research paper with paired t test

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The paired t test and beyond: Recommendations for testing the central tendencies of two paired samples in research on speech, language and hearing pathology

Affiliations.

1 Centre for Language Studies, Radboud University, Erasmusplein 1, 6525 HT Nijmegen, The Netherlands. Electronic address: [email protected].
2 Centre for Language Studies, Radboud University, Erasmusplein 1, 6525 HT Nijmegen, The Netherlands.
PMID: 28777928
DOI: 10.1016/j.jcomdis.2017.07.002

Purpose: In this tutorial we review current practice in the analysis of data obtained in designs involving two dependent samples and evaluate two conventional statistics: the t test for paired samples and its non-parametric alternative, the Wilcoxon Signed Ranks test (WSR). It is a sequel to our tutorial on the analysis of designs with two independent samples on the basis of non-count data (Rietveld & van Hout, 2015). The frequency with which these statistics are used is assessed on the basis of publications on disordered communication in Clinical Linguistics & Phonetics, Journal of Communication Disorders and Journal of Speech, Language and Hearing Research for the time interval 2006-2015. We conclude with a number of recommendations for the analysis and presentation of data.

Conclusions: Researchers should more consistently present the relevant characteristics of their data (means, medians, SD, skewness, tailedness, outliers etc.) and explicitly consider the assumptions that apply to their statistical methods, such as correlations between data obtained on two occasions, interactions between participants and treatment, and the symmetry of difference scores, many of which are hardly ever reported or even tested. Two recommendations are particularly relevant. First, the WSR is not a proper test for central tendencies as a replacement of the conventional t test for paired samples whenever assumptions about the dependent variable are in doubt. Second, researchers should choose statistical procedures on the basis of the null hypothesis (H0) to be tested and not primarily on the basis of the type of data (ordinal or interval). Two relevant H0's in the field of speech-language pathology are: (1) μ 1 =μ 2 (the mean obtained in condition 1 is equal to the mean in condition 2) and (2) p=0.5, which says: the probability to obtain (for instance) higher scores in condition 2 than in condition 1 is 0.5. We recommend the permuted t test for paired samples to test the first H0 and the permuted Brunner-Munzel rank test to test the second.

Keywords: Assumptions for nonparametric statistics; Recent developments in the analysis of data obtained in paired samples designs; Statistical interaction and correlation in paired samples designs; Tests for paired samples.

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Paired Samples T-Test

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Amanda Ross 3 &
Victor L. Willson 4

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A paired-samples t -test compares the mean of two matched groups of people or cases, or compares the mean of a single group, examined at two different points in time. If the same group is tested again, on the same measure, the t-test is called a repeated measures t -test.

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Ross, A., Willson, V.L. (2017). Paired Samples T-Test. In: Basic and Advanced Statistical Tests. SensePublishers, Rotterdam. https://doi.org/10.1007/978-94-6351-086-8_4

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Published: 08 November 2019

Analysis of t- test misuses and SPSS operations in medical research papers

Guangping Liang 1 ,
Wenliang Fu 1 &
Kaifa Wang ORCID: orcid.org/0000-0002-6787-5018 2

Burns & Trauma volume 7 , Article number: 31 ( 2019 ) Cite this article

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In medical research papers, the selection of appropriate statistical methods serves as one of the pivotal premises to ensure the quality of papers and credibility of their results [ 1 , 2 , 3 ]. To correctly perform the statistical analysis of quantitative data, two key points should be considered. One is to identify the type of experimental design correctly, and the other is to check whether data meets the preconditions of parameter test [ 2 , 3 , 4 ]. Otherwise, it may cause different misuse in some situations and may even draw different or opposite conclusions about the same data.

As one of the most commonly used statistical methods in medical research papers, t- test can be divided into one-sample t- test and two-sample t- test [ 3 , 4 ]. Thus, it is inappropriate to compare the means among multiple groups (more than three). Concretely, one-sample t- test is used to compare one group’s average value to a single number (a known population mean, for example, the norm). The two-sample t test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups. Furthermore, there are two types of two-sample t -test [ 3 , 4 ]. One is independent sample t- test (group t- test), which is performed when the samples typically consist of independent population. The other is paired (or correlated) sample t- test, which is used when each observation in one group is paired with a related observation in the other group, i.e., the samples typically consist of matched pairs of similar units, or when there are cases of repeated measures.

Note that t- test belongs to the category of parametric test. The assumptions of the parametric test, including independence, normality, and homogeneity of variance, must be met to ensure the correct use of t- test [ 3 , 4 ]. In addition, according to the theoretical deduction of t- test, it can only be applied to the quantitative data of single factor design, so it is inappropriate to perform t- test for multifactor design. For example, there are multiple independent variables/factors (such as gender and different types and dosage of drugs) and the comparisons among groups after controlling for simple effects of each independent variable.

As a journal editor and reviewer, we often encounter that some authors blindly use t- test to process quantitative data without analyzing the prerequisites of t- test or considering the type of experimental design, especially to independent sample t- test (group t- test). In order to improve the quality of statistical analysis in medical research papers, according to the problems found in the process of reviewing manuscripts, we summarized the following five most common misuses of t- test and analyzed them with examples. We hope that it can provide real help to improve our data analysis ability.

It is particularly noted that all the examples herein are artificially constructed for the purpose of illustration and do not represent actual clinical design and data. They are only for reference in the selection of statistical analysis methods.

Misuse of t- test because data do not obey normal distribution

Normal fitting tests, including the Shapiro-Wilk test for small sample size ( n ≤ 50) or Kolmogorov-Smirnov test for large sample size ( n > 50), usually require the analysis of the original data. However, there is a common and concise method to judge whether the data obey normal distribution, that is, to compare the mean and corresponding standard deviation (SD) of the data. If the mean is much smaller than its standard deviation, then the data may not obey the normal distribution, so t- test may also be inappropriate. In this case, it is better to perform t- test after an appropriate variable transformation (such as logarithm transforms and rank transforms) or perform nonparametric test method for original data.

A researcher adopts the independent sample t- test to compare the demographic data (age) between the experimental group and the control group. Table 1 provides the statistical results (see Additional file 1 for the original data). Is this appropriate?

The data are quantitative data for two independent samples under single factor design. However, from Table 1 , we can find that the standard deviation is larger than its mean value in control group. Thus, the age in control group may not meet normal distribution. As a result, it may be inappropriate to analyze this data by the independent sample t- test directly.

[Correction]

Since the sample size of two groups is less than 50, the Shapiro-Wilk test is more suitable for normal fitting test. Selecting “Analyze➔Descriptive Statistics➔Explore…” and ticking “Normality plots with tests” in the “Plots” dialog box in SPSS. The results show that the age in experimental group accepts the normal distribution hypothesis ( W = 0.915, p = 0.080), but the age in control group rejects the normal distribution hypothesis ( W = 0.635, p < 0.001). Therefore, appropriate variable transformation should be performed if t- test must be used. In fact, the nonparametric Wilcoxon rank sum W test is a simpler and more suitable statistical method, and the Mann-Whitney U test method should be selected in this case. Selecting “Analyze➔Nonparametric Tests➔2 Independent Samples…” and ticking “Mann-Whitney U ” in “Test Type” part. After performing the test in SPSS, we have the test statistic U = 116.500 and p = 0.024. As a result, we can conclude that the difference of mean rank has statistical significance between the experimental group and control group, which is completely contrary to the results of independent sample t- test (Table 1 ). By the way, when a variable does not obey the normal distribution, it is better to report as median with its corresponding first and third quartiles (Q1–Q3) or median with its range, not as mean and standard deviation. In the following parts, all variables are subject to the assumption of normal distribution without special explanation.

Misuse of independent sample t- test because of paired samples

In medical research, before-after study in the same patient is often used to compare the effect of a treatment factor (such as drug and operation). This is a typical self-matching experimental design type, which does not meet the independent assumption of independent sample t- test. In this case, the paired sample t- test is more suitable if the difference value is met normally distributed. Otherwise, the nonparametric test (Wilcoxon signed rank test) of two related samples is recommended.

In order to explore the effect of a certain treatment scheme on the scar of burn patients, the scar area of the patients is measured 1 day before and 1 week after treatment, respectively. And the independent sample t- test is used to compare the changes of scar area of the patients before and after treatment. Table 2 shows the statistical results (see Additional file 2 for the original data). Is this appropriate?

Clearly, the independent assumption of independent sample t- test is not satisfied under the study protocol, and independent sample t- test is inappropriate for the data.

Using the origin data and paired samples t- test, i.e., selecting “Analyze➔Compare Means➔Paired-Samples T Test…” in SPSS, we have the test statistic t = 10.025 and p < 0.001. It should be noted that in this example, by comparing the p values obtained by the two methods, we find that the result of the independent sample t- test may underestimate the efficacy of the treatment scheme, though both results indicate that the treatment scheme can significantly reduce the scar area of burn patients.

Misuse of independent sample t- test because there are more than three levels in independent samples

The single factor k -level ( k ≥ 3) independent sample design is a widely used experimental design method in medical experiments. For example, to investigate the difference of a physiological index with different disease types, we measured the index of patients with k ( k ≥ 3) disease types. In this case, we need to compare the means among k independent samples and determine whether there are any statistically significant differences between the means of three or more independent (unrelated) groups. Because direct multiple use of independent samples t- test will increase the probability of type I error, one-way analysis of variance (ANOVA) is more suitable at this time. If the one-way ANOVA returns a statistically significant result, we accept the alternative hypothesis, which is that there are at least two group means that are statistically significantly different from each other. To determine which specific groups differed from each other, we further need to perform post hoc multiple comparisons. If we want to compare each group with the control group, Dunnett’s test is recommended.

For a new antihypertensive drug, we hope to compare the antihypertensive effect of high- and low-dose groups with that of placebo group. The independent sample t- test is adopted to compare the low-dose group with the placebo group and the high-dose group with the placebo group, respectively. The statistic results are presented in Table 3 (see Additional file 3 for the original data). Is this appropriate?

These data are typical quantitative data of multigroup independent sample design, also known as the single factor design with multiple levels, and the number of levels is 3. Thus, it is not appropriate to perform the independent sample t- test directly for comparisons with control group.

