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- Publisher Website: 10.1145/3375462.3375529
- Scopus: eid_2-s2.0-85082388668
- WOS: WOS:000558753800031
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Conference Paper: Learning with Background Music: A Field Experiment
Title | Learning with Background Music: A Field Experiment |
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Authors | |
Keywords | Background music Learning engagement Learning performance Music information retrieval Naturalistic setting |
Issue Date | 2020 |
Publisher | Association for Computing Machinery (ACM). |
Citation | Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK20): Celebrating 10 years of LAK: Shaping the future of the field, virtual Conference, Frankfurt, Germany, 23-27 March 2020, p. 224-229 How to Cite? |
Abstract | Empirical evidence of how background music benefits or hinders learning becomes the crux of optimizing music recommendation in educational settings. This study aims to further probe the underlying mechanism by investigating the interactions among music characteristics, learning context, and learners’ personal factors. 30 participants were recruited to join a field experiment which was conducted in their own study places for one week. During the experiment, participants were asked to search for and listen to music while studying using a novel mobile-based music discovery application. A set of participant-related, context-related, and music-related data were collected via a pre-experiment questionnaire, surveys popped up in the music app, and the logging system of the music app. Preliminary results reveal correlations between certain music characteristics and learners’ task engagement and perceived task performance. This study is expected to provide evidence for understanding the effects of background music on learning, as well as implications for designing music recommendation systems that are capable of intelligently selecting background music for facilitating learning. |
Persistent Identifier | http://hdl.handle.net/10722/288481 |
ISBN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, FJ | - |
dc.contributor.author | Hu, X | - |
dc.contributor.author | Que, Y | - |
dc.date.accessioned | 2020-10-05T12:13:33Z | - |
dc.date.available | 2020-10-05T12:13:33Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Proceedings of the 10th International Conference on Learning Analytics & Knowledge (LAK20): Celebrating 10 years of LAK: Shaping the future of the field, virtual Conference, Frankfurt, Germany, 23-27 March 2020, p. 224-229 | - |
dc.identifier.isbn | 9781450377126 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288481 | - |
dc.description.abstract | Empirical evidence of how background music benefits or hinders learning becomes the crux of optimizing music recommendation in educational settings. This study aims to further probe the underlying mechanism by investigating the interactions among music characteristics, learning context, and learners’ personal factors. 30 participants were recruited to join a field experiment which was conducted in their own study places for one week. During the experiment, participants were asked to search for and listen to music while studying using a novel mobile-based music discovery application. A set of participant-related, context-related, and music-related data were collected via a pre-experiment questionnaire, surveys popped up in the music app, and the logging system of the music app. Preliminary results reveal correlations between certain music characteristics and learners’ task engagement and perceived task performance. This study is expected to provide evidence for understanding the effects of background music on learning, as well as implications for designing music recommendation systems that are capable of intelligently selecting background music for facilitating learning. | - |
dc.language | eng | - |
dc.publisher | Association for Computing Machinery (ACM). | - |
dc.relation.ispartof | Proceedings of the Tenth International Conference on Learning Analytics & Knowledge | - |
dc.subject | Background music | - |
dc.subject | Learning engagement | - |
dc.subject | Learning performance | - |
dc.subject | Music information retrieval | - |
dc.subject | Naturalistic setting | - |
dc.title | Learning with Background Music: A Field Experiment | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Hu, X: xiaoxhu@hku.hk | - |
dc.identifier.authority | Hu, X=rp01711 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/3375462.3375529 | - |
dc.identifier.scopus | eid_2-s2.0-85082388668 | - |
dc.identifier.hkuros | 315745 | - |
dc.identifier.spage | 224 | - |
dc.identifier.epage | 229 | - |
dc.identifier.isi | WOS:000558753800031 | - |
dc.publisher.place | New York, NY, USA | - |