Research Article

Effect of Educational Videos on the Interest, Motivation, and Preparation Processes for Mathematics Courses

Emine Ozgur Sen 1 *
More Detail
1 Department of Mathematics and Science Education, Faculty of Education, Yozgat Bozok University, Yozgat, TURKEY* Corresponding Author
Contemporary Mathematics and Science Education, 3(1), 2022, ep22009,
Published: 10 March 2022
OPEN ACCESS   1519 Views   1828 Downloads
Download Full Text (PDF)


Videos are widely used teaching materials in education. The current research aimed to conduct an examination of the effects that different educational videos prepared for the distance education model had on the motivation, interest, and course preparation processes of students for mathematics courses. A total of 106 (80 females and 26 males) mathematics teacher candidates agreed to participate in the current study. Two different educational videos were used in the study. The first of these was prepared by the educator, while the second was taken from the Khan Academy education videos. It was determined that, although the educational videos prepared by the educator made no significant difference with regard to the motivation of the students toward the course, there was a significant difference with regard to the level of interest in the course. On the other hand, the Khan Academy videos were found to have a significant effect on the pre-test as well as the post-test scores of the motivation of students toward the course, but did not result in a significant difference in their interest in the course.


Sen, E. O. (2022). Effect of Educational Videos on the Interest, Motivation, and Preparation Processes for Mathematics Courses. Contemporary Mathematics and Science Education, 3(1), ep22009.