According to the study design, selecting “Analyze➔Compare Means➔One-Way ANOVA…” and ticking “Dunnett” in the “Post Hoc Multiple Comparisons” dialog box in SPSS, we perform one-way ANOVA and Dunnett’s post hoc test to compare each dose group with the placebo group. The results indicate that there is a statistically significant difference between groups as determined by one-way ANOVA ( F = 24.728, p < 0.001). The results of multiple comparisons show that the difference between low-dose group and placebo group is not statistically significant ( p = 0.069), which is completely contrary to the results of the independent sample t -test (Table 3 ). The difference between high-dose group and placebo group is still statistically significant ( p < 0.001).

Misuse of independent sample t- test because of factorial design data

To understand the effect of two or more independent variables upon a single dependent variable, completely randomized factorial design is often used in medical experiments or clinical trials. A factor is a variable that is controlled and varied during the course of an experiment. In a factorial design, there are two or more factors with multiple levels that are crossed, e.g., two dose levels of drug A and two levels of drug B can be crossed to yield a total of four treatment combinations. Factorial designs offer certain advantages over conventional designs. The design can examine not only the differences among the levels of each factor, but also the interactions among the factors. For quantitative data of factorial design, direct multiple use of independent sample t- test will not only increase the probability of type I error, but also lead to wrong conclusions when there is interaction between various factors. A more appropriate method at this point is to perform ANOVA of factorial design. Taking two factors of independent samples as an example, it is also called the two-way ANOVA of independent samples.

To study the difference of pain score between patients with different disease types (burn, trauma, and arthritis) after receiving two treatment schemes (named as scheme A and scheme B), ten patients were recruited for each type of disease and randomly assigned to the possible treatment schemes with equal possibility. For the measured pain scores, independent sample t- tests are performed repeatedly to compare the difference between disease types and treatment schemes. Table 4 shows the statistical results (see Additional file 4 for the original data). Is this appropriate?

This study involves two factors. One is treatment factor with two levels, scheme A and scheme B, while the other is disease type factor with three levels, burns, trauma, and arthritis. Since the patients in each level combination are different, the samples are independent. Therefore, this study belongs to the 2 × 3 factorial design, and the ANOVA of factorial design should be performed for comparative analysis. Firstly, the interaction effect between the factors should be tested. If the interaction effect is not statistically significant, the main effect of each factor can be analyzed. Otherwise, the individual effect of each factor needs to be analyzed separately.

ANOVA of factorial design should be performed using the General Linear Model in SPSS (selecting “Analyze➔General Linear Model➔Univariate…”), and the results show that the interaction term between treatment and disease type reaches the significance level ( p < 0.001), indicating that the interaction of these two factors does have an effect on the dependent variable (pain score). Therefore, it is necessary to conduct simple primary effect test for each factor. Since these two factors are independent samples, the “Split File” instruction under drop-down menu of “Data” in SPSS can be used to select qualified samples for independent sample one-way ANOVA. Through the test, in the case of scheme B, we find that there is no statistically significant difference in the pain scores between the burn/trauma and arthritis ( p = 0.067/0.187), which is completely contrary to the results of independent sample t- test (Table 4 ).

Misuse of independent sample t- test because of repeated measurement design

Repeated measurement designs are commonly used in longitudinal studies, such as the dynamic changes over time of temperature, blood pressure, and other indicators, which is often encountered in medical research. The purpose is usually to detect whether there is a statistical significance in the difference of the indicator values at different time points. In practice, many authors usually calculate the mean and standard deviation of each time point, and then carry out independent sample t- test repeatedly for each time point. However, according to the design principle, we know that repeated measures design uses the same subjects with every condition of the research, including the control. Thus, the measurements at different time points are correlated with each other, that is, the samples at different time points are not independent of each other. Roughly speaking, such data are often time-dependent. In this case, the appropriate analysis method is ANOVA of repeated measures designs. If there is another factor with independent samples, two-way ANOVA with mixed samples is recommended.

To study the difference for a certain indicator at different postoperative time points, 10 patients (5 males and 5 females) are enrolled in the study and the indictor of each of them is measured at 1, 2, 4, and 8 weeks after the operation. The researchers use the independent sample t- test to analyze the difference of this indictor of different time points. The statistical results are presented in Table 5 (see Additional file 5 for the original data). Is this appropriate?

According to the experimental process of this study, the indicators of each patient are repeatedly measured at 1 week, 2 weeks, 4 weeks, and 8 weeks after the surgery, so the postoperative time serves as a factor of repeated measurement with four levels. In addition, gender is another factor, which is an independent sample at each level. Thus, the overall design was separated by pairwise comparison at different time points through independent sample t- test and fails to take into account the fact that the data on the same subject at different time points are not independent.

Two-way ANOVA with mixed samples should be performed using the General Linear Model in SPSS (selecting “Analyze➔General Linear Model➔Repeated Measures…”). Similarly, since the interaction between gender and postoperative time reaches the level of significance ( p < 0.001), it is necessary to perform simple primary effect test. However, since the gender factor is an independent sample and the postoperative time factor is a related sample, the test methods for the two factors are different. For gender factor, four independent sample one-way ANOVA analyses were performed based on the four levels of postoperative time, but for postoperative time factor, two related sample ANOVAs were carried out based on the two levels of gender. Using the original data, we can find that the difference between 1 week after operation and 8 weeks after operation is not statistically significant in males ( p = 0.057), but there is a significant difference between 8 weeks after operation and 1 week after operation in females ( p = 0.045), which was completely contrary to the results of independent sample t- test (Table 5 ).

In summary, in order to effectively reduce misuse of statistical methods and improve credibility of the statistical results, it is necessary to carefully consider the experimental design type, distribution characteristics of the data, and other relevant factors. Concretely, we should meticulously review the applicable preconditions of each statistical analysis technique and reasonably select the appropriate method before analysis of quantitative data. In this paper, the five cases of most commonly misused t- tests are summarized, with the causes of each misuse analyzed and the more appropriate statistical methods are also offered in SPSS. By doing so, we believe that this paper can be helpful to the writing and editing of biomedical research papers.

Availability of data and materials

All artificially constructed data are presented in the tables and additional files.

Abbreviations

Analysis of variance

Standard deviation

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The conception and design was developed by GL and KW. The article drafting and revising were performed by WF and KW. The data analysis and interpretation, revision, and final approval of article were carried out by WF, GL, and KW.

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Correspondence to Kaifa Wang .

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Liang, G., Fu, W. & Wang, K. Analysis of t- test misuses and SPSS operations in medical research papers. Burn Trauma 7 , 31 (2019). https://doi.org/10.1186/s41038-019-0170-3

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DOI : https://doi.org/10.1186/s41038-019-0170-3

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Published: 02 May 2024

Effectiveness of social media-assisted course on learning self-efficacy

Jiaying Hu 1 ,
Yicheng Lai 2 &
Xiuhua Yi 3

Scientific Reports volume 14 , Article number: 10112 ( 2024 ) Cite this article

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Human behaviour

The social media platform and the information dissemination revolution have changed the thinking, needs, and methods of students, bringing development opportunities and challenges to higher education. This paper introduces social media into the classroom and uses quantitative analysis to investigate the relation between design college students’ learning self-efficacy and social media for design students, aiming to determine the effectiveness of social media platforms on self-efficacy. This study is conducted on university students in design media courses and is quasi-experimental, using a randomized pre-test and post-test control group design. The study participants are 73 second-year design undergraduates. Independent samples t-tests showed that the network interaction factors of social media had a significant impact on college students learning self-efficacy. The use of social media has a significant positive predictive effect on all dimensions of learning self-efficacy. Our analysis suggests that using the advantages and value of online social platforms, weakening the disadvantages of the network, scientifically using online learning resources, and combining traditional classrooms with the Internet can improve students' learning self-efficacy.

Impact of artificial intelligence on human loss in decision making, laziness and safety in education

Misunderstanding the harms of online misinformation

Determinants of behaviour and their efficacy as targets of behavioural change interventions

Introduction.

Social media is a way of sharing information, ideas, and opinions with others one. It can be used to create relationships between people and businesses. Social media has changed the communication way, it’s no longer just about talking face to face but also using a digital platform such as Facebook or Twitter. Today, social media is becoming increasingly popular in everyone's lives, including students and researchers 1 . Social media provides many opportunities for learners to publish their work globally, bringing many benefits to teaching and learning. The publication of students' work online has led to a more positive attitude towards learning and increased achievement and motivation. Other studies report that student online publications or work promote reflection on personal growth and development and provide opportunities for students to imagine more clearly the purpose of their work 2 . In addition, learning environments that include student publications allow students to examine issues differently, create new connections, and ultimately form new entities that can be shared globally 3 , 4 .

Learning self-efficacy is a belief that you can learn something new. It comes from the Latin word “self” and “efficax” which means efficient or effective. Self-efficacy is based on your beliefs about yourself, how capable you are to learn something new, and your ability to use what you have learned in real-life situations. This concept was first introduced by Bandura (1977), who studied the effects of social reinforcement on children’s learning behavior. He found that when children were rewarded for their efforts they would persist longer at tasks that they did not like or had low interest in doing. Social media, a ubiquitous force in today's digital age, has revolutionized the way people interact and share information. With the rise of social media platforms, individuals now have access to a wealth of online resources that can enhance their learning capabilities. This access to information and communication has also reshaped the way students approach their studies, potentially impacting their learning self-efficacy. Understanding the role of social media in shaping students' learning self-efficacy is crucial in providing effective educational strategies that promote healthy learning and development 5 . Unfortunately, the learning curve for the associated metadata base modeling methodologies and their corresponding computer-aided software engineering (CASE) tools have made it difficult for students to grasp. Addressing this learning issue examined the effect of this MLS on the self-efficacy of learning these topics 6 . Bates et al. 7 hypothesize a mediated model in which a set of antecedent variables influenced students’ online learning self-efficacy which, in turn, affected student outcome expectations, mastery perceptions, and the hours spent per week using online learning technology to complete learning assignments for university courses. Shen et al. 8 through exploratory factor analysis identifies five dimensions of online learning self-efficacy: (a) self-efficacy to complete an online course (b) self-efficacy to interact socially with classmates (c) self-efficacy to handle tools in a Course Management System (CMS) (d) self-efficacy to interact with instructors in an online course, and (e) self-efficacy to interact with classmates for academic purposes. Chiu 9 established a model for analyzing the mediating effect that learning self-efficacy and social self-efficacy have on the relationship between university students’ perceived life stress and smartphone addiction. Kim et al. 10 study was conducted to examine the influence of learning efficacy on nursing students' self-confidence. The objective of Paciello et al. 11 was to identify self-efficacy configurations in different domains (i.e., emotional, social, and self-regulated learning) in a sample of university students using a person-centered approach. The role of university students’ various conceptions of learning in their academic self-efficacy in the domain of physics is initially explored 12 . Kumar et al. 13 investigated factors predicting students’ behavioral intentions towards the continuous use of mobile learning. Other influential work includes 14 .

