Enhancing Graduate Studies with Interactive Videos: Uncovering Student and Instructor Perspectives on Motivation, Self-Efficacy, and Future Intentions

Year 2024, Volume: 11 Issue: 5, 81 - 101, 12.09.2024

Nuray Gedik , Barış Yiğit , İlknur Demirtaş , Kadir Gedik , Zehra Yiğit Avdan

https://doi.org/10.17275/per.24.65.11.5

Abstract

Laboratory-based courses and research studies play a crucial role in many fields in higher education. With the idea that the creation and use of interactive materials of experimental periods can be a potentially transformative teaching and learning experience, graduate students and instructors have been trained to design and integrate interactive videos as part of their experimental studies. This study aimed to explore self-efficacy, motivation and future intentions of graduate student and instructors to develop and use interactive videos as a learning material. Using a mixed-method approach via a questionnaire and semi-structured interviews, data were collected from graduate students and instructors before and after face-to-face/online trainings on the design and use of interactive videos. Data were analyzed descriptively for the survey items on motivation and perceptions on the use of interactive videos for graduate experiments. For the interview data, the data were analyzed based on specific themes. The results showed that the self-efficacy of the participants have been increased and they had high motivation and strong intention to use interactive videos for a number of reasons. As the participants' self-efficacy has improved, they reported positive perceptions regarding the contributions of interactive videos to their understanding of experimental processes. The findings showed that graduate students shooting an experimental process with their presence can yield better learning outcomes for other graduate students. The results can be valuable for demonstrating potential use of interactive videos during laboratory-based educational and research contexts.

Keywords

interactive learning material, laboratory work, digital learning, higher education

Ethical Statement

The ethics approval was gathered on 09.01.2023 from the Ethics Committee of Eskisehir Technical University with the number 87914409-640-2300001361. Informed consent was obtained from all individual participants included in the study.

Supporting Institution

The Scientific and Technological Research Council of Türkiye (TUBITAK)

