OPEN ACCESS JOURNALS
|JournalsTopicsAuthorsEditor's Choice||For AuthorsAbout PsyJournals.ruContact Us|
Efficiency of learning and academic motivation of students in conditions of online interaction with the teacher (on the example of video-lecture) 428
The objective is to study the relationship between students’ online lecture assessment, the quality of learning and academic motivation. Background. Digitalization of education actualizes the problem of the online-learning effectiveness, which might decrease through reducing the social presence of the teacher and students in the educational situation. Due to these conditions, students’ motivation might mean a great deal. Study design. Students evaluated the classroom lecture and its video using the parameters “interest”, “content” and “usefulness”, and then the scores and the volume of the reproduced educational material were compared. Participants. The study involved 112 students (19.55±0.66 years, 83.9% of women). Measurements. Students evaluated lectures on the proposed parameters using a 7-point scale and retold their content. Students’ motivation was measured by “Academic Motivation Scale”. In addition, students reported about their professional plans and professional experience. Results. Students assessed video lectures lower and reproduced their content worse in comparison with classroom lectures. Assessments of the video lecture content were positively correlated with the students’ intrinsic cognitive motivation, and the volume of the reproduced content of the lecture was negatively correlated with extrinsic motivation. The influence of intrinsic cognitive motivation and extrinsic motivation of students on the assessment of the video lecture content and the volume of the reproduced content was confirmed by a variance analysis. Conclusions. In terms of online interaction, the students’ subjective assessments of the classroom lectures are reduced. Intrinsic cognitive motivation prevents the reduction of sub¬jective assessments of the video content. Extrinsic motivation helps to reduce the reproduced content of the video lecture.
Keywords: online interaction, teacher, students, academic motivation, online learning, efficiency of learning, video lecture
Column: Empirical Research
The reported study was funded by RFBR, project number 19-013-00412.
1. Gordeeva T.O., Sychev O.A., Osin E.N. Oprosnik “Shkaly akademicheskoi motivatsii” [“Academic motivation scales” questionnaire]. Psikhologicheskii zhurnal [Psychological Journal], 2014, Vol. 35, no. 4. pp. 96—107. (In Russ., abstr in Engl.)
2. Nasledov A.D. Psikhologicheskie osobennosti obucheniya v usloviyakh tekhnicheski oposredovannogo pedagogicheskogo obshcheniya : avtoreferat diss. k.ps.n. [Psychological features of training in the conditions of technically mediated pedagogical communication. Ph. D. (Psychology) Thesis]. Leningrad, 1990. 16 p.
3. Orlova A.V. Osobennosti sotsial’noi pertseptsii litsa cheloveka, pred”yavlyaemogo na ekrane monitora : avtoreferat dis. kand. ps. n. [Features of social perception of a person’s face presented on a monitor screen. Ph. D. (Psychology) Thesis]. Saint-Petersburg, 2009. 24 p.
4. Shamina N.V. Onlain-obuchenie v obrazovatel’nom protsesse: sil’nye i slabye storony [Online learning in the educational process: strengths and weakness]. Kazanskii pedagogicheskii zhurnal [Kazan Pedagogical Journal], 2019. Vol. 2, no. 133, pp. 20—24.
5. Bassili J.N. Motivation and Cognitive Strategies in the Choice to Attend Lectures or Watch Them Online. Journal of Distance Education, 2008. Vol. 22, no. 3, pp. 129—148.
6. Brooker A. et al. A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology, 2018. Vol. 34, no. 1, pp. 73—87. doi:10.14742/ajet.3237
7. Chen K.C., Jang S.J. Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 2010. Vol. 26, no. 4, pp. 741—752. doi:10.1016/j.chb.2010.01.011
8. Cho M.H., Heron M.L. Self-regulated learning: the role of motivation, emotion, and use of learning strategies in students’ learning experiences in a self-paced online mathematics course. Distance Education, 2015. Vol. 36, no. 1, pp. 80—99. doi:10.1080/01 587919.2015.1019963
9. De Barba P.G., Kennedy G.E., Ainley M.D. The role of students’ motivation and participation in predicting performance in a MOOC. Journal of Computer Assisted Learning, 2016. Vol. 32, no. 3, pp. 218-231. doi:10.1111/jcal.12130
10. Deci E.L., Ryan R.M. Intrinsic motivation and self-determination in human behavior. New York: Plenum, 1985. 372 p. doi:10.1007/978-1-4899-2271-7
11. Hartnett M., George A.S., Dron J. Examining motivation in online distance learning environments: Complex, multifaceted and situation-dependent. The International Review of Research in Open and Distributed Learning, 2011. Vol. 12, no. 6, pp. 20—38, doi:10.19173/irrodl.v12i6.1030
12. Inglis M. et al. Individual differences in students’ use of optional learning resources. Journal of Computer Assisted Learning, 2011. Vol. 27, no. 6, pp. 490—502. doi:10.1111/ j.1365-2729.2011.00417.x
13. Kim K.J., Frick T.W. Changes in student motivation during online learning. Journal of Educational Computing Research, 2011. Vol. 44, no. 1, pp. 1—23. doi:10.2190/EC.44.1.a
14. Le A. et al. Online lecture accessibility and its influence on performance in skills-based courses. Computers & Education, 2010. Vol. 55, no. 1, pp. 313—319. doi:10.1016/j. compedu.2010.01.017
15. Liu Q. et al. The effectiveness of blended learning in health professions: systematic review and meta-analysis. Journal of medical Internet research, 2016. Vol. 18, no. 1. doi:10.2196/jmir.4807
16. Markova T.,
17. Means B. et al. The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 2013. Vol. 115(3), pp. 1—47.
18. Muilenburg L.Y., Berge Z.L. Student barriers to online learning: A factor analytic study. Distance Education, 2005. Vol. 26, no. 1, pp. 29—48. doi:10.1080/01587910500081269
19. Milligan C., Littlejohn A. Why study on a MOOC? The motives of students and professionals. The International Review of Research in Open and Distributed Learning, 2017. Vol. 18, no. 2, URL: http://www.irrodl.org/index.php/irrodl/article/view/3033 (assessed: 02.08.2019). doi:10.19173/irrodl.v18i2.3033
20. O’Neill D.K., Sai T.H. Why not? Examining college students’ reasons for avoiding an online course. Higher Education, 2014. Vol. 68, no. 1, pp. 1—14. doi:10.1007/s10734-013-9663-3
21. Richardson J.C. et al. Social presence in relation to students’ satisfaction and learning in the online environment: A meta-analysis. Computers in Human Behavior, 2017. Vol. 71, pp. 402—417. doi:10.1016/j.chb.2017.02.001
22. Short J.A., Williams E., Christie B. The social psychology of telecommunications. London: Wiley, 1976. 195 p.
23. Tu C.H., McIssac M. The relationship of social presence and interaction in online classes. The American journal of distance education, 2002. Vol. 16, no. 3, pp. 131—150. doi:10.1207/S15389286AJDE1603_2
24. Wang Y., Baker R. Content or platform: Why do students complete MOOCs? MERLOT Journal of Online Learning and Teaching, 2015. Vol. 11, no. 1, pp. 17—30.
25. Young S., Duncan H.E. Online and face-to-face teaching: How do student ratings differ? MERLOT Journal of Online Learning and Teaching, 2014. Vol. 10, no. 1, pp. 70—79.