Many studies have focused on social networking tools such as Facebook and MySpace 15 , 16 . Teachers are concerned that the setup and use of social media apps take up too much of their time, may have plagiarism and privacy issues, and contribute little to actual student learning outcomes; they often consider them redundant or simply not conducive to better learning outcomes 17 . Cao et al. 18 proposed that the central questions in addressing the positive and negative pitfalls of social media on teaching and learning are whether the use of social media in teaching and learning enhances educational effectiveness, and what motivates university teachers to use social media in teaching and learning. Maloney et al. 3 argued that social media can further improve the higher education teaching and learning environment, where students no longer access social media to access course information. Many studies in the past have shown that the use of modern IT in the classroom has increased over the past few years; however, it is still limited mainly to content-driven use, such as accessing course materials, so with the emergence of social media in students’ everyday lives 2 , we need to focus on developing students’ learning self-efficacy so that they can This will enable students to 'turn the tables and learn to learn on their own. Learning self-efficacy is considered an important concept that has a powerful impact on learning outcomes 19 , 20 .

Self-efficacy for learning is vital in teaching students to learn and develop healthily and increasing students' beliefs in the learning process 21 . However, previous studies on social media platforms such as Twitter and Weibo as curriculum support tools have not been further substantiated or analyzed in detail. In addition, the relationship between social media, higher education, and learning self-efficacy has not yet been fully explored by researchers in China. Our research aims to fill this gap in the topic. Our study explored the impact of social media on the learning self-efficacy of Chinese college students. Therefore, it is essential to explore the impact of teachers' use of social media to support teaching and learning on students' learning self-efficacy. Based on educational theory and methodological practice, this study designed a teaching experiment using social media to promote learning self-efficacy by posting an assignment for post-course work on online media to explore the actual impact of social media on university students’ learning self-efficacy. This study examines the impact of a social media-assisted course on university students' learning self-efficacy to explore the positive impact of a social media-assisted course.

Theoretical background

Social media

Social media has different definitions. Mayfield (2013) first introduced the concept of social media in his book-what is social media? The author summarized the six characteristics of social media: openness, participation, dialogue, communication, interaction, and communication. Mayfield 22 shows that social media is a kind of new media. Its uniqueness is that it can give users great space and freedom to participate in the communication process. Jen (2020) also suggested that the distinguishing feature of social media is that it is “aggregated”. Social media provides users with an interactive service to control their data and information and collaborate and share information 2 . Social media offers opportunities for students to build knowledge and helps them actively create and share information 23 . Millennial students are entering higher education institutions and are accustomed to accessing and using data from the Internet. These individuals go online daily for educational or recreational purposes. Social media is becoming increasingly popular in the lives of everyone, including students and researchers 1 . A previous study has shown that millennials use the Internet as their first source of information and Google as their first choice for finding educational and personal information 24 . Similarly, many institutions encourage teachers to adopt social media applications 25 . Faculty members have also embraced social media applications for personal, professional, and pedagogical purposes 17 .

Social networks allow one to create a personal profile and build various networks that connect him/her to family, friends, and other colleagues. Users use these sites to stay in touch with their friends, make plans, make new friends, or connect with someone online. Therefore, extending this concept, these sites can establish academic connections or promote cooperation and collaboration in higher education classrooms 2 . This study defines social media as an interactive community of users' information sharing and social activities built on the technology of the Internet. Because the concept of social media is broad, its connotations are consistent. Research shows that Meaning and Linking are the two key elements that make up social media existence. Users and individual media outlets generate social media content and use it as a platform to get it out there. Social media distribution is based on social relationships and has a better platform for personal information and relationship management systems. Examples of social media applications include Facebook, Twitter, MySpace, YouTube, Flickr, Skype, Wiki, blogs, Delicious, Second Life, open online course sites, SMS, online games, mobile applications, and more 18 . Ajjan and Hartshorne 2 investigated the intentions of 136 faculty members at a US university to adopt Web 2.0 technologies as tools in their courses. They found that integrating Web 2.0 technologies into the classroom learning environment effectively increased student satisfaction with the course and improved their learning and writing skills. His research focused on improving the perceived usefulness, ease of use, compatibility of Web 2.0 applications, and instructor self-efficacy. The social computing impact of formal education and training and informal learning communities suggested that learning web 2.0 helps users to acquire critical competencies, and promotes technological, pedagogical, and organizational innovation, arguing that social media has a variety of learning content 26 . Users can post digital content online, enabling learners to tap into tacit knowledge while supporting collaboration between learners and teachers. Cao and Hong 27 investigated the antecedents and consequences of social media use in teaching among 249 full-time and part-time faculty members, who reported that the factors for using social media in teaching included personal social media engagement and readiness, external pressures; expected benefits; and perceived risks. The types of Innovators, Early adopters, Early majority, Late majority, Laggards, and objectors. Cao et al. 18 studied the educational effectiveness of 168 teachers' use of social media in university teaching. Their findings suggest that social media use has a positive impact on student learning outcomes and satisfaction. Their research model provides educators with ideas on using social media in the education classroom to improve student performance. Maqableh et al. 28 investigated the use of social networking sites by 366 undergraduate students, and they found that weekly use of social networking sites had a significant impact on student's academic performance and that using social networking sites had a significant impact on improving students' effective time management, and awareness of multitasking. All of the above studies indicate the researcher’s research on social media aids in teaching and learning. All of these studies indicate the positive impact of social media on teaching and learning.

Learning self-efficacy

For the definition of concepts related to learning self-efficacy, scholars have mainly drawn on the idea proposed by Bandura 29 that defines self-efficacy as “the degree to which people feel confident in their ability to use the skills they possess to perform a task”. Self-efficacy is an assessment of a learner’s confidence in his or her ability to use the skills he or she possesses to complete a learning task and is a subjective judgment and feeling about the individual’s ability to control his or her learning behavior and performance 30 . Liu 31 has defined self-efficacy as the belief’s individuals hold about their motivation to act, cognitive ability, and ability to perform to achieve their goals, showing the individual's evaluation and judgment of their abilities. Zhang (2015) showed that learning efficacy is regarded as the degree of belief and confidence that expresses the success of learning. Yan 32 showed the extent to which learning self-efficacy is viewed as an individual. Pan 33 suggested that learning self-efficacy in an online learning environment is a belief that reflects the learner's ability to succeed in the online learning process. Kang 34 believed that learning self-efficacy is the learner's confidence and belief in his or her ability to complete a learning task. Huang 35 considered self-efficacy as an individual’s self-assessment of his or her ability to complete a particular task or perform a specific behavior and the degree of confidence in one’s ability to achieve a specific goal. Kong 36 defined learning self-efficacy as an individual’s judgment of one’s ability to complete academic tasks.

Based on the above analysis, we found that scholars' focus on learning self-efficacy is on learning behavioral efficacy and learning ability efficacy, so this study divides learning self-efficacy into learning behavioral efficacy and learning ability efficacy for further analysis and research 37 , 38 . Search the CNKI database and ProQuest Dissertations for keywords such as “design students’ learning self-efficacy”, “design classroom self-efficacy”, “design learning self-efficacy”, and other keywords. There are few relevant pieces of literature about design majors. Qiu 39 showed that mobile learning-assisted classroom teaching can control the source of self-efficacy from many aspects, thereby improving students’ sense of learning efficacy and helping middle and lower-level students improve their sense of learning efficacy from all dimensions. Yin and Xu 40 argued that the three elements of the network environment—“learning content”, “learning support”, and “social structure of learning”—all have an impact on university students’ learning self-efficacy. Duo et al. 41 recommend that learning activities based on the mobile network learning community increase the trust between students and the sense of belonging in the learning community, promote mutual communication and collaboration between students, and encourage each other to stimulate their learning motivation. In the context of social media applications, self-efficacy refers to the level of confidence that teachers can successfully use social media applications in the classroom 18 . Researchers have found that self-efficacy is related to social media applications 42 . Students had positive experiences with social media applications through content enhancement, creativity experiences, connectivity enrichment, and collaborative engagement 26 . Students who wish to communicate with their tutors in real-time find social media tools such as web pages, blogs, and virtual interactions very satisfying 27 . Overall, students report their enjoyment of different learning processes through social media applications; simultaneously, they show satisfactory tangible achievement of tangible learning outcomes 18 . According to Bandura's 'triadic interaction theory’, Bian 43 and Shi 44 divided learning self-efficacy into two main elements, basic competence, and control, where basic competence includes the individual's sense of effort, competence, the individual sense of the environment, and the individual's sense of control over behavior. The primary sense of competence includes the individual's Sense of effort, competence, environment, and control over behavior. In this study, learning self-efficacy is divided into Learning behavioral efficacy and Learning ability efficacy. Learning behavioral efficacy includes individuals' sense of effort, environment, and control; learning ability efficacy includes individuals' sense of ability, belief, and interest.