Project Number

122B188

References

• Albion, P. R. (1999). Self-efficacy beliefs as an indicator of teachers’ preparedness for teaching with technology. Proceedings of Society for Information Technology & Teacher Education International Conference. Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).
• Alsharif, A. (2024) Understanding technology. Pressbooks. Utah Valley University. https://uen.pressbooks.pub/tech1010/
• Anantrasirichai, N., & Bull, D. R. (2021). Artificial intelligence in the creative industries: a review. Artificial Intelligence Review, 55(1), 589–656. https://doi.org/10.1007/s10462-021-10039-7
• Bakla, A., & Mehdiyev, E. (2022). A qualitative study of teacher-created interactive videos versus YouTube videos in flipped learning. E-Learning and Digital Media, 19(5), 495-514. https://doi.org/10.1177/20427530221107789
• Bal, I.A., Arslan, O., Budhrani, K. et al. (2020). The balance of roles: Graduate student perspectives during the COVID-19 pandemic. TechTrends 64, 796–798. https://doi.org/10.1007/s11528-020-00534-z
• Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71-81). New York: Academic Press
• Bandura, A. (1997). Self-efficacy: The exercise of control. Macmillan.
• Barut Tugtekin, E., & Dursun, O. O. (2022). Effect of animated and interactive video variations on learners' motivation in distance education. Education and Information Technologies, 27(3), 3247-3276. https://doi.org/10.1007/s10639-021-10735-5
• Bates, T. A.W. (2005). Technology, e-learning and distance Education. (2nd ed). New York: Routledge.
• Bates, T., Cobo, C., Marino, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education? International Journal of Educational Technology in Higher Education, 17, 1-12. https://doi.org/10.1186/s41239-020-00218-x
• Berg, C. (2023). The case for generative AI in scholarly practice. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4407587
• Boekaerts, M. (2010). Motivation and self-regulation: two close friends. In T. Urdan, & S. A. Karabenick (Eds.), Advances in motivation and achievement. The next decade of research in motivation and achievement, 16B, 73-112, London: Emerald.
• Bos, A. S., Zaro, M. A., Prestes, L. P., Pízzato, M. C., De Azevedo, D. F. G., De Avila, F. R., & Batista, M. C. (2019). Student’s attention: The use of brain waves sensors in interactive videos. International Journal of Advanced Engineering Research and Science, 6(4), 155–157. https://doi.org/10.22161/ijaers.6.4.18
• Bouffard-Bouchard, T., Parent, S., & Larivee, S. (1991). Influence of self-efficacy on self-regulation and performance among junior and senior high-school age students. International Journal of Behavioral Development, 14(2), 153-164. https://doi.org/10.1177/016502549101400203
• Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
• Chan, C., & Zhou, W. (2023). Deconstructing student perceptions of generative AI (GenAI) through an expectancy value theory (EVT)-based instrument. Preprint Document.
• Chan, C.K.Y., Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(43). https://doi.org/10.1186/s41239-023-00411-8
• Cresswell, S. L., Loughlin, W. A., Coster, M. J., & Green, D. M. (2019). Development and Production of Interactive Videos for Teaching Chemical Techniques during Laboratory Sessions. Journal of Chemical Education, 96(5), 1033–1036. https://doi.org/10.1021/acs.jchemed.8b00647
• Cuban, L. (1986). Teachers and machines: the classroom use of technology since 1920. New York: Teachers College Press.
• Dagar, D., & Vishwakarma, D. K. (2022). A literature review and perspectives in deepfakes: generation, detection, and applications. International Journal of Multimedia Information Retrieval, 11(3), 219–289. https://doi.org/10.1007/s13735-022-00241-w
• Dieck-Assad, G., Hinojosa-Olivares, J. M., & Colomer-Farrarnos, J. (2020). Study of the effectiveness of interactive videos in applied electronics courses.” International Journal on Interactive Design &Manufacturing (IJIDeM) 14(3): 983–1001. https://doi.org/10.1007/s12008-020-00689-2
• Doğru, M. S. (2023). ChatGPT - Science education and instruction reshapes management. Online Science Education Journal, 8(1), 12-21.
• Doğru, M. S., Yüzbaşıoğlu, F., & Arpaci, İ. (2023). The effect of interactive videos enhanced with pop-up questions on teacher candidates’ learning performance in science. Research In Science & Technological Education, 1-16. https://doi.org/10.1080/02635143.2023.2272820
• European Commission. (2020). Digital education action plan (2021-2027). Publications Office of the European Union.
• Feher, K. (2024). Exploring AI media. Definitions, conceptual model, research agenda. Journal of Media Business Studies, 1–24. https://doi.org/10.1080/16522354.2024.2340419
• Fintschenko, Y. (2011). Education: A modular approach to microfluidics in the teaching laboratory. Lab on a Chip, 11(20), 3394-3400.
