Abstract
The use of instructional videos is rampant in education; however, their interaction is limited by weak instructional design. Gagne has never insisted on using his renowned 9 Events of Instruction slavishly in situations as a viable paradigm for utilization in video design. Connecting grade level, video length, and interaction, this study seeks to determine the relevance of Gagne’s prescribed 9 event sequence in instructional mathematics videos. We scrutinized 50 instructional mathematics videos on YouTube geared towards middle school pupils ranging between 5th and 8th grades. We used quantitative media content analysis for video analysis. In data analysis, partial least squares were used. Bayesian estimation was also resorted to for cross checking. The data revealed that one-third of Gagne’s instructional design steps were not always present: activating prior knowledge, eliciting performance, and finally providing feedback. A mediation analysis between grade level and video length revealed that 6 events fully mediated the association between the two. We also elicited the impact of these variables on affective and behavioral interactions in videos. This study assists in creating an idiosyncratic instructional design model, called Birgili’s 8 steps for instructional video design, and in infusing this with a melange of four theories. In contrast with the status quo attesting that the literature abounds with scholarly works touting “the shorter is the better” mantra, the results substantiated that longer may be better in leveraging video interactions provided that the length is judiciously used to conform to instructional design principles.
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References
Afify, M. K. (2020). Effect of interactive video length within e-learning environments on cognitive load, cognitive achievement and retention of learning. Turkish Online Journal of Distance Education, 21(4), 68–89. https://doi.org/10.17718/tojde.803360
Al-Naabi, I. S. (2020). Is it worth flipping? The impact of flipped classrooms on efl students’ grammar. English Language Teaching, 13(6), 64–75. https://doi.org/10.5539/elt.v13n6p64
Alwin, D. F., & Hauser, R. M. (1975). The decomposition of effects in path analysis. American Sociological Review, 40, 37–47. https://doi.org/10.2307/2094445
Andrade, E. B. (2005). Behavioral consequences of affect: Combining evaluative and regulatory mechanisms. Journal of Consumer Research, 32(3), 355–362. https://doi.org/10.1086/497546
Bennett, S., & Oliver, M. (2011). Talking back to theory: The missed opportunities in learning technology research. Research in Learning Technology, 19(3), 179–189. https://doi.org/10.3402/rlt.v19i3.17108
Bernard, R. M., Abrami, P. C., Borokhovski, E., Wade, C. A., Tamim, R. M., Surkes, M. A., & Bethel, E. C. (2009). A meta-analysis of three types of interaction treatments in distance education. Review of Educational Research, 79(3), 1243–1289. https://doi.org/10.3102/2F0034654309333844
Bloom, B. S. (1973). Recent developments in mastery learning. Educational Psychologist, 10(2), 53–57. https://doi.org/10.1080/00461527309529091
Bollen, K. A., & Ting, K. F. (2000). A tetrad test for causal indicators. Psychological Methods, 5(1), 3–22. https://doi.org/10.1037/1082-989X.5.1.3
Cain, M. K., & Zhang, Z. (2019). Fit for a Bayesian: An evaluation of PPP and DIC for structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 26(1), 39–50. https://doi.org/10.1080/10705511.2018.1490648
Cevikbas, M., & Kaiser, G. (2022). Student engagement in a flipped secondary mathematics classroom. International Journal of Science and Mathematics Education, 20, 1455–1480. https://doi.org/10.1007/s10763-021-10213-x
Cheung, L. (2016). Using an instructional design model to teach medical procedures. Medical Science Educator, 26, 175–180. https://doi.org/10.1007/s40670-016-0228-9
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Erlbaum Press.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety: Experiencing flow in work and play. Jossey-Bass Press.
de Araujo, Z., Otten, S., & Birisci, S. (2017). Teacher-created videos in a flipped mathematics class: Digital curriculum materials or lesson enactments? ZDM-Mathematics Education, 49(5), 687–699. https://doi.org/10.1007/s11858-017-0872-6
Derry, S. J. (1996). Cognitive schema theory in the constructivist debate. Educational Psychologist, 31(3/4), 163–174. https://doi.org/10.1080/00461520.1996.9653264
Duffy, M. C., & Azevedo, R. (2015). Motivation matters: Interactions between achievement goals and agent scaffolding for self-regulated learning within an intelligent tutoring system. Computers in Human Behavior, 52, 338–348. https://doi.org/10.1016/j.chb.2015.05.041
Elkind, D. (2009). Child development in educational settings. Educational Psychologist, 12(1), 49–58. https://doi.org/10.1080/00461527609529155
Fidan, M. (2023). The effects of microlearning-supported flipped classroom on pre-service teachers’ learning performance, motivation and engagement. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11639-2. Advance online publication.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Fraenkel, J. R., Wallen, N. E., & Hyun, H. N. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill Press.
