Abstract
Modelling diversity is especially valuable in soft skills learning, where contextual awareness and understanding of different perspectives are crucial. This paper presents an application of a diversity analytics pipeline to generate domain diversity profiles for learners as captured in their comments while watching videos for learning a soft skill. The datasets for analysis were collected from a series of studies on learning presentation skills with Active Video Watching system (AVW-Space). Two user studies (with 37 postgraduates and 140 undergraduates, respectively) were compared. The learners’ diversity and personal profiles are used to further understand and highlight any notable patterns about their domain coverage on presentation skills.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abolkasim, E., Lau, L., Dimitrova, V.: A semantic-driven model for ranking digital learning objects based on diversity in the user comments. In: Verbert, K., Sharples, M., Klobučar, T. (eds.) EC-TEL 2016. LNCS, vol. 9891, pp. 3–15. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45153-4_1
Abolkasim, E., Lau, L., Dimitrova, V., Mitrovic, A.: Ontology-based domain diversity profiling of user comments. In: Proceedings of the 17th Conference on Artificial Intelligence in Education (2018). (in press)
Dimitrova, V., Mitrovic, A., Piotrkowicz, A., Lau, L., Weerasinghe, A.: Using learning analytics to devise interactive personalised nudges for active video watching. In: Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization. pp. 22–31. ACM (2017)
Hua, K.: Education as Entertainment: YouTube Sensations Teaching The Future. Forbes (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)
Stirling, A.: A general framework for analysing diversity in science, technology and society. J. R. Soc. Interface 4(15), 707–719 (2007)
Acknowledgements
Support by EU-FP7-ICT-257184 ImREAL, Ako Aotearoa and teaching development grant at University of Canterbury. We thank Amali Weerasinghe and Alicja Piotrkowicz for helping with the creation of PreSOn, and the expert trainers from Skills@Library at Leeds University for validating the ontology. Finally, we thank all participants in the user studies.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Abolkasim, E., Lau, L., Dimitrova, V., Mitrovic, A. (2018). Diversity Profiling of Learners to Understand Their Domain Coverage While Watching Videos. In: Pammer-Schindler, V., Pérez-Sanagustín, M., Drachsler, H., Elferink, R., Scheffel, M. (eds) Lifelong Technology-Enhanced Learning. EC-TEL 2018. Lecture Notes in Computer Science(), vol 11082. Springer, Cham. https://doi.org/10.1007/978-3-319-98572-5_45
Download citation
DOI: https://doi.org/10.1007/978-3-319-98572-5_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98571-8
Online ISBN: 978-3-319-98572-5
eBook Packages: Computer ScienceComputer Science (R0)