• Firdaus, M., Mukhtar, Darari, M. B., & Azis, Z. (2021). Designing interactive videos in online multivariable calculus course to support student’s critical thinking. Journal of Physics, 1819(1), 012057. https://doi.org/10.1088/1742-6596/1819/1/012057
• Gedik, N. & Yiğit, B. (2023). Mikroplastik ar-ge çalışmalarının dijitalleştirilmesi ve yayılımı bağlamında videolar [Videos in the context of digitization and dissemination of microplastics R&D studies]. In K. Gedik & E. Gaga (Eds). Mikroplastiklerden Nanoplastiklere Plastik Partiküller [Plastic Particles from Microplastics to Nanoplastics] (pp. 483-500). Nobel Yayın.
• Harrer, S. (2023). Attention is not all you need: The complicated case of ethically using large language models in healthcare and medicine. eBioMedicine, 90, 104512. https://doi.org/10.1016/j.ebiom.2023.104512
• Howard, S., Buttke, D., Lovejoy, T. Ε., Clark, K., Ashby, E., & Aguirre, A. A. (2021). The Loop Trail “Quest”: Use of a Choice-based Digital Simulation, An Interactive Video, and a Booklet to Communicate and Analyze Decision-making of Park Visitors. Environmental Communication-a Journal of Nature and Culture, 15(8), 1025–1044. https://doi.org/10.1080/17524032.2021.1927129
• Howell, D. C. (2019). Statistical methods for psychology (9th ed.). Cengage Learning.
• Hsia, J. W., Chang, C. C., & Tseng, A. H. (2014). Effects of individuals’ locus of control and computer self-efficacy on their e-learning acceptance in high-tech companies. Behaviour & Information Technology, 33(1), 51-64.
• Jiang, L., Yu, S., & Zhao, Y. (2019). Teacher engagement with digital multimodal composing in a Chinese tertiary EFL curriculum. Language Teaching Research. doi:10.1177/1362168819864975
• Jiang, L., Zang, N., Zhou, N., & Cao, H. (2022). English teachers’ intention to use flipped teaching: Interrelationships with needs satisfaction, motivation, self-efficacy, belief, and support. Computer Assisted Language Learning, 35(8), 1890-1919.
• Karmila, D., Putri, D. M., Berlian, M., Pratama, D. O., & Fatrima. (2021). The role of interactive videos in mathematics learning activities during the COVID-19 pandemic. Advances in Social Science, Education and Humanities Research. https://doi.org/10.2991/assehr.k.210227.024
• Keller, J. M. (2016). Motivation, learning, and technology: Applying the ARCS-V motivation model. Participatory Educational Research (PER), 3(2), 1-13. http://dx.doi.org/10.17275/per.16.06.3.2
• Kumar, J.A., Bervell, B., & Osman, S. (2020). Google classroom: Insights from Malaysian higher education students’ and instructors’ experiences. Education and Information Technologies, 25(5), 4175-4195. https://doi.org/10.1007/s10639-020-10163-x
• Mayer, R. E. (1997). Multimedia learning: Are we asking the right questions? Educational Psychologist, 32(1), 1-19. https://doi.org/10.1207/s15326985ep3201_1
• Mayer, R. E. (2005). The Cambridge handbook of multimedia learning. New York: Cambridge University Press.
• Mayer, R. E. (2014a). Introduction to multimedia learning. In R. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (Cambridge Handbooks in Psychology, pp. 1-24). Cambridge: Cambridge University Press. doi:10.1017/CBO9781139547369.002
• Mayer, R. E. (2014b). Cognitive theory of multimedia learning. In R. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (Cambridge Handbooks in 177 Psychology, pp. 43-71). Cambridge: Cambridge University Press. doi:10.1017/CBO9781139547369.005
• Mayer, R. E., & Pilegard, C. (2014). Principles for managing essential processing in multimedia learning: Segmenting, pre-training, and modality principles. In R. E. Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 316–344). Cambridge University Press.
• Mayer, R.E., Fiorella, L. & Stull, A. (2020). Five ways to increase the effectiveness of instructional video. Educational Technology Research & Development, 68, 837–852. https://doi.org/10.1007/s11423-020-09749-6
• Merkt, M., Weigand, S., Heier, A., & Schwan, S. (2011). Learning with videos vs learning with print: The role of interactive features. Learning and Instruction, 21(6), 687-704. https://doi.org/10.1016/j.learninstruc.2011.03.004.
• Newstetter, W. C., Behravesh, E., Nersessian, N. J., & Fasse, B. B. (2010). Design principles for problem-driven learning Bakla, A., & Mehdiyev, E. (2022). A qualitative study of teacher-created interactive videos versus YouTube videos in flipped learning. E-learning and Digital Media, 19(5), 495–514. https://doi.org/10.1177/20427530221107789
• Pi, Z., Zhang, Y., Yu, Q., & Yang, J. (2023). A familiar peer improves students’ behavior patterns, attention, and performance when learning from video lectures. International Journal of Educational Technology in Higher Education, 20. https://doi.org/10.1186/s41239-023-00418-1
• Pintrich, P. R. (1999). The role of motivation in promoting and sustaining self-regulated learning. International Journal of Educational Research, 31(6), 459-470. doi:10.1016/s0883-0355(99)00015-4