In Fig. 1 , learning self-efficacy includes learning behavior efficacy and learning ability efficacy, in which the learning behavior efficacy is determined by the sense of effort, the sense of environment, the sense of control, and the learning ability efficacy is determined by the sense of ability, sense of belief, sense of interest. “Sense of effort” is the understanding of whether one can study hard. Self-efficacy includes the estimation of self-effort and the ability, adaptability, and creativity shown in a particular situation. One with a strong sense of learning self-efficacy thinks they can study hard and focus on tasks 44 . “Sense of environment” refers to the individual’s feeling of their learning environment and grasp of the environment. The individual is the creator of the environment. A person’s feeling and grasp of the environment reflect the strength of his sense of efficacy to some extent. A person with a shared sense of learning self-efficacy is often dissatisfied with his environment, but he cannot do anything about it. He thinks the environment can only dominate him. A person with a high sense of learning self-efficacy will be more satisfied with his school and think that his teachers like him and are willing to study in school 44 . “Sense of control” is an individual’s sense of control over learning activities and learning behavior. It includes the arrangement of individual learning time, whether they can control themselves from external interference, and so on. A person with a strong sense of self-efficacy will feel that he is the master of action and can control the behavior and results of learning. Such a person actively participates in various learning activities. When he encounters difficulties in learning, he thinks he can find a way to solve them, is not easy to be disturbed by the outside world, and can arrange his own learning time. The opposite is the sense of losing control of learning behavior 44 . “Sense of ability” includes an individual’s perception of their natural abilities, expectations of learning outcomes, and perception of achieving their learning goals. A person with a high sense of learning self-efficacy will believe that he or she is brighter and more capable in all areas of learning; that he or she is more confident in learning in all subjects. In contrast, people with low learning self-efficacy have a sense of powerlessness. They are self-doubters who often feel overwhelmed by their learning and are less confident that they can achieve the appropriate learning goals 44 . “Sense of belief” is when an individual knows why he or she is doing something, knows where he or she is going to learn, and does not think before he or she even does it: What if I fail? These are meaningless, useless questions. A person with a high sense of learning self-efficacy is more robust, less afraid of difficulties, and more likely to reach their learning goals. A person with a shared sense of learning self-efficacy, on the other hand, is always going with the flow and is uncertain about the outcome of their learning, causing them to fall behind. “Sense of interest” is a person's tendency to recognize and study the psychological characteristics of acquiring specific knowledge. It is an internal force that can promote people's knowledge and learning. It refers to a person's positive cognitive tendency and emotional state of learning. A person with a high sense of self-efficacy in learning will continue to concentrate on studying and studying, thereby improving learning. However, one with low learning self-efficacy will have psychology such as not being proactive about learning, lacking passion for learning, and being impatient with learning. The elements of learning self-efficacy can be quantified and detailed in the following Fig. 1 .

Learning self-efficacy research structure in this paper.

Research participants

All the procedures were conducted in adherence to the guidelines and regulations set by the institution. Prior to initiating the study, informed consent was obtained in writing from the participants, and the Institutional Review Board for Behavioral and Human Movement Sciences at Nanning Normal University granted approval for all protocols.

Two parallel classes are pre-selected as experimental subjects in our study, one as the experimental group and one as the control group. Social media assisted classroom teaching to intervene in the experimental group, while the control group did not intervene. When selecting the sample, it is essential to consider, as far as possible, the shortcomings of not using randomization to select or assign the study participants, resulting in unequal experimental and control groups. When selecting the experimental subjects, classes with no significant differences in initial status and external conditions, i.e. groups with homogeneity, should be selected. Our study finally decided to select a total of 44 students from Class 2021 Design 1 and a total of 29 students from Class 2021 Design 2, a total of 74 students from Nanning Normal University, as the experimental subjects. The former served as the experimental group, and the latter served as the control group. 73 questionnaires are distributed to measure before the experiment, and 68 are returned, with a return rate of 93.15%. According to the statistics, there were 8 male students and 34 female students in the experimental group, making a total of 44 students (mirrors the demographic trends within the humanities and arts disciplines from which our sample was drawn); there are 10 male students and 16 female students in the control group, making a total of 26 students, making a total of 68 students in both groups. The sample of those who took the course were mainly sophomores, with a small number of first-year students and juniors, which may be related to the nature of the subject of this course and the course system offered by the university. From the analysis of students' majors, liberal arts students in the experimental group accounted for the majority, science students and art students accounted for a small part. In contrast, the control group had more art students, and liberal arts students and science students were small. In the daily self-study time, the experimental and control groups are 2–3 h. The demographic information of research participants is shown in Table 1 .

Research procedure

Firstly, the ADDIE model is used for the innovative design of the teaching method of the course. The number of students in the experimental group was 44, 8 male and 35 females; the number of students in the control group was 29, 10 male and 19 females. Secondly, the classes are targeted at students and applied. Thirdly, the course for both the experimental and control classes is a convenient and practice-oriented course, with the course title “Graphic Design and Production”, which focuses on learning the graphic design software Photoshop. The course uses different cases to explain in detail the process and techniques used to produce these cases using Photoshop, and incorporates practical experience as well as relevant knowledge in the process, striving to achieve precise and accurate operational steps; at the end of the class, the teacher assigns online assignments to be completed on social media, allowing students to post their edited software tutorials online so that students can master the software functions. The teacher assigns online assignments to be completed on social media at the end of the lesson, allowing students to post their editing software tutorials online so that they can master the software functions and production skills, inspire design inspiration, develop design ideas and improve their design skills, and improve students' learning self-efficacy through group collaboration and online interaction. Fourthly, pre-tests and post-tests are conducted in the experimental and control classes before the experiment. Fifthly, experimental data are collected, analyzed, and summarized.

We use a questionnaire survey to collect data. Self-efficacy is a person’s subjective judgment on whether one can successfully perform a particular achievement. American psychologist Albert Bandura first proposed it. To understand the improvement effect of students’ self-efficacy after the experimental intervention, this work questionnaire was referenced by the author from “Self-efficacy” “General Perceived Self Efficacy Scale” (General Perceived Self Efficacy Scale) German psychologist Schwarzer and Jerusalem (1995) and “Academic Self-Efficacy Questionnaire”, a well-known Chinese scholar Liang 45 . The questionnaire content is detailed in the supplementary information . A pre-survey of the questionnaire is conducted here. The second-year students of design majors collected 32 questionnaires, eliminated similar questions based on the data, and compiled them into a formal survey scale. The scale consists of 54 items, 4 questions about basic personal information, and 50 questions about learning self-efficacy. The Likert five-point scale is the questionnaire used in this study. The answers are divided into “completely inconsistent", “relatively inconsistent”, “unsure”, and “relatively consistent”. The five options of “Completely Meet” and “Compliant” will count as 1, 2, 3, 4, and 5 points, respectively. Divided into a sense of ability (Q5–Q14), a sense of effort (Q15–Q20), a sense of environment (Q21–Q28), a sense of control (Q29–Q36), a sense of Interest (Q37–Q45), a sense of belief (Q46–Q54). To demonstrate the scientific effectiveness of the experiment, and to further control the influence of confounding factors on the experimental intervention. This article thus sets up a control group as a reference. Through the pre-test and post-test in different periods, comparison of experimental data through pre-and post-tests to illustrate the effects of the intervention.

Reliability indicates the consistency of the results of a measurement scale (See Table 2 ). It consists of intrinsic and extrinsic reliability, of which intrinsic reliability is essential. Using an internal consistency reliability test scale, a Cronbach's alpha coefficient of reliability statistics greater than or equal to 0.9 indicates that the scale has good reliability, 0.8–0.9 indicates good reliability, 7–0.8 items are acceptable. Less than 0.7 means to discard some items in the scale 46 . This study conducted a reliability analysis on the effects of the related 6-dimensional pre-test survey to illustrate the reliability of the questionnaire.

From the Table 2 , the Cronbach alpha coefficients for the pre-test, sense of effort, sense of environment, sense of control, sense of interest, sense of belief, and the total questionnaire, were 0.919, 0.839, 0.848, 0.865, 0.852, 0.889 and 0.958 respectively. The post-test Cronbach alpha coefficients were 0.898, 0.888, 0.886, 0.889, 0.900, 0.893 and 0.970 respectively. The Cronbach alpha coefficients were all greater than 0.8, indicating a high degree of reliability of the measurement data.

The validity, also known as accuracy, reflects how close the measurement result is to the “true value”. Validity includes structure validity, content validity, convergent validity, and discriminative validity. Because the experiment is a small sample study, we cannot do any specific factorization. KMO and Bartlett sphericity test values are an important part of structural validity. Indicator, general validity evaluation (KMO value above 0.9, indicating very good validity; 0.8–0.9, indicating good validity; 0.7–0.8 validity is good; 0.6–0.7 validity is acceptable; 0.5–0.6 means poor validity; below 0.45 means that some items should be abandoned.

Table 3 shows that the KMO values of ability, effort, environment, control, interest, belief, and the total questionnaire are 0.911, 0.812, 0.778, 0.825, 0.779, 0.850, 0.613, and the KMO values of the post-test are respectively. The KMO values are 0.887, 0.775, 0.892, 0.868, 0.862, 0.883, 0.715. KMO values are basically above 0.8, and all are greater than 0.6. This result indicates that the validity is acceptable, the scale has a high degree of reasonableness, and the valid data.

In the graphic design and production (professional design course), we will learn the practical software with cases. After class, we will share knowledge on the self-media platform. We will give face-to-face computer instruction offline from 8:00 to 11:20 every Wednesday morning for 16 weeks. China's top online sharing platform (APP) is Tik Tok, micro-blog (Micro Blog) and Xiao hong shu. The experiment began on September 1, 2022, and conducted the pre-questionnaire survey simultaneously. At the end of the course, on January 6, 2023, the post questionnaire survey was conducted. A total of 74 questionnaires were distributed in this study, recovered 74 questionnaires. After excluding the invalid questionnaires with incomplete filling and wrong answers, 68 valid questionnaires were obtained, with an effective rate of 91%, meeting the test requirements. Then, use the social science analysis software SPSS Statistics 26 to analyze the data: (1) descriptive statistical analysis of the dimensions of learning self-efficacy; (2) Using correlation test to analyze the correlation between learning self-efficacy and the use of social media; (3) This study used a comparative analysis of group differences to detect the influence of learning self-efficacy on various dimensions of social media and design courses. For data processing and analysis, use the spss26 version software and frequency statistics to create statistics on the basic situation of the research object and the basic situation of the use of live broadcast. The reliability scale analysis (internal consistency test) and use Bartlett's sphericity test to illustrate the reliability and validity of the questionnaire and the individual differences between the control group and the experimental group in demographic variables (gender, grade, Major, self-study time per day) are explained by cross-analysis (chi-square test). In the experimental group and the control group, the pre-test, post-test, before-and-after test of the experimental group and the control group adopt independent sample T-test and paired sample T-test to illustrate the effect of the experimental intervention (The significance level of the test is 0.05 two-sided).

Results and discussion

Comparison of pre-test and post-test between groups.

To study whether the data of the experimental group and the control group are significantly different in the pre-test and post-test mean of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. The research for this situation uses an independent sample T-test and an independent sample. The test needs to meet some false parameters, such as normality requirements. Generally passing the normality test index requirements are relatively strict, so it can be relaxed to obey an approximately normal distribution. If there is serious skewness distribution, replace it with the nonparametric test. Variables are required to be continuous variables. The six variables in this study define continuous variables. The variable value information is independent of each other. Therefore, we use the independent sample T-test.