Gagne, R. M. (1965). The conditions of learning. Holt, Rinehart & Winston Press.
Gagne, R. M., Wager, W., & Rojas, A. (1981). Planning and authoring computer-assisted instruction lessons. Educational Technology, 21(9), 17–26. http://www.jstor.org/stable/44422635
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 91–109. https://doi.org/10.17705/1CAIS.01605
Geisser, S. (1974). A predictive approach to the random effects model. Biometrika, 61(1), 101–107. https://doi.org/10.2307/2334290
Ghilay, Y. (2021). Text-based video: The effectiveness of learning math in higher education through videos and texts. Journal of Education and Learning, 10(3), 55–63. https://doi.org/10.5539/jel.v10n3p55
Ginsburg, H. P., & Opper, S. (1988). Piaget’s theory of intellectual development (3rd ed.). International Psychotherapy Institute Press.
Gudergan, S. P., Ringle, C. M., Wende, S., & Will, A. (2008). Confirmatory tetrad analysis in PLS path modeling. Journal of Business Research, 61(12), 1238–1249. https://psycnet.apa.org/doi/10.1016/j.jbusres.2008.01.012
Guo, P. J., Kim, J., & Rubin, R. (2014). How video production affects student engagement: An empirical study of MOOC videos [Paper Presentation]. Proceedings of the First ACM Conference on Learning at Scale (pp. 41–50), Atlanta, Georgia, USA. https://doi.org/10.1145/2556325.2566239
Gurcan, F., & Cagiltay, N. E. (2023). Research trends on distance learning: A text mining-based literature review from 2008 to 2018. Interactive Learning Environments, 31(2), 1007–1028. https://doi.org/10.1080/10494820.2020.1815795
Hair, J. F., Jr., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017b). PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123. https://doi.org/10.1504/IJMDA.2017.087624
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017a). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd Ed.). Sage Press.
Hardy, G. H. (1940). A mathematician’s apology. Cambridge University Press.
Hoyle, R. H., & Kenny, D. A. (1999). Statistical power and tests of mediation. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 195–222). Sage Press.
Hricko, M. (2008). Gagne’s nine events of instruction. Encyclopedia of Information Technology Curriculum Integration (pp. 353–356). IGI Global Press. https://doi.org/10.4018/978-1-59904-881-9.ch058
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Ilie, M. D. (2014). An adaption of Gagné’s instructional model to increase the teaching effectiveness in the classroom: The impact in Romanian Universities. Educational Technology Research and Development, 62(6), 767–794. http://www.jstor.org/stable/24546611
Jacobson, B. P., Dorneich, M. C., & Potter, L. A. (2018). Impact of lecture video acceleration in a flipped introductory engineering course. The International Journal of Engineering Education, 34(6), 1863–1875.
Jahnke, I., Lee, Y. M., Pham, M., He, H., & Austin, L. (2019). Unpacking the inherent design principles of mobile microlearning. Technology, Knowledge and Learning, 25(3), 585–619. https://doi.org/10.1007/s10758-019-09413-w
Jeong, A. (2019). Comparing instructional event sequences in audio podcasts with low versus high user satisfaction. TechTrends, 63(5), 559–563. https://doi.org/10.1007/s11528-018-0369-3
Jia, C., Hew, K. F., Jiahui, D., & Liuyufeng, L. (2023). Towards a fully online flipped classroom model to support student learning outcomes and engagement: A 2-year design-based study. The Internet and Higher Education, 56, e100878. https://doi.org/10.1016/j.iheduc.2022.100878
Karaoglan-Yilmaz, F. G., & Durak, H. (2018). Examining pre-service teachers’ opinions about digital story design. Education and Information Technologies, 23, 1277–1295. https://doi.org/10.1007/s10639-017-9666-2
Karras, O., Schneider, K., & Fricker, S. A. (2020). Representing software project vision by means of video: a quality model for vision videos. Journal of Systems and Software, 162, e110479.
Keller, J. M. (1983). Motivational design of instruction. In C. M. Reigeluth (Ed.), Instructional design theories and models: An overview of their current status (pp. 383–434). Erlbaum Press.
Kenny, D. A. (2021). Mediation. Retrieved July 2, 2023, from https://davidakenny.net/cm/mediate.htm#COMP
Krippendorff, K. (2004). Content analysis: An introduction to its methodology. SAGE Press.
