Abstract
Learning through video watching has been popular through the education community and is considered as a common choice especially for self-directed informal learning. However, the learner in this situation acts only as a passive consumer and does not receives any feedback for improving his/her performance, an element important in any educational context. Studies in music psychology reveal that gender, perceptual, and cognitive, differences, along with the level of music education of the individual, should be considered when support is generated to a person who is watching a music video for educational purposes. In this sense, individual differences should be exploited when designing an adaptive learning support aiming to suit the individual in music learning. In this line, this paper presents an exploratory study into interaction data of music experts and amateurs when they were actively watching a music video. Linguistic analysis is also employed for taking an insight into the written comments provided by participants at several timepoints in the music videos. Results reveal significant differences between genders in their interaction behavior but also in their perception processing of the music videos, reflected in their comments. Suggestions are provided based on the results on how these can be utilized for the design of personalized support in informal music education.
Original language | English |
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Title of host publication | UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization |
Publisher | Association for Computing Machinery, Inc |
Pages | 241-246 |
Number of pages | 6 |
ISBN (Electronic) | 9781450350679 |
DOIs | |
Publication status | Published - 9 Jul 2017 |
Event | 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 - Bratislava, Slovakia Duration: 9 Jul 2017 → 12 Jul 2017 |
Other
Other | 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 |
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Country/Territory | Slovakia |
City | Bratislava |
Period | 9/07/17 → 12/07/17 |
Keywords
- Analytics
- Individual characteristics: personalization