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- Publisher Website: 10.1145/3448139.3448206
- Scopus: eid_2-s2.0-85103884895
- WOS: WOS:000883342500067
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Conference Paper: Studying with Learners’ Own Music: Preliminary Findings on Concentration and Task Load
Title | Studying with Learners’ Own Music: Preliminary Findings on Concentration and Task Load |
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Authors | |
Issue Date | 2021 |
Publisher | Association for Computing Machinery (ACM). |
Citation | Proceedings of the 11th International Learning Analytics and Knowledge Conference (LAK21), Irvine, CA, USA, 12-16 April 2021, p. 613-619 How to Cite? |
Abstract | Through profiling learners’ music usage in everyday learning settings and depicting their learning experience when studying with a music app powered by a large-scale and real-world music library, this study revealed preliminary observations on how background music impacts learning under varying task load, and manifested intriguing patterns of learners’ music usage and music preferences in various task load conditions. Specifically, we piloted a three-day field experiment in students’ everyday learning environment. During the experiment, participants performed learning tasks with music in the background and completed a set of online surveys before and after each learning session. Our results suggested that learners’ self-selected, real-life background music could enhance their learning effectiveness, while the beneficial effect of background music was more apparent when the learning task was less mentally or temporally demanding. Towards a closer look at the characteristics of preferable music pieces under various task load conditions, our findings showed that music preferred by participants under high versus low temporal demand differs in a number of characteristics, including speechiness, acousticness, danceability, and energy. This study further reveals the effects of background music on learning under varying task load levels and provides implications for context-aware background music selection when designing musically enriched learning environments. |
Persistent Identifier | http://hdl.handle.net/10722/304830 |
ISBN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Li, F | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Ng, TD | - |
dc.contributor.author | Hu, X | - |
dc.date.accessioned | 2021-10-05T02:35:49Z | - |
dc.date.available | 2021-10-05T02:35:49Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Proceedings of the 11th International Learning Analytics and Knowledge Conference (LAK21), Irvine, CA, USA, 12-16 April 2021, p. 613-619 | - |
dc.identifier.isbn | 9781450389358 | - |
dc.identifier.uri | http://hdl.handle.net/10722/304830 | - |
dc.description.abstract | Through profiling learners’ music usage in everyday learning settings and depicting their learning experience when studying with a music app powered by a large-scale and real-world music library, this study revealed preliminary observations on how background music impacts learning under varying task load, and manifested intriguing patterns of learners’ music usage and music preferences in various task load conditions. Specifically, we piloted a three-day field experiment in students’ everyday learning environment. During the experiment, participants performed learning tasks with music in the background and completed a set of online surveys before and after each learning session. Our results suggested that learners’ self-selected, real-life background music could enhance their learning effectiveness, while the beneficial effect of background music was more apparent when the learning task was less mentally or temporally demanding. Towards a closer look at the characteristics of preferable music pieces under various task load conditions, our findings showed that music preferred by participants under high versus low temporal demand differs in a number of characteristics, including speechiness, acousticness, danceability, and energy. This study further reveals the effects of background music on learning under varying task load levels and provides implications for context-aware background music selection when designing musically enriched learning environments. | - |
dc.language | eng | - |
dc.publisher | Association for Computing Machinery (ACM). | - |
dc.relation.ispartof | LAK21: Proceedings of the 11th International Learning Analytics and Knowledge Conference 2021 | - |
dc.title | Studying with Learners’ Own Music: Preliminary Findings on Concentration and Task Load | - |
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 | 10.1145/3448139.3448206 | - |
dc.identifier.scopus | eid_2-s2.0-85103884895 | - |
dc.identifier.hkuros | 326495 | - |
dc.identifier.spage | 613 | - |
dc.identifier.epage | 619 | - |
dc.identifier.isi | WOS:000883342500067 | - |
dc.publisher.place | New York, NY | - |