An investigation of using elaborated and metacognitive feedback strategies in interactive instructional videos

Year 2023, Volume: 6 Issue: 4 - ICETOL 2023 Special Issue, 991 - 1008, 31.12.2023

Ezgi Diri Koç Diler Öner

https://doi.org/10.31681/jetol.1339219

Abstract

The purpose of this study is to compare the use of elaborated and metacognitive feedback strategies in interactive instructional videos in terms of undergraduate students’ engagement and metacognitive awareness levels. This study also aims to investigate undergraduate students’ evaluations of elaborated and metacognitive feedback in these instructional videos based on qualitative data. This study used a basic randomized post-test-only experimental design comparing two treatments supported by qualitative data. The participants were 52 preservice teachers who registered for an undergraduate educational technology course offered by a faculty of education. They were randomly assigned to the metacognitive and the elaborated feedback groups. The data were collected with the Short Form of the User Engagement Scale and the Metacognitive Awareness Inventory. In addition, qualitative data were collected through interviews and used to examine students’ evaluations of the elaborated and metacognitive feedback used in the interactive instructional videos. The results showed that there was no statistically significant difference between the two types of feedback in terms of students’ engagement and metacognitive awareness levels. The qualitative findings indicated that while the two types of feedback did not provide a significant superiority over each other, students viewed the two types of feedback as serving different purposes. Our findings suggest that customizing the type of feedback based on students' answers and subject mastery level, or a thoughtful integration of both types of feedback, could enhance the learning experience in interactive instructional videos.

Keywords

Interactive Instructional Videos, Feedback, Metacognitive Feedback, Elaborated Feedback, Video-Based Learning

