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Academic Achievements of University Students in Blended and Online E-Courses in Mathematical Methods in Psychology

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posted on 01.06.2021, 12:19 authored by Marina SorokovaMarina Sorokova, Maria Odintsova, Nataly RadchikovaNataly Radchikova
The article presents a comparative analysis of the academic achievements of students (N = 809) who completed e-courses in mathematical methods in psychology by means of blended learning (N = 404) and online learning (N = 405). The research was carried out at the Moscow State University of Psychology and Education in 2019-2020

Funding

The reported study was funded by the Moscow State University of Psychology and Education (MSUPE) in the framework of the research project "Digital Technologies in Higher Education: Development of Technology for Individualizing Education Using E-Courses"

History

Research questions / Hypotheses

RQ1. Do the academic achievements of students enrolled in e-courses in mathematical methods in psychology differ between blended and online learning formats? RQ2. How do the academic achievements of graduate and undergraduate students compare with each other? RQ3. Is there an effect of learning in e-courses in blended and online formats compared to the initial level of competence?

Participants / Sample description

The sample consists of N = 809 students of the MSUPE who completed e-courses in mathematical methods in psychology: N = 418 graduate students (male 14.6%, female 85.4%) and N = 391 undergraduate ones (male 16.1%, female 83.9%). There are no differences in sex (p = 0.55). N = 404 students (49.9%) studied in blended learning (BL) format (male 18.3%, female 81.7%), N = 405 (50.1%) - in online format (male 12.6%, female 87.6%), in the 1-st group the men’s share is slightly predominant (p = 0.02). Share of BL-students (54.0% vs 46.0%) and online education ones (49.4% vs 50.6%) in graduate and undergraduate groups do not differ (p = 0.19). Contextual parameters “age” and “employment” were collected using an anonymous feedback questionnaire to analyze the learning experience, which students filled out after completing e-courses: N = 344 BL-group students and N = 396 online education ones (N = 740 in total). For this truncated sample, no age differences were found (p = 0.116)

Apparatus and materials

E-courses are aimed at developing competencies and basic skills for quantitative data analysis in research and scientific and practical activities in SPSS and consist of 3 identical modules regarding basic methods of mathematical statistics, and the master's course also has the 4th additional module “Multidimensional Statistical Methods”. We compared academic outcomes after completing 3 mandatory modules. Educational outcomes were evaluated using 5 tests inside the e-course, i.e. pre-test, 3 learning tests inside the modules, post-test, and an individual case-task including 6 cases. Cases in different case-tasks varied in data sets. Students performed case-tasks in SPSS. Students who completed the e-course filled out an anonymous feedback survey. After 1 – 1,5 months, students participated at testing again at the MSUPE Department for Monitoring the Quality of Professional Education (DMQPE) to evaluate knowledge retention. The pretest, the final test and the test at DMQPE are the same

Experimental design

Quasi-experimental study was carried out at MSUPE in the 2019 (blended learning - BL) and 2020 (online learning OL) according to the "flipped classroom (FC)" model. Students from 45 academic groups of 6 faculties completed one of the 3 e-courses in mathematical methods in psychology. LMS Moodle platform was used. FC-model implies transition from teacher-centered to student-centered learning management. The video-lectures were offered for independent pre-class preparation along with presentations, videos demonstrating case solving in SPSS, data and output files, hyperlinks to textbooks in MSUPE e-library and journal articles at PsyJournals.ru portal. At face-to-face or online sessions, students answered questions, participated in group discussions, solved in SPSS authentic cases, learned to choose methods, analyze data and interpret the results. In 2020, interactive tasks were added to all e-courses in order to make the learning process more individualized

Data collection procedure

Academic achievements were evaluated using 5 tests inside the e-course, i.e. pre-test, 3 learning tests inside the modules, post-test, and an individual case-task including 6 cases. The results within the e-courses were recorded automatically by means of LMS Moodle. Cases in different case-tasks varied in data sets. Students performed case-tasks in SPSS, we evaluated and commented on them. Students who completed the e-course filled out an anonymous feedback questionnaire. Knowledge retention was tested after 1 – 1,5 months at the MSUPE Department for Monitoring the Quality of Professional Education (DMQPE). The psychometric characteristics of the academic achievement test in the field of empirical data quantitative analysis can be considered satisfactory

Statistical methods

1. Differences between the final test indicators and the final e-course score were checked using two-way analysis of covariance (ANCOVA) 2x2, where the pre-test indicators were considered as the covariates. The covariate was used to remove extraneous variation from the dependent variable and to identify the effects of factors. The factors were the format of training (blended vs online) and higher education level (graduate vs undergraduate). 2. The dynamics of changes in academic achievements at the pre-test, post-test, and 1-1.5 months after e-course completing was examined using a two-factor analysis of variance (ANOVA) for a mixed scheme. 3. Data analysis was performed in the SPSS V. 23

Results

(1) Students in OL achieved higher results compared with the BL group in the pre-test, post-test, and final course grades, however, the difference in the means for all 3 indicators is minimal. In a smaller sample, no significant differences in post-test and final course grades were found. (2) The academic achievements of graduate and undergraduate students after e-course completion are on the verge of statistical significance. (3) The dynamics of changes in the BL and OL groups showed a very pronounced growth in the post-test indicators compared to the pre-test, and then a less pronounced decline in external test results after 1 - 1.5 months, which remain significantly higher than the pre-test ones. (4) The decline in the OL group is very minor, i.e., the dynamics is better. The latter result requires further verification under more equalized external testing conditions. (5) The effect of learning in e-courses in both blended and online formats has been statistically proven

Publication reference

Sorokova M.G., Odintsova M.A., Radchikova N. Students Educational Results in Blended and Online E-Courses. Modelirovanie i analiz dannikh = Modelling and Data Analysis, 2021. Vol. 11, no. 1, pp. 61–77. doi:10.17759/mda.2021110105. (In Russ., аbstr. in Engl.)

Affiliation

Marina G. Sorokova, Doctor in Education, PhD in Physics and Mathematics, Head of Scientific and Practical Center for Comprehensive Support of Psychological Research «PsyDATA», Professor, Chair of Applied Mathematics, Faculty of Information Technology, Moscow State University of Psychology and Education, Moscow, Russia Maria A. Odintsova, PhD in Psychology, Professor, Chair of Psychology and Pedagogy of Distance Learning, Head of the Chair of Psychology and Pedagogy of Distance Learning, Faculty of Distance Learning, Moscow State University of Psychology and Education, Moscow Nataly P. Radchikova, PhD in Psychology, Associate Professor of the Department of Developmental Psychology, Faculty of Pre-School Pedagogy and Psychology, Moscow Pedagogical State University; Leading Researcher of Scientific and Practical Center for Comprehensive Support of Psychological Research «PsyDATA», Moscow State University of Psychology and Education, Moscow