From the Table 4 , a pre-test found that there was no statistically significant difference between the experimental group and the control group at the 0.05 confidence level ( p > 0.05) for perceptions of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. Before the experiment, the two groups of test groups have the same quality in measuring self-efficacy. The experimental class and the control class are homogeneous groups. Table 5 shows the independent samples t-test for the post-test, used to compare the experimental and control groups on six items, including the sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief.

The experimental and control groups have statistically significant scores ( p < 0.05) for sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief, and the experimental and control groups have statistically significant scores (t = 3.177, p = 0.002) for a sense of competence. (t = 3.177, p = 0.002) at the 0.01 level, with the experimental group scoring significantly higher (3.91 ± 0.51) than the control group (3.43 ± 0.73). The experimental group and the control group showed significance for the perception of effort at the 0.01 confidence level (t = 2.911, p = 0.005), with the experimental group scoring significantly higher (3.88 ± 0.66) than the control group scoring significantly higher (3.31 ± 0.94). The experimental and control groups show significance at the 0.05 level (t = 2.451, p = 0.017) for the sense of environment, with the experimental group scoring significantly higher (3.95 ± 0.61) than the control group scoring significantly higher (3.58 ± 0.62). The experimental and control groups showed significance for sense of control at the 0.05 level of significance (t = 2.524, p = 0.014), and the score for the experimental group (3.76 ± 0.67) would be significantly higher than the score for the control group (3.31 ± 0.78). The experimental and control groups showed significance at the 0.01 level for sense of interest (t = 2.842, p = 0.006), and the experimental group's score (3.87 ± 0.61) would be significantly higher than the control group's score (3.39 ± 0.77). The experimental and control groups showed significance at the 0.01 level for the sense of belief (t = 3.377, p = 0.001), and the experimental group would have scored significantly higher (4.04 ± 0.52) than the control group (3.56 ± 0.65). Therefore, we can conclude that the experimental group's post-test significantly affects the mean scores of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. A social media-assisted course has a positive impact on students' self-efficacy.

Comparison of pre-test and post-test of each group

The paired-sample T-test is an extension of the single-sample T-test. The purpose is to explore whether the means of related (paired) groups are significantly different. There are four standard paired designs: (1) Before and after treatment of the same subject Data, (2) Data from two different parts of the same subject, (3) Test results of the same sample with two methods or instruments, 4. Two matched subjects receive two treatments, respectively. This study belongs to the first type, the 6 learning self-efficacy dimensions of the experimental group and the control group is measured before and after different periods.

Paired t-tests is used to analyze whether there is a significant improvement in the learning self-efficacy dimension in the experimental group after the experimental social media-assisted course intervention. In Table 6 , we can see that the six paired data groups showed significant differences ( p < 0.05) in the pre and post-tests of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. There is a level of significance of 0.01 (t = − 4.540, p = 0.000 < 0.05) before and after the sense of ability, the score after the sense of ability (3.91 ± 0.51), and the score before the Sense of ability (3.41 ± 0.55). The level of significance between the pre-test and post-test of sense of effort is 0.01 (t = − 4.002, p = 0.000). The score of the sense of effort post-test (3.88 ± 0.66) will be significantly higher than the average score of the sense of effort pre-test (3.31 ± 0.659). The significance level between the pre-test and post-test Sense of environment is 0.01 (t = − 3.897, p = 0.000). The average score for post- Sense of environment (3.95 ± 0.61) will be significantly higher than that of sense of environment—the average score of the previous test (3.47 ± 0.44). The average value of a post- sense of control (3.76 ± 0.67) will be significantly higher than the average of the front side of the Sense of control value (3.27 ± 0.52). The sense of interest pre-test and post-test showed a significance level of 0.01 (− 4.765, p = 0.000), and the average value of Sense of interest post-test was 3.87 ± 0.61. It would be significantly higher than the average value of the Sense of interest (3.25 ± 0.59), the significance between the pre-test and post-test of belief sensing is 0.01 level (t = − 3.939, p = 0.000). Thus, the average value of a post-sense of belief (4.04 ± 0.52) will be significantly higher than that of a pre-sense of belief Average value (3.58 ± 0.58). After the experimental group’s post-test, the scores for the Sense of ability, effort, environment, control, interest, and belief before the comparison experiment increased significantly. This result has a significant improvement effect. Table 7 shows that the control group did not show any differences in the pre and post-tests using paired t-tests on the dimensions of learning self-efficacy such as sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief ( p > 0.05). It shows no experimental intervention for the control group, and it does not produce a significant effect.

The purpose of this study aims to explore the impact of social media use on college students' learning self-efficacy, examine the changes in the elements of college students' learning self-efficacy before and after the experiment, and make an empirical study to enrich the theory. This study developed an innovative design for course teaching methods using the ADDIE model. The design process followed a series of model rules of analysis, design, development, implementation, and evaluation, as well as conducted a descriptive statistical analysis of the learning self-efficacy of design undergraduates. Using questionnaires and data analysis, the correlation between the various dimensions of learning self-efficacy is tested. We also examined the correlation between the two factors, and verifies whether there was a causal relationship between the two factors.

Based on prior research and the results of existing practice, a learning self-efficacy is developed for university students and tested its reliability and validity. The scale is used to pre-test the self-efficacy levels of the two subjects before the experiment, and a post-test of the self-efficacy of the two groups is conducted. By measuring and investigating the learning self-efficacy of the study participants before the experiment, this study determined that there was no significant difference between the experimental group and the control group in terms of sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. Before the experiment, the two test groups had homogeneity in measuring the dimensionality of learning self-efficacy. During the experiment, this study intervened in social media assignments for the experimental group. The experiment used learning methods such as network assignments, mutual aid communication, mutual evaluation of assignments, and group discussions. After the experiment, the data analysis showed an increase in learning self-efficacy in the experimental group compared to the pre-test. With the test time increased, the learning self-efficacy level of the control group decreased slightly. It shows that social media can promote learning self-efficacy to a certain extent. This conclusion is similar to Cao et al. 18 , who suggested that social media would improve educational outcomes.

We have examined the differences between the experimental and control group post-tests on six items, including the sense of ability, sense of effort, sense of environment, sense of control, sense of interest, and sense of belief. This result proves that a social media-assisted course has a positive impact on students' learning self-efficacy. Compared with the control group, students in the experimental group had a higher interest in their major. They showed that they liked to share their learning experiences and solve difficulties in their studies after class. They had higher motivation and self-directed learning ability after class than students in the control group. In terms of a sense of environment, students in the experimental group were more willing to share their learning with others, speak boldly, and participate in the environment than students in the control group.

The experimental results of this study showed that the experimental group showed significant improvement in the learning self-efficacy dimensions after the experimental intervention in the social media-assisted classroom, with significant increases in the sense of ability, sense of effort, sense of environment, sense of control, sense of interest and sense of belief compared to the pre-experimental scores. This result had a significant improvement effect. Evidence that a social media-assisted course has a positive impact on students' learning self-efficacy. Most of the students recognized the impact of social media on their learning self-efficacy, such as encouragement from peers, help from teachers, attention from online friends, and recognition of their achievements, so that they can gain a sense of achievement that they do not have in the classroom, which stimulates their positive perception of learning and is more conducive to the awakening of positive effects. This phenomenon is in line with Ajjan and Hartshorne 2 . They argue that social media provides many opportunities for learners to publish their work globally, which brings many benefits to teaching and learning. The publication of students' works online led to similar positive attitudes towards learning and improved grades and motivation. This study also found that students in the experimental group in the post-test controlled their behavior, became more interested in learning, became more purposeful, had more faith in their learning abilities, and believed that their efforts would be rewarded. This result is also in line with Ajjan and Hartshorne's (2008) indication that integrating Web 2.0 technologies into classroom learning environments can effectively increase students' satisfaction with the course and improve their learning and writing skills.

We only selected students from one university to conduct a survey, and the survey subjects were self-selected. Therefore, the external validity and generalizability of our study may be limited. Despite the limitations, we believe this study has important implications for researchers and educators. The use of social media is the focus of many studies that aim to assess the impact and potential of social media in learning and teaching environments. We hope that this study will help lay the groundwork for future research on the outcomes of social media utilization. In addition, future research should further examine university support in encouraging teachers to begin using social media and university classrooms in supporting social media (supplementary file 1 ).

The present study has provided preliminary evidence on the positive association between social media integration in education and increased learning self-efficacy among college students. However, several avenues for future research can be identified to extend our understanding of this relationship.

Firstly, replication studies with larger and more diverse samples are needed to validate our findings across different educational contexts and cultural backgrounds. This would enhance the generalizability of our results and provide a more robust foundation for the use of social media in teaching. Secondly, longitudinal investigations should be conducted to explore the sustained effects of social media use on learning self-efficacy. Such studies would offer insights into how the observed benefits evolve over time and whether they lead to improved academic performance or other relevant outcomes. Furthermore, future research should consider the exploration of potential moderators such as individual differences in students' learning styles, prior social media experience, and psychological factors that may influence the effectiveness of social media in education. Additionally, as social media platforms continue to evolve rapidly, it is crucial to assess the impact of emerging features and trends on learning self-efficacy. This includes an examination of advanced tools like virtual reality, augmented reality, and artificial intelligence that are increasingly being integrated into social media environments. Lastly, there is a need for research exploring the development and evaluation of instructional models that effectively combine traditional teaching methods with innovative uses of social media. This could guide educators in designing courses that maximize the benefits of social media while minimizing potential drawbacks.

In conclusion, the current study marks an important step in recognizing the potential of social media as an educational tool. Through continued research, we can further unpack the mechanisms by which social media can enhance learning self-efficacy and inform the development of effective educational strategies in the digital age.

Data availability

The data that support the findings of this study are available from the corresponding authors upon reasonable request. The data are not publicly available due to privacy or ethical restrictions.