Lagerstrom, L., Johanes, P., & Ponsukcharoen, U. (2015, June 14–17). The myth of the six-minute rule: Student engagement with online videos [Paper Presentation]. In 2015 ASEE Annual Conference & Exposition (pp. 26–1558), Seattle, WA, USA.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2F2529310
Lee, S. Y., & Song, X. Y. (2004). Evaluation of the Bayesian and maximum likelihood approaches in analyzing structural equation models with small sample sizes. Multivariate Behavioral Research, 39, 653–686. https://doi.org/10.1207/s15327906mbr3904_4
Leetaru, K. (2019). Social media has taught us to talk rather than listen. Forbes. Retrieved July 2, 2023, from https://www.forbes.com/sites/kalevleetaru/2019/04/23/social-media-has-taught-us-to-talk-rather-than-listen/?sh=5256381355c0
Leow, F. T., & Neo, M. (2015). Collaborative learning with Web 2.0 tools: Analysing Malaysian students’ perceptions and peer interaction. Educational Media International, 52(4), 308–327. https://doi.org/10.1080/09523987.2015.1100392
Lin, Y. C., Liu, T. C., & Sweller, J. (2015). Improving the frame design of computer simulations for learning: Determining the primacy of the isolated elements or the transient information effects. Computers & Education, 88, 280–291. https://doi.org/10.1016/j.compedu.2015.06.001
Lo, C. K., & Hew, K. F. (2016). A comparison of video production styles in mathematics flipped classroom: Examining students’ preferences. In C. K. Looi, J. L. Polman, U. Cress, & P. Reimann (Eds.), Proceedings of the 12th international conference of the learning sciences (Vol. 2, pp. 1282–1285). International Society of the Learning Sciences.
Lo, C. K., Cheung, K. L., Chan, H. R., & Chau, C. L. E. (2021). Developing flipped learning resources to support secondary school mathematics teaching during the COVID-19 pandemic. Interactive Learning Environments. https://doi.org/10.1080/10494820.2021.1981397. Advance Online Publication.
Lo, C. K., & Hew, K. F. (2017). A critical review of flipped classroom challenges in K-12 education: Possible solutions and recommendations for future research. Research and Practice in Technology Enhanced Learning, 12(1). https://doi.org/10.1186/s41039-016-0044-2
Manasrah, A., Masoud, M., & Jaradat, Y. (2021). Short videos, or long Videos? A study on the ideal video length in online learning [Paper presentation]. In 2021 International Conference on Information Technology (ICIT) (pp. 366–370), Amman, Jordan. IEEE Press. https://doi.org/10.1109/ICIT52682.2021.9491115
Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139.
McNeill, L., & Fitch, D. (2022). Microlearning through the lens of Gagne’s nine events of instruction: A qualitative study. TechTrends. https://doi.org/10.1007/s11528-022-00805-x. Advance Online Publication.
Ministry of National Education [MoNE]. (2018). Mathematics curriculum (primary and middle school 1,2,3,4,5,6,7 and 8th grades). http://mufredat.meb.gov.tr/Dosyalar/201813017165445-MATEMATİK%20ÖĞRETİM%20PROGRAMI%202018v.pdf
Moore, M. G. (1989). Three types of interaction (Editorial). American Journal of Distance Education, 3(2), 1–7. https://doi.org/10.1080/08923648909526659
National Council of Teachers of Mathematics [NCTM]. (2021). Continuing the journey: Mathematics learning 2021 and beyond. Retrieved July 2, 2023, from https://www.nctm.org/uploadedFiles/Research_and_Advocacy/collections/Continuing_the_Journey/NCTM_NCSM_Continuing_the_Journey_Report-Fnl2.pdf
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill Press.
Park, M., & Kim, Y. (2023). Instructional quality of two beginning mathematics teachers for three years: What professional competency makes a difference? Educational Studies in Mathematics, 112, 505–529. https://doi.org/10.1007/s10649-022-10195-9
Piaget, J. (1952). The origins of intelligence in children. Norton & Company Press.
Ramma, Y., Bholoa, A., & Watts, M. (2020). Guided discovery—Robert Gagné. In B. Akpan & T. J. Kennedy (Eds.), Science education in theory and practice (pp. 191–208). Springer Press. https://doi.org/10.1007/978-3-030-43620-9_14
Raubenheimer, J. E. (2004). An item selection procedure to maximize scale reliability and validity. South African Journal of Industrial Psychology, 30(4), 59–64. https://doi.org/10.4102/sajip.v30i4.168
Renner, J., Stafford, D., Lawson, A., McKinnon, J., Friot, E., & Kellogg, D. (1976). Research, teaching, and learning with the Piaget model. University of Oklahoma Press.