  1. Ainley, M., Hidi, S., & Berndorff, D. (2002). Interest, learning, and the psychological processes that mediate their relationship. Journal of Educational Psychology, 94(3), 545-561.
  2. Bergin, D. A. (2016). Social influences on interest. Educational Psychologist, 51(1), 7-22.
  3. Bertiz, Y., & Karoglu, A. K. (2020). Distance education students’ cognitive flexibility levels and distance education motivations. International Journal of Research in Education and Science, 6(4), 638-648.
  4. Bozkurt, A. (2019). From distance education to open and distance learning: a holistic evaluation of history, definitions, and theories. In S. Sisman-Ugur, & G. Kurubacak (Eds.), Handbook of research on learning in the age of transhumanism (pp. 252-273). IGI Global.
  5. Brame, C. J. (2016). Effective educational videos: Principles and guidelines for maximizing student learning from video content. CBE—Life Sciences Education, 15(4), 1-6.
  6. Bravo, E., Amante, B., Simo, P., Enache, M., & Fernandez, V. (2011, April). Video as a new teaching tool to increase student motivation. In Proceedings of the IEEE Global Engineering Education Conference (pp. 638-642).
  7. Cakir, O., Karademir, T., & Erdogdu, F. (2018). Psychological variables of estimating distance learners’ motivation. Turkish Online Journal of Distance Education, 19(1), 163-182.
  8. Carmichael, C., Callingham, R., & Watt, H. M. (2017). Classroom motivational environment influences on emotional and cognitive dimensions of student interest in mathematics. ZDM, 49(3), 449-460.
  9. Carney, D., Ormes, N., & Swanson, R. (2015). Partially flipped linear algebra: A team-based approach. PRIMUS, 25(8), 641-654.
  10. Chang, C. (2004). Constructing a streaming video-based learning forum for collaborative learning. Journal of Educational Multimedia and Hypermedia, 13(3), 245-263.
  11. Chao, T., Saj, T., & Tessier, F. (2006). Establishing a quality review for online courses. Educause Quarterly, 29(3), 32-39.
  12. Choi, H. J., & Johnson, S. D. (2005). The effect of context-based video instruction on learning and motivation in online courses. The American Journal of Distance Education, 19(4), 215-227.
  13. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Lawrence Erlbaum Associates, Publishers.
  14. de Barba, P. G., Kennedy, G. E., & Ainley, M. D. (2016). The role of students’ motivation and participation in predicting performance in a MOOC. Journal of Computer Assisted Learning, 32(3), 218-231.
  15. de Barros, R. S. M., Hidalgo, J. I. G., & de Lima-Cabral, D. R. (2018). Wilcoxon rank sum test drift detector. Neurocomputing, 275, 1954-1963.
  16. Dewey, J. (1913). Interest and effort in education. Houghton Mifflin.
  17. Dincer, S., & Doganay, A. (2016). Turkish adaptation study of instructional materials motivation survey (IMMS). Elementary Education Online, 15(4), 1131-1148.
  18. Field, A. (2009). Discovering statistics using SPSS. SAGE.
  19. Firat, M., Kilinc, H., & Yuzer, T. V. (2018). Level of intrinsic motivation of distance education students in e‐learning environments. Journal of Computer Assisted Learning, 34(1), 63-70.
  20. Geisler, S., & Rach, S. (2019). Interest development and satisfaction during the transition from school to university. In M. Graven, H. Venkat, A. Essien, & P. Vale (Eds.), Proceedings of the 43rd Conference of the International Group for the Psychology of Mathematics Education (pp. 264-271). PME.
  21. George, D., & Mallery, P. (2010). SPSS for Windows step by step. A simple study guide and reference. Pearson Education.
  22. Guo, P. J., Kim, J., & Rubin, R. (2014, March). How video production affects student engagement: An empirical study of MOOC videos. In Proceedings of the 1st ACM Conference on Learning@ Scale Conference (pp. 41-50).
  23. Hartnett, M., St George, A., & Dron, J. (2011). Examining motivation in online distance learning environments: Complex, multifaceted, and situation-dependent. International Review of Research in Open and Distributed Learning, 12(6), 20-38.
  24. Hidi, S., & Harackiewicz, J. M. (2000). Motivating the academically unmotivated: A critical issue for the 21st century. Review of Educational Research, 70(2), 151-179.
  25. Hidi, S., & Renninger, K. A. (2006). The four-phase model of interest development. Educational Psychologist, 41(2), 111-127.
  26. Huang, B., & Hew, K. F. T. (2016). Measuring learners’ motivation level in massive open online courses. International Journal of Information and Education Technology, 6(10), 759-764.
  27. Kay, R., & Kletskin, I. (2012). Evaluating the use of problem-based video podcasts to teach mathematics in higher education. Computers & Education, 59(2), 619-627.
  28. Keller, J. M. (2005). Course interest course survey – Short form. Tallahassee, Florida.
  29. Keller, J. M. (2008) First principles of motivation to learn and e3‐learning. Distance Education, 29(2), 175-185.
  30. Keller, J. M. (2010). Motivational design for learning and performance: The ARCS Model approach. Springer.
  31. Keller, J. M., & Suzuki, K. (2004) Learner motivation and e-learning design: A multinationally validated process. Journal of Educational Media, 29(3), 229-239.
  32. Larreamendy-Joerns, J., & Leinhardt, G. (2006). Going the distance with online education. Review of Educational Research, 76(4), 567-605.
  33. Liao, L. F. (2006). A flow theory perspective on learner motivation and behavior in distance education. Distance Education, 27(1), 45-62.
  34. Linnenbrink-Garcia, L., Durik, A. M., Conley, A. M., Barron, K. E., Tauer, J. M., Karabenick, S. A., & Harackiewicz, J. M. (2010). Measuring situational interest in academic domains. Educational and Psychological Measurement, 70(4), 647-671.
  35. Mullen, G. E., & Tallent-Runnels, M. K. (2006). Student outcomes and perceptions of instructors’ demands and support in online and traditional classrooms. Internet & Higher Education, 9(4), 257-266.
  36. Murphy, P. K., & Alexander, P. A. (2000). A motivated exploration of motivation terminology. Contemporary Educational Psychology, 25(1), 3-53.
  37. Pallant, J. (2002). SPSS survival manual. A step by step guide to data analysis using SPSS. Edmundsbury Press.
  38. Park, J. H., & Choi, H. J. (2009). Factors influencing adult learners’ decision to drop out or persist in online learning. Educational Technology & Society, 12(4), 207-217.
  39. Ratanothayanon, K. (2018, May). The comparison of undergraduate student’s learning achievement of open video online in business statistics course. In Proceedings of the 5th International Conference on Business and Industrial Research (pp. 550-554).
  40. Renninger, K. A., & Bachrach, J. E. (2015). Studying triggers for interest and engagement using observational methods. Educational Psychologist, 50(1), 58-69.
  41. Renninger, K. A., & Hidi, S. (2011). Revisiting the conceptualization, measurement, and generation of interest. Educational Psychologist, 46(3), 168-184.
  42. Rovai, A. P. (2003). A practical framework for evaluating online distance education programs. The Internet and Higher Education, 6(2), 109-124.
  43. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54-67.
  44. Sahin, A., Cavlazoglu, B., & Zeytuncu, Y. E. (2015). Flipping a college calculus course: A case study. Educational Technology & Society, 18(3), 142-152.
  45. Sansone, C., Smith, J. L., Thoman, D. B., & MacNamara, A. (2012). Regulating interest when learning online: Potential motivation and performance trade-offs. The Internet and Higher Education, 15(3), 141-149.
  46. Shroff, R. H., Vogel, D. R., Coombes, J., & Lee, F. (2007). Student e-learning intrinsic motivation: A qualitative analysis. Communications of the Association for Information Systems, 19(1), 12.
  47. Sun, J. C. Y., & Rueda, R. (2012). Situational interest, computer self‐efficacy and self‐regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191-204.
  48. Tallent-Runnels, M. K., Thomas, J. A., Lan, W. Y., Cooper, S., Ahern, T. C., Shaw, S. M., & Liu, X. (2006). Teaching courses online: A review of the research. Review of Educational Research, 76(1), 93-135.
  49. Ucar, H. (2016). The effects of the motivational strategies on learners’ interest, motivation, volition, and achievement in distance education [Unpublished doctoral thesis]. Anadolu University.
  50. Ucar, H., & Kumtepe, A. T. (2020). Effects of the ARCS‐V‐based motivational strategies on online learners’ academic performance, motivation, volition, and course interest. Journal of Computer Assisted Learning, 36(3), 335-349.
  51. Vidergor, H. E., & Ben-Amram, P. (2020). Khan academy effectiveness: The case of math secondary students’ perceptions. Computers & Education, 157, 103985.
  52. Weber, K. (2003). The relationship of interest to internal and external motivation. Communication Research Reports, 20(4), 376-383.
  53. Williamson, B., Eynon, R., & Potter, J. (2020). Pandemic politics, pedagogies and practices: digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2), 107-114.
  54. Zhang, D., Zhou, L., Briggs, R. O., & Nunamaker Jr, J. F. (2006). Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management, 43(1), 15-27.