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Acknowledgements

This work is supported by the 2023 Guangxi University Young and middle-aged Teachers' Basic Research Ability Enhancement Project—“Research on Innovative Communication Strategies and Effects of Zhuang Traditional Crafts from the Perspective of the Metaverse” (Grant Nos. 2023KY0385), and the special project on innovation and entrepreneurship education in universities under the “14th Five-Year Plan” for Guangxi Education Science in 2023, titled “One Core, Two Directions, Three Integrations - Strategy and Practical Research on Innovation and Entrepreneurship Education in Local Universities” (Grant Nos. 2023ZJY1955), and the 2023 Guangxi Higher Education Undergraduate Teaching Reform General Project (Category B) “Research on the Construction and Development of PBL Teaching Model in Advertising” (Grant Nos.2023JGB294), and the 2022 Guangxi Higher Education Undergraduate Teaching Reform Project (General Category A) “Exploration and Practical Research on Public Art Design Courses in Colleges and Universities under Great Aesthetic Education” (Grant Nos. 2022JGA251), and the 2023 Guangxi Higher Education Undergraduate Teaching Reform Project Key Project “Research and Practice on the Training of Interdisciplinary Composite Talents in Design Majors Based on the Concept of Specialization and Integration—Taking Guangxi Institute of Traditional Crafts as an Example” (Grant Nos. 2023JGZ147), and the2024 Nanning Normal University Undergraduate Teaching Reform Project “Research and Practice on the Application of “Guangxi Intangible Cultural Heritage” in Packaging Design Courses from the Ideological and Political Perspective of the Curriculum” (Grant Nos. 2024JGX048),and the 2023 Hubei Normal University Teacher Teaching Reform Research Project (Key Project) -Curriculum Development for Improving Pre-service Music Teachers' Teaching Design Capabilities from the Perspective of OBE (Grant Nos. 2023014), and the 2023 Guangxi Education Science “14th Five-Year Plan” special project: “Specialized Integration” Model and Practice of Art and Design Majors in Colleges and Universities in Ethnic Areas Based on the OBE Concept (Grant Nos. 2023ZJY1805), and the 2024 Guangxi University Young and Middle-aged Teachers’ Scientific Research Basic Ability Improvement Project “Research on the Integration Path of University Entrepreneurship and Intangible Inheritance - Taking Liu Sanjie IP as an Example” (Grant Nos. 2024KY0374), and the 2022 Research Project on the Theory and Practice of Ideological and Political Education for College Students in Guangxi - “Party Building + Red”: Practice and Research on the Innovation of Education Model in College Student Dormitories (Grant Nos. 2022SZ028), and the 2021 Guangxi University Young and Middle-aged Teachers’ Scientific Research Basic Ability Improvement Project - "Research on the Application of Ethnic Elements in the Visual Design of Live Broadcast Delivery of Guangxi Local Products" (Grant Nos. 2021KY0891).

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The contribution of H. to this paper primarily lies in research design and experimental execution. H. was responsible for the overall framework design of the paper, setting research objectives and methods, and actively participating in data collection and analysis during the experimentation process. Furthermore, H. was also responsible for conducting literature reviews and played a crucial role in the writing and editing phases of the paper. L.'s contribution to this paper primarily manifests in theoretical derivation and the discussion section. Additionally, author L. also proposed future research directions and recommendations in the discussion section, aiming to facilitate further research explorations. Y.'s contribution to this paper is mainly reflected in data analysis and result interpretation. Y. was responsible for statistically analyzing the experimental data and employing relevant analytical tools and techniques to interpret and elucidate the data results.

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Hu, J., Lai, Y. & Yi, X. Effectiveness of social media-assisted course on learning self-efficacy. Sci Rep 14 , 10112 (2024). https://doi.org/10.1038/s41598-024-60724-0

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Fall 2024 Semester

Undergraduate courses.

Composition courses that offer many sections (ENGL 101, 201, 277 and 379) are not listed on this schedule unless they are tailored to specific thematic content or particularly appropriate for specific programs and majors.

100-200 level

ENGL 151.S01: Introduction to English Studies

Tuesday and Thursday, 11 a.m.-12:15 p.m.

Sharon Smith

ENGL 151 serves as an introduction to both the English major and the discipline of English studies. In this class, you will develop the thinking, reading, writing and research practices that define both the major and the discipline. Much of the semester will be devoted to honing your literary analysis skills, and we will study and discuss texts from several different genres—poetry, short fiction, the novel, drama and film—as well as some literary criticism. As we do so, we will explore the language of the discipline, and you will learn a variety of key literary terms and concepts. In addition, you will develop your skills as both a writer and researcher within the discipline of English.

ENGL 201.ST1 Composition II: The Mind/Body Connection

In this section of English 201, students will use research and writing to learn more about problems that are important to them and articulate ways to address those problems. The course will focus specifically on issues related to the mind, the body and the relationship between them. The topics we will discuss during the course will include the correlation between social media and body image; the efficacy of sex education programs; the degree to which beliefs about race and gender influence school dress codes; and the unique mental and physical challenges faced by college students today. In this course, you will be learning about different approaches to argumentation, analyzing the arguments of others and constructing your own arguments. At the same time, you will be honing your skills as a researcher and developing your abilities as a persuasive and effective writer.

ENGL 201.S10 Composition II: Environmental Writing

Monday/Wednesday/Friday 1-1:50 p.m.

Gwen Horsley

English 201 will help students develop the ability to think critically and analytically and to write effectively for other university courses and careers. This course will provide opportunities to develop analytical skills that will help students become critical readers and effective writers. Specifically, in this class, students will:

Focus on the relationships between world environments, land, animals and humankind.
Read various essays by environmental, conservational and regional authors.
Produce student writings.

Students will improve their writing skills by reading essays and applying techniques they witness in others’ work and those learned in class. This class is also a course in logical and creative thought. Students will write about humankind’s place in the world and our influence on the land and animals, places that hold special meaning to them or have influenced their lives and stories of their own families and their places and passions in the world. Students will practice writing in an informed and persuasive manner, in language that engages and enlivens readers by using vivid verbs and avoiding unnecessary passives, nominalizations and expletive constructions.

Students will prepare writing assignments based on readings and discussions of essays included in "Literature and the Environment " and other sources. They may use "The St. Martin’s Handbook," as well as other sources, to review grammar, punctuation, mechanics and usage as needed.

ENGL 201.13 Composition II: Writing the Environment

Tuesday and Thursday 9:30-10:45 a.m.

Paul Baggett

For generations, environmentalists have relied on the power of prose to change the minds and habits of their contemporaries. In the wake of fires, floods, storms and droughts, environmental writing has gained a new sense of urgency, with authors joining activists in their efforts to educate the public about the grim realities of climate change. But do they make a difference? Have reports of present and future disasters so saturated our airwaves that we no longer hear them? How do writers make us care about the planet amidst all the noise? In this course, students will examine the various rhetorical strategies employed by some of today’s leading environmental writers and filmmakers. And while analyzing their different arguments, students also will strengthen their own strategies of argumentation as they research and develop essays that explore a range of environmental concerns.

ENGL 201 Composition II: Food Writing

S17 Tuesday and Thursday 12:30-1:45 p.m.

S18 Tuesday and Thursday 2-3:15 p.m.

Jodi Andrews

In this composition class, students will critically analyze essays about food, food systems and environments, food cultures, the intersections of personal choice, market forces and policy and the values underneath these forces. Students will learn to better read like writers, noting authors’ purpose, audience organizational moves, sentence-level punctuation and diction. We will read a variety of essays including research-intensive arguments and personal narratives which intersect with one of our most primal needs as humans: food consumption. Students will rhetorically analyze texts, conduct advanced research, reflect on the writing process and write essays utilizing intentional rhetorical strategies. Through doing this work, students will practice the writing moves valued in every discipline: argument, evidence, concision, engaging prose and the essential research skills for the 21st century.

ENGL 221.S01 British Literature I

Michael S. Nagy

English 221 is a survey of early British literature from its inception in the Old English period with works such as "Beowulf" and the “Battle of Maldon,” through the Middle Ages and the incomparable writings of Geoffrey Chaucer and the Gawain - poet, to the Renaissance and beyond. Students will explore the historical and cultural contexts in which all assigned reading materials were written, and they will bring that information to bear on class discussion. Likely themes that this class will cover include heroism, humor, honor, religion, heresy and moral relativity. Students will write one research paper in this class and sit for two formal exams: a midterm covering everything up to that point in the semester, and a comprehensive final. Probable texts include the following:

The Norton Anthology of English Literature: The Middle Ages. Ed. Alfred David, M. H. Abrams, and Stephen Greenblatt. 9th ed. New York: W. W. Norton & Company, 2012.
The Norton Anthology of English Literature: The Sixteenth Century and Early Seventeenth Century. Ed. George M. Logan, Stephen Greenblatt, Barbara K Lewalski, and M. H. Abrams. 9th ed. New York: W. W. Norton & Company, 2012.
The Norton Anthology of English Literature: The Restoration and the Eighteenth Century. Ed. George M. Logan, Stephen Greenblatt, Barbara K Lewalski, and M. H. Abrams. 9th ed. New York: W. W. Norton & Company, 2012.
Gibaldi, Joseph. The MLA Handbook for Writers of Research Papers. 6th ed. New York: The Modern Language Association of America, 2003.
Any Standard College Dictionary.

ENGL 240.S01 Juvenile Literature Elementary-5th Grade

Monday, Wednesday and Friday noon-12:50 p.m.

April Myrick

A survey of the history of literature written for children and adolescents, and a consideration of the various types of juvenile literature. Text selection will focus on the themes of imagination and breaking boundaries.

ENGL 240.ST1 Juvenile Literature Elementary-5th Grade

Randi Anderson

In English 240 students will develop the skills to interpret and evaluate various genres of literature for juvenile readers. This particular section will focus on various works of literature at approximately the K-5 grade level. We will read a large range of works that fall into this category, as well as information on the history, development and genre of juvenile literature.

Readings for this course include classical works such as "Hatchet," "Little Women", "The Lion, the Witch and the Wardrobe" and "Brown Girl Dreaming," as well as newer works like "Storm in the Barn," "Anne Frank’s Diary: A Graphic Adaptation," "Lumberjanes," and a variety of picture books. These readings will be paired with chapters from "Reading Children’s Literature: A Critical Introduction " to help develop understanding of various genres, themes and concepts that are both related to juvenile literature and also present in our readings.

In addition to exposing students to various genres of writing (poetry, historical fiction, non-fiction, fantasy, picture books, graphic novels, etc.) this course will also allow students to engage in a discussion of larger themes present in these works such as censorship, race and gender. Students’ understanding of these works and concepts will be developed through readings, research, discussion posts, exams and writing assignments designed to get students to practice analyzing poetry, picture books, informational books and transitional/easy readers.

ENGL 241.S01: American Literature I

Tuesday and Thursday 12:30-1:45 p.m.

This course provides a broad, historical survey of American literature from the early colonial period to the Civil War. Ranging across historical periods and literary genres—including early accounts of contact and discovery, narratives of captivity and slavery, poetry of revolution, essays on gender equality and stories of industrial exploitation—this class examines how subjects such as colonialism, nationhood, religion, slavery, westward expansion, race, gender and democracy continue to influence how Americans see themselves and their society.

