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Tackling Learning Obstacles in Learning Videos by Thematic Ad-Hoc Recommendations

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Towards a Hybrid, Flexible and Socially Engaged Higher Education (ICL 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 899))

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Abstract

Learning videos enjoy great popularity in a digitalized world, especially since their use is usually possible regardless of time and location. Learners use this advantage mainly in self-study. Supervision, as for example in classroom teaching, is rather difficult and learners are usually left to their own devices when learning obstacles arise. However, not treating learning obstacles can have serious consequences, ranging from a gradual loss of the learners’ motivation to the termination of the learning project. Consequently, learning obstacles must be identified and treated in order to support an efficient learning process. Fortunately, a digital learning environment opens up many opportunities to support learners automatically. This paper explains an approach to identify potential learning obstacles in video learning based on indirect feedback. The first part of the approach to removing learning obstacles in learning videos is based on an analysis of learners’ click interaction within a video to identify potential problem areas. Building on this, the second part provides first thematically relevant ad hoc video recommendations for the potentially identified learning obstacle. In order to verify whether there is actually a learning obstacle, the third part explicitly induces learners to give indirect or direct feedback on whether the recommendations have helped them and, consequently, whether they have removed an actual learning obstacle.

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Correspondence to Alexander Lehmann .

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Lehmann, A., Landes, D. (2024). Tackling Learning Obstacles in Learning Videos by Thematic Ad-Hoc Recommendations. In: Auer, M.E., Cukierman, U.R., Vendrell Vidal, E., Tovar Caro, E. (eds) Towards a Hybrid, Flexible and Socially Engaged Higher Education. ICL 2023. Lecture Notes in Networks and Systems, vol 899. Springer, Cham. https://doi.org/10.1007/978-3-031-51979-6_49

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