• Pintrich, P. R., & Zusho, A. (2002). The development of academic self-regulation: the role of cognitive and motivational factors. In A. Wigfield, & J. S. Eccles (Eds.), Development of achievement motivation (pp. 249–284). San Diego: Academic Press.
• Ploetzner, R. (2022). The effectiveness of enhanced interaction features in educational videos: A meta-analysis. Interactive Learning Environments, 1–16. https://doi.org/10.1080/10494820.2022.2123002
• Preradovic, N.M., Lauc, T., & Panev, I. (2020). Investigating interactivity in instructional video tutorials for an undergraduate informatics course. Issues in Educational Research, 30, 203-223.
• Radhamani, R., Kumar, D., Nizar, N., Achuthan, K., Nair, B., & Diwakar, S. (2021). What virtual laboratory usage tells us about laboratory skill education pre-and post-COVID-19: Focus on usage, behavior, intention and adoption. Education and Information Technologies, 26(6), 7477-7495.
• Rosenthal, R. (1991). Meta-analytic procedures for social research (Rev. ed.). SAGE Publications.
• Saettler, P. (2004). The evolution of American educational technology. Greenwich, CT: Information Age Publishing.
• Schoentgen, A., & Wilkinson, L. (2021). Ethical issues in digital technologies. 23rd Biennial Conference of the International Telecommunications Society (ITS): "Digital societies and industrial transformations: Policies, markets, and technologies in a post-Covid world", Gothenburg, Sweden.
• Schunk, D. H., & Hanson, A. R. (1985). Peer models: Influence on children's self-efficacy and achievement. Journal of Educational Psychology, 77, 313–322.
• Schunk, D. H., & Zimmerman, B. J. (2008). Motivation and self-regulated learning: Theory, research, and applications. Mahwah, NJ: Lawrence Erlbaum.
• Schunk, D.H. (1984). Self-efficacy perspective on achievement behavior. Educational Psychologist, 19, 48–58.
• Schwan, S., & Riempp, R. (2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and Instruction, 14, 293–305.
• Shroff, R. H., & Keyes, C. J. (2017). A proposed framework to understand the intrinsic motivation factors on university students’ behavioral intention to use a mobile application for learning. Journal of Information Technology Education: Research, 16, 143-168. Retrieved from http://www.informingscience.org/Publications/3694
• Sinnayah, P., Salcedo, A., & Rekhari, S. (2021). Reimagining physiology education with interactive content developed in H5P. Advances in Physiology Education, 45(1), 71–76. https://doi.org/10.1152/advan.00021.2020
• Smaldino, S. E., Lowther, D. L., Mims, C., & Russell, J. D. (2014). Instructional technology and media for learning. Pearson Limited.
• Spanjers, I. A. E., van Gog, T., & van Merriënboer, J. J. G. (2010). A theoretical analysis of how segmentation of dynamicvisualizations optimizes students’ learning. Educational Psychology Review, 22(4), 411–423. https://doi.org/10.1007/s10648-010-9135-6
• Taslibeyaz, E., Dursun, O. B., Karaman, S. (2016). Interactive video usage on autism spectrum disorder training in medical education. Interactive Learning Environments, 25(8), 1025-1034. https://doi.org/10.1080/10494820.2016.1242504
• Uğur, S., & Okur, M. R. (2016). Açık ve uzaktan öğrenmede etkileşimli video kullanımı [Interactive video use in open and distance learning]. AUAd, 2(4), 104-126.
• UNESCO (2021). Reimagining our futures together: A new social contract for education. United Nations Educational, Scientific and Cultural Organization.
• Wachtler, J., Hubmann, M., Zöhrer, H. et al. (2016). An analysis of the use and effect of questions in interactive learning-videos. Smart Learning Environments, 3(13). https://doi.org/10.1186/s40561-016-0033-3
• Whittaker, L., Kietzmann, T. C., Kietzmann, J., & Dabirian, A. (2020). “All around me are synthetic faces”: The mad world of AI-Generated Media. IT Professional, 22(5), 90–99. https://doi.org/10.1109/mitp.2020.2985492
• Wiseman, A., Al-Bakr, F., Davidson, P. M., & Bruce, E. (2018). Using technology to break gender barriers: Gender differences in teachers’ information and communication technology use in Saudi Arabian classrooms. Compare: A Journal of Comparative and International Education, 48(2), 224–243. doi:10.1080/03057925.2017.1301200.
• Zhang, D., Zhou, L., Briggs, R.O., & Nunamaker, J.F. (2006). Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management, 43(1),15-27. https://doi.org/10.1016/j.im.2005.01.004
• Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25(1), 82–91. https://doi.org/10.1006/ceps.1999.1016
• Zimmerman, B. J., & Kitsantas, A. (1999). Acquiring writing revision skill: Shifting from process to outcome self-regulatory goals. Journal of Educational Psychology, 91, 1-10.
• Zimmerman, B. J., & Schunk, D. H. (2004). Self-regulating intellectual processes and outcomes: A social cognitive perspective. In D. Y. Dai & R. J. Sternberg (Eds.), Motivation, emotion, and cognition: Integrative perspectives on intellectual functioning and development (pp. 323–349). Lawrence Erlbaum Associates.