Required Texts

The Norton Anthology of American Literature: Package 1, Volumes A and B Beginnings to 1865, Ninth Edition. (ISBN 978-0-393-26454-8)

ENGL 283.S01 Introduction to Creative Writing

Steven Wingate

Students will explore the various forms of creative writing (fiction, nonfiction and poetry) not one at a time in a survey format—as if there were decisive walls of separation between then—but as intensely related genres that share much of their creative DNA. Through close reading and work on personal texts, students will address the decisions that writers in any genre must face on voice, rhetorical position, relationship to audience, etc. Students will produce and revise portfolios of original creative work developed from prompts and research. This course fulfills the same SGR #2 requirements ENGL 201; note that the course will involve a research project. Successful completion of ENGL 101 (including by test or dual credit) is a prerequisite.

ENGL 283.S02 Introduction to Creative Writing

Jodilyn Andrews

This course introduces students to the craft of writing, with readings and practice in at least two genres (including fiction, poetry and drama).

ENGL 283.ST1 Introduction to Creative Writing

Amber Jensen, M.A., M.F.A.

This course explores creative writing as a way of encountering the world, research as a component of the creative writing process, elements of craft and their rhetorical effect and drafting, workshop and revision as integral parts of writing polished literary creative work. Student writers will engage in the research practices that inform the writing of literature and in the composing strategies and writing process writers use to create literary texts. Through their reading and writing of fiction, poetry and creative nonfiction, students will learn about craft elements, find examples of those craft elements in published works and apply these elements in their own creative work, developed through weekly writing activities, small group and large group workshop and conferences with the instructor. Work will be submitted, along with a learning reflection and revision plan in each genre and will then be revised and submitted as a final portfolio at the end of the semester to demonstrate continued growth in the creation of polished literary writing.

300-400 level

ENGL 424.S01 Language Arts Methods grades 7-12

Tuesday 6-8:50 p.m.

Danielle Harms

Techniques, materials and resources for teaching English language and literature to middle and secondary school students. Required of students in the English education option.

AIS/ENGL 447.S01: American Indian Literature of the Present

Thursdays 3-6 p.m.

This course introduces students to contemporary works by authors from various Indigenous nations. Students examine these works to enhance their historical understanding of Indigenous peoples, discover the variety of literary forms used by those who identify as Indigenous writers, and consider the cultural and political significance of these varieties of expression. Topics and questions to be explored include:

Genre: What makes Indigenous literature indigenous?
Political and Cultural Sovereignty: Why have an emphasis on tribal specificity and calls for “literary separatism” emerged in recent decades, and what are some of the critical conversations surrounding such particularized perspectives?
Gender and Sexuality: What are the intersecting concerns of Indigenous Studies and Women, Gender and Sexuality Studies, and how might these research fields inform one another?
Trans-Indigeneity: What might we learn by comparing works across different Indigenous traditions, and what challenges do such comparisons present?
Aesthetics: How do Indigenous writers understand the dynamics between tradition and creativity?
Visual Forms: What questions or concerns do visual representations (television and film) by or about Indigenous peoples present?

Possible Texts

Akiwenzie-Damm, Kateri and Josie Douglas (eds), Skins: Contemporary Indigenous Writing. IAD Press, 2000. (978-1864650327)
Erdrich, Louise, The Sentence. Harper, 2021 (978-0062671127)
Harjo, Joy, Poet Warrior: A Memoir. Norton, 2021 (978-0393248524)
Harjo, Sterlin and Taika Waititi, Reservation Dogs (selected episodes)
Talty, Morgan. Night of the Living Rez, 2022, Tin House (978-1953534187)
Wall Kimmerer, Robin. Braiding Sweet Grass, Milkweed Editions (978-1571313560)
Wilson, Diane. The Seed Keeper: A Novel. Milkweed Editions (978-1571311375)
Critical essays by Alexie, Allen, Cohen, Cox, King, Kroeber, Ortiz, Piatote, Ross and Sexton, Smith, Taylor, Teuton, Treuer, Vizenor, and Womack.

ENGL 472.S01: Film Criticism

Tuesdays 2-4:50 p.m.

Jason McEntee

Do you have an appreciation for, and enjoy watching, movies? Do you want to study movies in a genre-oriented format (such as those we typically call the Western, the screwball comedy, the science fiction or the crime/gangster, to name a few)? Do you want to explore the different critical approaches for talking and writing about movies (such as auteur, feminist, genre or reception)?

In this class, you will examine movies through viewing and defining different genres while, at the same time, studying and utilizing different styles of film criticism. You will share your discoveries in both class discussions and short writings. The final project will be a formal written piece of film criticism based on our work throughout the semester. The course satisfies requirements and electives for all English majors and minors, including both the Film Studies and Professional Writing minors. (Note: Viewing of movies outside of class required and may require rental and/or streaming service fees.)

ENGL 476.ST1: Fiction

In this workshop-based creative writing course, students will develop original fiction based on strong attention to the fundamentals of literary storytelling: full-bodied characters, robust story lines, palpable environments and unique voices. We will pay particular attention to process awareness, to the integrity of the sentence, and to authors' commitments to their characters and the places in which their stories unfold. Some workshop experience is helpful, as student peer critique will be an important element of the class.

ENGL 479.01 Capstone: The Gothic

Wednesday 3-5:50 p.m.

With the publication of Horace Walpole’s "The Castle of Otranto " in 1764, the Gothic officially came into being. Dark tales of physical violence and psychological terror, the Gothic incorporates elements such as distressed heroes and heroines pursued by tyrannical villains; gloomy estates with dark corridors, secret passageways and mysterious chambers; haunting dreams, troubling prophecies and disturbing premonitions; abduction, imprisonment and murder; and a varied assortment of corpses, apparitions and “monsters.” In this course, we will trace the development of Gothic literature—and some film—from the eighteenth-century to the present time. As we do so, we will consider how the Gothic engages philosophical beliefs about the beautiful and sublime; shapes psychological understandings of human beings’ encounters with horror, terror, the fantastic and the uncanny; and intervenes in the social and historical contexts in which it was written. We’ll consider, for example, how the Gothic undermines ideals related to domesticity and marriage through representations of domestic abuse, toxicity and gaslighting. In addition, we’ll discuss Gothic texts that center the injustices of slavery and racism. As many Gothic texts suggest, the true horrors of human existence often have less to do with inexplicable supernatural phenomena than with the realities of the world in which we live.

ENGL 485.S01: Undergraduate Writing Center Learning Assistants

Flexible Scheduling

Nathan Serfling

Since their beginnings in the 1920s and 30s, writing centers have come to serve numerous functions: as hubs for writing across the curriculum initiatives, sites to develop and deliver workshops and resource centers for faculty as well as students, among other functions. But the primary function of writing centers has necessarily and rightfully remained the tutoring of student writers. This course will immerse you in that function in two parts. During the first four weeks, you will explore writing center praxis—that is, the dialogic interplay of theory and practice related to writing center work. This part of the course will orient you to writing center history, key theoretical tenets and practical aspects of writing center tutoring. Once we have developed and practiced this foundation, you will begin work in the writing center as a tutor, responsible for assisting a wide variety of student clients with numerous writing tasks. Through this work, you will learn to actively engage with student clients in the revision of a text, respond to different student needs and abilities, work with a variety of writing tasks and rhetorical situations, and develop a richer sense of writing as a complex and negotiated social process.

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Engl 572.s01: film criticism, engl 576.st1 fiction.

In this workshop-based creative writing course, students will develop original fiction based on strong attention to the fundamentals of literary storytelling: full-bodied characters, robust story lines, palpable environments and unique voices. We will pay particular attention to process awareness, to the integrity of the sentence and to authors' commitments to their characters and the places in which their stories unfold. Some workshop experience is helpful, as student peer critique will be an important element of the class.

ENGL 605.S01 Seminar in Teaching Composition

Thursdays 1-3:50 p.m.

This course will provide you with a foundation in the pedagogies and theories (and their attendant histories) of writing instruction, a foundation that will prepare you to teach your own writing courses at SDSU and elsewhere. As you will discover through our course, though, writing instruction does not come with any prescribed set of “best” practices. Rather, writing pedagogies stem from and continue to evolve because of various and largely unsettled conversations about what constitutes effective writing and effective writing instruction. Part of becoming a practicing writing instructor, then, is studying these conversations to develop a sense of what “good writing” and “effective writing instruction” might mean for you in our particular program and how you might adapt that understanding to different programs and contexts.

As we read about, discuss and research writing instruction, we will address a variety of practical and theoretical topics. The practical focus will allow us to attend to topics relevant to your immediate classroom practices: designing a curriculum and various types of assignments, delivering the course content and assessing student work, among others. Our theoretical topics will begin to reveal the underpinnings of these various practical matters, including their historical, rhetorical, social and political contexts. In other words, we will investigate the praxis—the dialogic interaction of practice and theory—of writing pedagogy. As a result, this course aims to prepare you not only as a writing teacher but also as a nascent writing studies/writing pedagogy scholar.

At the end of this course, you should be able to engage effectively in the classroom practices described above and participate in academic conversations about writing pedagogy, both orally and in writing. Assessment of these outcomes will be based primarily on the various writing assignments you submit and to a smaller degree on your participation in class discussions and activities.

ENGL 726.S01: The New Woman, 1880–1900s

Thursdays 3–5:50 p.m.

Katherine Malone

This course explores the rise of the New Woman at the end of the nineteenth century. The label New Woman referred to independent women who rebelled against social conventions. Often depicted riding bicycles, smoking cigarettes and wearing masculine clothing, these early feminists challenged gender roles and sought broader opportunities for women’s employment and self-determination. We will read provocative fiction and nonfiction by New Women writers and their critics, including authors such as Sarah Grand, Mona Caird, George Egerton, Amy Levy, Ella Hepworth Dixon, Grant Allen and George Gissing. We will analyze these exciting texts through a range of critical lenses and within the historical context of imperialism, scientific and technological innovation, the growth of the periodical press and discourse about race, class and gender. In addition to writing an argumentative seminar paper, students will complete short research assignments and lead discussion.

