Abstract
Although videos are a highly popular digital medium for learning, video watching can be a passive activity and results in limited learning. This calls for interactive means to support engagement and active video watching. However, there is limited insight into what engagement challenges have to be overcome and what intelligent features are needed. This paper presents an empirical way to elicit requirements for innovative functionality to support constructive video-based learning. We present two user studies with an active video watching system instantiated for soft skill learning (pitch presentations). Based on the studies, we identify whether learning is happening and what kind of interaction contributes to learning, what difficulties participants face and how these can be overcome with additional intelligent support. Our findings show that participants who engaged in constructive learning have improved their conceptual understanding of presentation skills, while those who exhibited more passive ways of learning have not improved as much as constructive learners. Analysis of participants’ profiles and experiences led to requirements for intelligent support with active video watching. Based on this, we propose intelligent nudging in the form of signposting and prompts to further promote constructive learning.
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References
Bull, S., Kay, J.: SMILI☺: a framework for interfaces to learning data in open learner models, learning analytics and related fields. Artif. Intell. Educ. 26(1), 293–331 (2016)
Cecez-Kecmanovic, D., Webb, C.: Towards a communicative model of collaborative web-mediated learning. Australas. J. Educ. Technol. 16(1), 73–85 (2000)
Chatti, M.A., Marinov, M., Sabov, O., et al.: Video annotation and analytics in CourseMapper. Smart Learn. Environ. 3(1), 10 (2016)
Chi, M.T., Wylie, R.: The ICAP framework: linking cognitive engagement to active learning outcomes. Educ. Psychol. 49(4), 219–243 (2014)
Conkey, C.A., Bowers, C., Cannon-Bowers, J., Sanchez, A.: Machinima and video-based soft-skills training for frontline healthcare workers. Games Health 2(1), 39–43 (2013)
Cronin, M.W., Cronin, K.A.: Recent empirical studies of the pedagogical effects of interactive video instruction in “soft skill” areas. Comput. High. Educ. 3(2), 53 (1992)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)
Giannakos, M., Sampson, D., Kidziński, Ł.: Introduction to smart learning analytics: foundations and developments in video-based learning. Smart Learn. Environ. 3(1), 1–9 (2016)
Guerra, J., Hosseini, R., Somyurek, S., Brusilovsky, P.: An intelligent interface for learning content: combining an open learner model and social comparison to support self-regulated learning and engagement. In: Proceedings of the 21st International Conference on Intelligent User Interfaces, pp. 152–163 (2016)
Guo, P.J., Kim, J., Rubin, R.: How video production affects student engagement: an empirical study of MOOC videos. In: Proceedings of the 1st ACM Conference Learning at Scale, pp. 41–50 (2014)
Hart, S.G.: NASA-task load index (NASA-TLX); 20 years later. Proc. Hum. Factors Ergon. Soc. Annu. Meet. 50(9), 904–908 (2006). Sage Publications
Kleftodimos, A., Evangelidis, G.: Using open source technologies and open internet resources for building an interactive video based learning environment that supports learning analytics. Smart Learn. Environ. 3(1), 1–23 (2016)
Koedinger, K.R., Kim, J., Jia, Z., McLaughlin, E., Bier, N.: Learning is not a spectator sport: doing is better than watching for learning from a MOOC learning at scale. In: Proceedings of the 2nd ACM Conference Learning @ Scale, pp. 111–120 (2015)
Kovacs, G.: Effects of in-video quizzes on MOOC lecture viewing. In: Proceedings of the 3rd Learning @ Scale, pp. 31–40 (2016)
Kurtz, G., Tsimerman, A., Steiner-Lavi, O.: The flipped-classroom approach: the answer to future learning? Eur. J. Open Distance E-learn. 17(2), 172–182 (2014)
Lau, L., Mitrovic, A., Weerasinghe, A., Dimitrova, V.: Usability of an active video watching system for soft skills training. In: Proceedings of the 1st International Workshop on Intelligent Mentoring Systems, ITS 2016, Zagreb (2016)
Long, Y., Aleven, V.: Enhancing learning outcomes through self-regulated learning support with an Open Learner Model. User Model. User-Adapt. Interact. 27(1), 55–88 (2017)
Mitrovic, A., Dimitrova, V., Weerasinghe, A., Lau, L.: Reflexive experiential learning using active video watching for soft skills training. In: Chen, W., et al. (eds.) Proceedings of the 24th International Conference on Computers in Education, Mumbai, pp. 192–201, 28 November–2 December 2016. APSCE (2016)
Morgan, G., Adams, J.: Pedagogy first: making web-technologies work for soft skills development in leadership and management education. Interact. Learn. Res. 20(2), 129–155 (2009)
Pardo, A., Mirriahi, N., Dawson, S., Zhao, Y., Zhao, A., Gašević, D.: Identifying learning strategies associated with active use of video annotation software. In: Proceedings of the 5th International Conference on Learning Analytics and Knowledge, pp. 255–259. ACM (2015)
Pintrich, P.R., De Groot, E.V.: Motivational and self-regulated learning components of classroom academic performance. J. Educ. Psychol. 82(1), 33 (1990)
Thakker, D., Dimitrova, V., Lau, L., Yang-Turner, F., Despotakis, D.: Assisting user browsing over linked data: requirements elicitation with a user study. In: Daniel, F., Dolog, P., Li, Q. (eds.) ICWE 2013. LNCS, vol. 7977, pp. 376–383. Springer, Heidelberg (2013). doi:10.1007/978-3-642-39200-9_31
Vieira, I., Lopes, A.P., Soares, F.: The potential benefits of using videos in higher education. In: Proceedings of the EDULEARN14 Conference, pp. 0750–0756. IATED Publications (2014)
Wachtler, J., Hubmann, M., Zöhrer, H., Ebner, M.: An analysis of the use and effect of questions in interactive learning-videos. Smart Learn. Environ. 3(1), 13 (2016)
Wang, X., Wen, M., Rosé, C.P.: Towards triggering higher-order thinking behaviors in MOOCs. In: Proceedings of the 6th International Conference Learning Analytics & Knowledge, pp. 398–407. ACM (2016)
World Economic Forum Report: What are the 21st-century skills every student needs? (2016). https://www.weforum.org/agenda/2016/03/21st-century-skills-future-jobs-students
Yousef, A.M.F., Chatti, M.A., Schroeder, U.: The state of video-based learning: a review and future perspectives. Int. J. Adv. Life Sci. 6(3/4), 122–135 (2014)
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This research was supported by the EU-FP7-ICT-257184 ImREAL grant, a teaching development grant from the University of Canterbury, and a regional grant from Ako Aotearoa.
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Mitrovic, A., Dimitrova, V., Lau, L., Weerasinghe, A., Mathews, M. (2017). Supporting Constructive Video-Based Learning: Requirements Elicitation from Exploratory Studies. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_19
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