References

• Abdelrahman, R. M. (2020). Metacognitive awareness and academic motivation and their impact on academic achievement of Ajman University students. Heliyon, 6(9), e04192.
• Adagideli, F. H., & Ader, E. (2017). Investigation of young children’s metacognitive regulatory abilities in mathematical problem-solving tasks. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 18(2), 193-211.
• Aktaş, E. E. (2021). The effects of traditional corrective feedback and language awareness enhanced feedback on learners’ second language and foreign language writing performance development (Unpublished Master’s Thesis). Bahçeşehir University, Istanbul, Turkey.
• Altıok, S., Başer, Z., & Yükseltürk, E. (2019). Enhancing metacognitive awareness of undergraduates through using an e-educational video environment. Computers & Education, 139, 129-145.
• Asha, L., Hamengkubuwono, Morganna, R., Warsah, I., & Alfarabi. (2022). Teacher collaborative metacognitive feedback as the application of teacher leadership concept to scaffold educational management students’ metacognition. European Journal of Educational Research, 981-993.
• Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245-281.
• Cho, M. H., & Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3), 290-301.
• Chung, Y. B., & Yuen, M. (2011). The role of feedback in enhancing students’ self-regulation in inviting schools. Journal of Invitational Theory and Practice, 17, 22-27.
• Coates, H. (2005). The value of student engagement for higher education quality assurance. Quality in Higher Education, 11(1), 25-36.
• Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson.
• Cummins, S., Beresford, A. R., & Rice, A. (2016). Investigating engagement with in-video quiz questions in a programming course. IEEE Transactions on Learning Technologies, 9(1), 57-66.
• Dignath, C., & Büttner, G. (2008). Components of fostering self-regulated learning among students. A meta-analysis on intervention studies at primary and secondary school level. Metacognition and Learning, 3(3), 231-264.
• Delen, E., Liew, J., & Willson, V. (2014). Effects of interactivity and instructional scaffolding on learning: Self-regulation in online video-based environments. Computers & Education, 78, 312-320.
• Eidenberger, M., & Nowotny, S. (2022). Video-based learning compared to face-to-face learning in psychomotor skills physiotherapy education. Creative Education, 13, 149-166.
• Field, A. (2009). Discovering statistics using SPSS (Third Edition). Sage Publications.
• Flavell, J. H. (1976). Metacognitive aspects of problem-solving, In L. B. Resnick (Ed.), The Nature of Intelligence (pp. 231-235). Lawrence Erlbaum.
• Gilman, A. G. (1969). Comparison of several feedback methods for correcting errors by computer-assisted instruction. Journal of Educational Psychology, 503-508.
• Golke, S., Dörfler, T., & Artelt, C. (2015). The impact of elaborated feedback on text comprehension within a computer-based assessment. Learning and Instruction, 39, 123-136.
• Guo, W., Chen, Y., Lei, J., & Wen, Y. (2014). The effects of facilitating feedback on online learners’ cognitive engagement: Evidence from the asynchronous online discussion. Education Sciences, 4(2), 193-208.
• Harrison, G. M., & Vallin, L. (2018). Evaluating the Metacognitive Awareness Inventory using empirical factor-structure evidence. Metacognition and Learning, 13(1), 15-38.
• Hepplestone, S., Holden, G., Irwin, B., Parkin, H. J., & Thorpe, L. (2011). Using technology to encourage student engagement with feedback: A literature review. Research in Learning Technology, 19(2), 117-127.
• Jaehnig, W., & Miller, M. (2007). Feedback types in programmed instruction: A systematic review. The Psychological Record, 57(2), 219–232.
• Karaoğlan Yılmaz, F. G., & Yılmaz, R. (2021). Learning analytics intervention improves students’ engagement in online learning. Technology, Knowledge, and Learning, 27(2).
• Khan, M. J., & Seemab, R. (2019). Moderating role of learning strategies between meta-cognitive awareness and study habits among university students. Pakistan Journal of Psychological Research, 34(1), 215-231.
• Khodaei, S., Hasanvand, S., Gholami, M., Mokhayeri, Y., & Amini, M. (2022). The effect of the online flipped classroom on self-directed learning readiness and metacognitive awareness in nursing students during the COVID-19 pandemic. BMC Nursing, 21(1), 22.
• Kim, J. H. (2018). The effect of metacognitive monitoring feedback on performance in a computer-based training simulation. Applied Ergonomics, 193-202.
• King, A. (1991). Effects of training in strategic questioning on children’s problem-solving performance. Journal of Educational Psychology, 83(3), 307–317.
• Kleij, F. M., Eggen, T. J., Timmers, C. F., & Veldkamp, B. P. (2012). Effects of feedback in a computer-based assessment for learning. Computers & Education, 263-272.
• Kolas, L. (2015). Application of interactive videos in education. International Conference on Information Technology Based Higher Education and Training (ITHET). Lisbon, Portugal: IEEE.
• Kovacs, G. (2016). Effects of in-video quizzes on MOOC lecture viewing. Proceedings of The Third ACM Conference on Learning (pp. 31-40).
• Lee, B. G., Muthoosamy, K., Chiang, C. L., & Ooi, M. C. (2016). Assessing the metacognitive awareness among foundation in engineering students. The IAFOR Journal of Education, 4(2), 48-61.
• Lee, S. C., Irving, K., Pape, S., & Owens, D. (2015). Teachers’ use of interactive technology to enhance students’ metacognition: Awareness of student learning and feedback. Journal of Computers in Mathematics and Science Teaching, 34(2), 175-198.
• Mevarech, Z., & Fridkin, S. (2006). The effects of IMPROVE on mathematical knowledge, mathematical reasoning, and meta-cognition. Metacognition and Learning, 1, 85-97.
• Molin, F., Haelermans, C., Cabus, S., & Groot, W. (2020). The effect of feedback on metacognition - A randomized experiment using polling technology. Computers & Education, 152(2020), 103885.
• Nabilah, C. H., Sesrita, A., & Suherman, I. (2020). Development of learning media based on articulate storyline. Indonesian Journal of Applied Research, 1(2), 80-85.
• Narciss, S. (2012). Feedback strategies. In Seel, N.M. (eds), Encyclopedia of the sciences of learning (pp. 1289-1293). Springer.
• Narciss, S. (2014). Feedback strategies for interactive learning tasks. In M. Spector, M. Merrill, J. Elen, & M. Bishop, Handbook of research on educational communications and technology (pp. 125-144). Springer-Verlag.
• O’Brien, H. L., Cairns, P., & Hall, M. (2018). A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form. International Journal of Human-Computer Studies, 112(2018), 28-39.
• Ostafichuk, P., Nesbit, S., Ellis, N., & Tembrevilla, G. (2020). Developing metacognition in first-year students through interactive online videos. 2020 ASEE Virtual Annual Conference Content Access. doi: 10.18260/1-2--34433
• Paris, S., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), 89-101.
• Pridemore, D. R., & Klein, J. D. (1195). Control of practice and level of feedback in computer-based instruction. Contemporary Educational Psychology, 444-450.
• Schraw, G. (1998). Promoting general metacognitive awareness. Instructional Science, 26(1), 113–125.
• Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460-475.
• Sebille, Y. V., Joksimovic, S., Kovanovic, V., & Mirriahi, N. (2018). Extending video interactions to support self-regulated learning in an online course. 35th International Conference on Innovation, Practice, and Research in the Use of Educational Technologies in Tertiary Education. Geelong.
• Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.
• Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153-189.
• Storyline. (2021). Retrieved from https://articulate.bilgikurdu.net/1.html
• Tanner, K. D. (2012). Promoting student metacognition. CBE—Life Sciences Education, 11(2), 113–120.
• Taub, M., & Azevedo, R. (2018). How does prior knowledge influence eye fixations and sequences of cognitive and metacognitive SRL processes during learning with an intelligent tutoring system? International Journal of Artificial Intelligence in Education, 29(1), 1-28.
• Teo, T., & Lee, C. B. (2012). Assessing the factorial validity of the Metacognitive Awareness Inventory (MAI) in an Asian country: A confirmatory factor analysis. The International Journal of Educational and Psychological Assessment, 92-103.
• Wanga, Z., Gonga, S.-Y., Xua, S., & Hua, X.-E. (2019). Elaborated feedback and learning: Examining cognitive and motivational influences. Computers & Education, 136, 130-140.
• Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future projects. American Educational Research Journal, 45(1), 166-183.