ENGL 792.ST1 Women in War: Female Authors and Characters in Contemporary War Lit

In this course, we will explore the voices of female authors and characters in contemporary literature of war. Drawing from various literary theories, our readings and discussion will explore the contributions of these voices to the evolving literature of war through archetypal and feminist criticism. We will read a variety of short works (both theoretical and creative) and complete works such as (selections subject to change): "Eyes Right" by Tracy Crow, "Plenty of Time When We Get Home" by Kayla Williams, "You Know When the Men are Gone" by Siobhan Fallon, "Still, Come Home" by Katie Schultz and "The Fine Art of Camouflage" by Lauren Johnson.

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v.44(3); 2019 Aug

Statistical notes for clinical researchers: the independent samples t -test

Hae-young kim.

Department of Health Policy and Management, College of Health Science, and Department of Public Health Science, Graduate School, Korea University, Seoul, Korea.

The t -test is frequently used in comparing 2 group means. The compared groups may be independent to each other such as men and women. Otherwise, compared data are correlated in a case such as comparison of blood pressure levels from the same person before and after medication ( Figure 1 ). In this section we will focus on independent t -test only. There are 2 kinds of independent t -test depending on whether 2 group variances can be assumed equal or not. The t -test is based on the inference using t -distribution.

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T -DISTRIBUTION

The t -distribution was invented in 1908 by William Sealy Gosset, who was working for the Guinness brewery in Dublin, Ireland. As the Guinness brewery did not permit their employee's publishing the research results related to their work, Gosset published his findings by a pseudonym, “Student.” Therefore, the distribution he suggested was called as Student's t -distribution. The t -distribution is a distribution similar to the standard normal distribution, z -distribution, but has lower peak and higher tail compared to it ( Figure 2 ).

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According to the sampling theory, when samples are drawn from a normal-distributed population, the distribution of sample means is expected to be a normal distribution. When we know the variance of population, σ 2 , we can define the distribution of sample means as a normal distribution and adopt z -distribution in statistical inference. However, in reality, we generally never know σ 2 , we use sample variance, s 2 , instead. Although the s 2 is the best estimator for σ 2 , the degree of accuracy of s 2 depends on the sample size. When the sample size is large enough ( e.g. , n = 300), we expect that the sample variance would be very similar to the population variance. However, when sample size is small, such as n = 10, we could guess that the accuracy of sample variance may be not that high. The t -distribution reflects this difference of uncertainty according to sample size. Therefore the shape of t -distribution changes by the degree of freedom (df), which is sample size minus one (n − 1) when one sample mean is tested.

The t -distribution appears to be a family of distribution of which shape varies according to its df ( Figure 2 ). When df is smaller, the t -distribution has lower peak and higher tail compared to those with higher df. The shape of t -distribution approaches to z -distribution as df increases. When df gets large enough, e.g. , n = 300, t -distribution is almost identical with z -distribution. For the inferences of means using small samples, it is necessary to apply t -distribution, while similar inference can be obtain by either t -distribution or z -distribution for a case with a large sample. For inference of 2 means, we generally use t -test based on t -distribution regardless of the sizes of sample because it is always safe, not only for a test with small df but also for that with large df.

INDEPENDENT SAMPLES T -TEST

To adopt z - or t -distribution for inference using small samples, a basic assumption is that the distribution of population is not significantly different from normal distribution. As seen in Appendix 1 , the normality assumption needs to be tested in advance. If normality assumption cannot be met and we have a small sample ( n < 25), then we are not permitted to use ‘parametric’ t -test. Instead, a non-parametric analysis such as Mann-Whitney U test should be selected.

For comparison of 2 independent group means, we can use a z -statistic to test the hypothesis of equal population means only if we know the population variances of 2 groups, σ 1 2 and σ 2 2 , as follows;

where X ̄ 1 and X ̄ 2 , σ 1 2 and σ 2 2 , and n 1 and n 2 are sample means, population variances, and the sizes of 2 groups.

Again, as we never know the population variances, we need to use sample variances as their estimates. There are 2 methods whether 2 population variances could be assumed equal or not. Under assumption of equal variances, the t -test devised by Gosset in 1908, Student's t -test, can be applied. The other version is Welch's t -test introduced in 1947, for the cases where the assumption of equal variances cannot be accepted because quite a big difference is observed between 2 sample variances.

1. Student's t -test

In Student's t -test, the population variances are assumed equal. Therefore, we need only one common variance estimate for 2 groups. The common variance estimate is calculated as a pooled variance, a weighted average of 2 sample variances as follows;

where s 1 2 and s 2 2 are sample variances.

The resulting t -test statistic is a form that both the population variances, σ 1 2 and σ 1 2 , are exchanged with a common variance estimate, s p 2 . The df is given as n 1 + n 2 − 2 for the t -test statistic.

In Appendix 1 , ‘(E-1) Leven's test for equality of variances’ shows that the null hypothesis of equal variances was accepted by the high p value, 0.334 (under heading of Sig.). In ‘(E-2) t -test for equality of means t -values’, the upper line shows the result of Student's t -test. The t -value and df are shown −3.357 and 18. We can get the same figures using the formulas Eq. 2 and Eq. 3, and descriptive statistics in Table 1 , as follows.

Group	No.	Mean	Standard deviation	value
1	10	10.28	0.5978	0.004
2	10	11.08	0.4590

The result of calculation is a little different from that by SPSS (IBM Corp., Armonk, NY, USA) of Appendix 1 , maybe because of rounding errors.

2. Welch's t -test

Actually there are a lot of cases where the equal variance cannot be assumed. Even if it is unlikely to assume equal variances, we still compare 2 independent group means by performing the Welch's t -test. Welch's t -test is more reliable when the 2 samples have unequal variances and/or unequal sample sizes. We need to maintain the assumption of normality.

Because the population variances are not equal, we have to estimate them separately by 2 sample variances, s 1 2 and s 2 2 . As the result, the form of t -test statistic is given as follows;

where ν is Satterthwaite degrees of freedom.

In Appendix 1 , ‘(E-1) Leven's test for equality of variances’ shows an equal variance can be successfully assumed ( p = 0.334). Therefore, the Welch's t -test is inappropriate for this data. Only for the purpose of exercise, we can try to interpret the results of Welch's t -test shown in the lower line in ‘(E-2) t -test for equality of means t -values’. The t -value and df are shown as −3.357 and 16.875.

We've confirmed nearly same results by calculation using the formula and by SPSS software.

The t -test is one of frequently used analysis methods for comparing 2 group means. However, sometimes we forget the underlying assumptions such as normality assumption or miss the meaning of equal variance assumption. Especially when we have a small sample, we need to check normality assumption first and make a decision between the parametric t -test and the nonparametric Mann-Whitney U test. Also, we need to assess the assumption of equal variances and select either Student's t -test or Welch's t -test.

Procedure of t -test analysis using IBM SPSS

The procedure of t -test analysis using IBM SPSS Statistics for Windows Version 23.0 (IBM Corp., Armonk, NY, USA) is as follows.

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The paired t test and beyond: Recommendations for testing the central
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In clinical research, comparisons of the results from experimental and control groups are often encountered. The two-sample t-test (also called independent samples t-test) and the paired t-test are probably the most widely used tests in statistics for the comparison of mean values between two samples.However, confusion exists with regard to the use of the two test methods, resulting in their ...
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The hypothesis testing using paired sample t-test was used for this study. The outcomes are expected to get higher mean value for post-test than pre-test. 1.1. Research Objective The aim of this study is to investigate the mean value for pre-test and post-test. 1.2.
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Paired T test. Paired t tests are can be categorized as a type of t test for a single sample because they test the difference between two paired results. If there is no difference between the two treatments, the difference in the results would be close to zero; hence, the difference in the sample means used for a paired t test would be 0.
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Abstract and Figures. The paired sample t-test is widely used to compare the difference between two population means in the matched sample design. The basic underlying assumption of this test is ...
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A paired-samples t -test compares the mean of two matched groups of people or cases, or compares the mean of a single group, examined at two different points in time. If the same group is tested again, on the same measure, the t-test is called a repeated measures t -test. Download to read the full chapter text.
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Student's t test (t test), analysis of variance (ANOVA), and analysis of covariance (ANCOVA) are statistical methods used in the testing of hypothesis for comparison of means between the groups.The Student's t test is used to compare the means between two groups, whereas ANOVA is used to compare the means among three or more groups. In ANOVA, first gets a common P value.
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As one of the most commonly used statistical methods in medical research papers, t-test can be divided into one-sample t-test and two-sample t-test [3, 4]. Thus, it is inappropriate to compare the means among multiple groups (more than three). ... Using the origin data and paired samples t-test, i.e., selecting "Analyze Compare Means Paired ...
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th several options.Select Paired Samples t Test from the drop-down list.You will see the list of all variables in the box on the left of the screen, an arrow in the middle. and a box on the right with the headings of "Pair 1" and "Pair 2." Click on the variable pretest from the box on the.
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ith df = n-1.3.3 Diferences between the two-sample t-test and paired t-testAs d. scussed above, these two tests should be used for different data structures. Two-sample t-test is used when the data of two samples are statistically independen. , while the paired t-test is used when data is in the f.
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In this paper we discuss the significance of t-test in small sample of statistics to analyze the data. Here we approach many application of t-test in statistics and research. This paper is aimed at introducing hypothesis testing, focusing on the paired t-test. It will explain how the paired t-test is applied to statistical analyses.
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The alter native non p arametric test for paired t test is Wilcoxon Si gned Rank T est. These derived eq uations are based on Ambrosius (2007), Bluman (2009) and petrie and Sabin (2005)
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Tuesday and Thursday, 11 a.m.-12:15 p.m. Sharon Smith. ENGL 151 serves as an introduction to both the English major and the discipline of English studies. In this class, you will develop the thinking, reading, writing and research practices that define both the major and the discipline. Much of the semester will be devoted to honing your ...
Statistical notes for clinical researchers: the independent samples t-test
The t-test is frequently used in comparing 2 group means.The compared groups may be independent to each other such as men and women. Otherwise, compared data are correlated in a case such as comparison of blood pressure levels from the same person before and after medication (Figure 1).In this section we will focus on independent t-test only.There are 2 kinds of independent t-test depending on ...
(PDF) T test as a parametric statistic
An independent-group t test can be carried out for a. comparison of means between two independen t groups, with a paired t test fo r paired data. As the t test is a parametric. test, samples ...

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Analysis of t- test misuses and SPSS operations in medical research papers

Misuse of t- test because data do not obey normal distribution

[Correction]

Misuse of independent sample t- test because of paired samples

Misuse of independent sample t- test because there are more than three levels in independent samples

Misuse of independent sample t- test because of factorial design data

Misuse of independent sample t- test because of repeated measurement design

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