Ringle, C. M., Wende, S., & Becker, J. M. (2015). SmartPLS 3. Retrieved July 2, 2023, from http://www.smartpls.com
Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., & Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies! Journal of Business Research, 69(10), 3998–4010. https://doi.org/10.1016/j.jbusres.2016.06.007
Saurabh, S., & Gautam, S. (2019). Modelling and statistical analysis of YouTube’s educational videos: A channel Owner’s perspective. Computers & Education, 128, 145–158. https://doi.org/10.1016/j.compedu.2018.09.003
Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Evaluating the predictive performance of PLS models. Journal of Business Research, 69(10), 4552–4564. https://doi.org/10.1016/j.jbusres.2016.03.049
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189
Shoufan, A. (2019). Estimating the cognitive value of YouTube’s educational videos: A learning analytics approach. Computers in Human Behavior, 92, 450–458. https://doi.org/10.1016/j.chb.2018.03.036
Slemmons, K., Anyanwu, K., Hames, J., Grabski, D., Mlsna, J., Simkins, E., & Cook, P. (2018). The impact of video length on learning in a middle-level flipped science setting: Implications for diversity inclusion. Journal of Science Education and Technology, 27(5), 469–479. https://doi.org/10.1007/s10956-018-9736-2
Smith, M., & Stein, M. K. (2018). 5 practices for orchestrating productive mathematics discussions (2nd ed.). NCTM Press.
Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–147. https://www.jstor.org/stable/2984809.
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12, 257–285. https://doi.org/10.1207/s15516709cog1202_4
Sweller, J. (2010). Cognitive load theory: Recent theoretical advances. In J. L. Plass, R. Moreno, & R. Brünken (Eds.), Cognitive load theory (pp. 29–47). Cambridge University Press. https://doi.org/10.1017/CBO9780511844744.004
Tambi, R., Bayoumi, R., Lansberg, P., & Banerjee, Y. (2018). Blending Gagne’s instructional model with Peyton’s approach to design an introductory bioinformatics lesson plan for medical students: Proof-of-concept study. JMIR Medical Education, 4(2), e11122. https://doi.org/10.2196/11122
Tolentino, C. L. (2016). Content analysis of Teachertube and Youtube videos for instructing English language learners [Doctoral dissertation, University of Hawaii]. ProQuest.
Torrington, J., & Bower, M. (2021). Teacher-created video instruction in the elementary classroom: Its impact on students and teachers. Journal of Computer Assisted Learning, 37(4), 1107–1126. https://doi.org/10.1111/jcal.12549
Trautz, T. (2022). Feel, behave, think: the pathway to human decision making. Maru Group Press.
Uğraş, G., Uzun, A. M., Battal, A., & Kayaduman, H. (2016). An examination of instructional high school chemistry videos on eba portal in terms of nine events of instruction. Participatory Educational Research, 3(1), 66–78. https://doi.org/10.17275/per.16.04.3.1
Van de Schoot, R., Kaplan, D., Denissen, J., Asendorpf, J. B., Neyer, F. J., & Van Aken, M. A. (2014). A gentle introduction to Bayesian analysis: Applications to developmental research. Child Development, 85(3), 842–860. https://doi.org/10.1111/cdev.12169
Weinberg, A., & Martin, J. (2020). Creating and using videos for teaching math suggestions from the field. MAA Focus. Retrieved July 2, 2023, from https://calcvids.org/publications/ARTICLE_creating%20videos_revised.pdf
Wold, H. O. A. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog, & H. O. A. Wold (Eds.), Systems under indirect observations (Part II, pp. 1–54). North-Holland Press.
Wong, A., Leahy, W., Marcus, N., & Sweller, J. (2012). Cognitive load theory, the transient information effect and e-learning. Learning and Instruction, 22(6), 449–457. https://doi.org/10.1016/j.learninstruc.2012.05.004
Yu, Z., & Gao, M. (2022). Effects of video length on a flipped English classroom. SAGE Open, 12(1), 1–14. https://doi.org/10.1177/21582440211068474
Zainuddin, Z., Zhang, Y., Li, X., Chu, S. K. W., Idris, S., & Keumala, C. M. (2019). Research trends in flipped classroom empirical evidence from 2017 to 2018: A content analysis. Interactive Technology and Smart Education, 16(3), 255–277. https://doi.org/10.1108/ITSE-10-2018-0082
Acknowledgements
We are obliged to Sinem DOĞAN, a junior teacher candidate in the department of Elementary Mathematics Education, the conqueror of Gagne’s all steps, and Gizem ÖZTEMÜR (PhD candidate in the department of Guidance and Psychological Counseling), the savior of Piaget’s stages of cognitive development, for their precious assistance in the preparation of the manuscript.
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Demir, Ö., Birgili, B. The mediating role of instructional design and video length between grade level and pupil-content interaction in instructional mathematics videos on YouTube. Educ Inf Technol 29, 5599–5629 (2024). https://doi.org/10.1007/s10639-023-12004-z
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DOI: https://doi.org/10.1007/s10639-023-12004-z