evidence will make clear that new forms of PPPs have been implemented that are not accounted for in the existing theory. The implications of these findings will be important for both public and private actors who will need to think about and formulate PPPs in different ways than they have been doing. Once this is explicated, I consider the implications of substituting PPPs for the traditional policymaking process, and what can reasonably be anticipated as outcomes for public goods and democratic accountability. PPPs must be understood as an alternative pathway to policymaking which most often will not include traditional policy makers, and by virtue of financial and operational conditions, will fast track educational reforms. This increase in speed and coherence of reform is likely to be accompanied by a decline in democratic accountability, which particularly as it concerns public K-12 education, may fundamentally change the nature of that specific public good, and may even extend to a larger reconceptualization in the country of the concept of public goods. The last section of the third paper moves from the theoretical to the applied. This section discusses how the research gathered and synthesized in the previous two papers contributes to an applied framework for formulating and assessing educational PPPs for rates of success. This is especially important as we can expect that there will not be a decline in educational PPPs, but rather an ever-growing prevalence of them in American public education systems. I then make the case specifically for the use of comparative-qualitative analysis as an appropriate analytic frame for an evaluation tool. The section then goes on to detail the development of this tool, which relies on the methods and findings of the previous applied research sections in the dissertation. I provide a methodology for documenting the qualitative elements to be observed through an interview protocol, as well as the methodology by which that qualitative data can be converted to a quantitative value using previously discussed key variables and then cross-assessed with other related variables, weighted, and inputted into a prescribed algorithm (using analytics frames from educational performance evaluations, quantitative regression, and machine learning prediction principles). This will produce a predictive outcome of success and a meta frame to compare and contrast different educational PPPs going forward. This aspect of the research is important, as it provides practitioners, educators, policymakers, and public and private leadership a better understanding of what in fact they are doing when attempting to formulate and implement a public private partnership; what elements they should seek to build into their partnership in order to create increased conditions for successful outcomes; and finally how as researchers, we might, in the future, have a tool to observe, track, and evaluate these partnerships to further our theoretical and applied understanding of educational policy.

Geographic Areas

• New Jersey--Newark
• Education and state
• School management and organization
• Political science
• Public policy (Law)
• Public-private sector cooperation
• Education--Political aspects
• Zuckerberg, Mark, 1984-

More About This Work

• DOI Copy DOI to clipboard

Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded.

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

Main Navigation

• Accept offer and enrol
• Current Students

Personalise your experience

Did you mean..., diploma of arts and social sciences, art/science collaboration wins waterhouse natural science art prize, unit of study educ7019 playing with theory and research methodology in education part 2 (2025).

Future students: T: 1800 626 481 E: Email your enquiry here

Current students: Contact: Faculty of Education

Students studying at an education collaboration: Please contact your relevant institution

updated - DO NOT REMOVE THIS LINE 6:07 AM on Tue, 9 April

Show me unit information for year

Unit snapshot.

PG Coursework Unit

Credit points

Faculty & college.

Faculty of Education

Enrolment information

One intensive on-site workshop (2 days in total) is held on the Gold Coast campus. Attendance at the workshop is compulsory.

Unit description

Moves students through the major tenets of educational theory and research methodology.  Students will engage with cutting-edge, conventional and historic theories and methodologies in education and the social sciences.  They will examine qualitative, post-qualitative and quantitative methodologies, and how they may be put to work with/through theory.  The unit incorporates direct research experience enabling students to work and play with theory and methodology in creative and innovative ways.

Unit content

• What comes before theory: Playing with the ‘ologies’; 
• Playing and working with theorists and theory in education and learning; and
• Paying and working with methodology: Qualitative, post-qualitative and quantitative methodologies.

Availabilities

2025 unit offering information will be available in November 2024

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes . The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:

critically identify the major tenets of educational theory

critically identify the major tenets of educational research methodologies

understand the nexus between epistemology, theory, methodology and methods in educational research

identify appropriate theory and research methodology to address educational problems or issues

design, plan and pilot a theory/methodology for an identified educational problem or issue

Fee information

Commonwealth Supported courses For information regarding Student Contribution Amounts please visit the Student Contribution Amounts .

Fee paying courses For postgraduate or undergraduate full-fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees .

International

Please check the international course and fee list to determine the relevant fees.

Any questions? We'd love to help

Science & Quantitative Reasoning Education

Yale undergraduate research, key to harnessing light waves first do the math.

A new, Yale-developed mathematical model to predict thermal energy transfer could help improve energy-harvesting technologies and impact optics and photonics.