Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects
Wearable sensor technology is increasingly being integrated into educational settings, offering innovative approaches to enhance teaching and learning experiences. These devices track various physiological and environmental variables, providing valuable insights into student engagement, comprehensio...
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MDPI AG
2025-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/9/2714 |
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| author | Huaqing Hong Ling Dai Xiulin Zheng |
| author_facet | Huaqing Hong Ling Dai Xiulin Zheng |
| author_sort | Huaqing Hong |
| collection | DOAJ |
| description | Wearable sensor technology is increasingly being integrated into educational settings, offering innovative approaches to enhance teaching and learning experiences. These devices track various physiological and environmental variables, providing valuable insights into student engagement, comprehension, and educational environments. However, the extensive and continuous data streams generated by these sensors create significant challenges for learning analytics. This paper presents a comprehensive review of research on learning analytics incorporating wearable technology, systematically identifying methods and approaches that address wearable sensor data challenges. We begin with a systematic review of wearable sensor technologies’ historical development and the current state of sensor data in learning analytics. We then examine multimodal sensor applications in learning analytics and propose research and application trends aligned with educational development needs. Our analysis identifies three key challenges: ethical considerations, explainable learning analytics, and technological and data management issues. The paper concludes by outlining seven future development directions for wearable sensors in educational contexts. |
| format | Article |
| id | doaj-art-3477fa495b2248a3b05365e3d1abbb75 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-3477fa495b2248a3b05365e3d1abbb752025-08-20T02:24:58ZengMDPI AGSensors1424-82202025-04-01259271410.3390/s25092714Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and ProspectsHuaqing Hong0Ling Dai1Xiulin Zheng2Institute of Language Sciences, Shanghai International Studies University, Shanghai 201620, ChinaFaculty of Education, East China Normal University, Shanghai 200061, ChinaDepartment of Special Education and Counselling, The Education University of Hong Kong, Hong Kong 999077, ChinaWearable sensor technology is increasingly being integrated into educational settings, offering innovative approaches to enhance teaching and learning experiences. These devices track various physiological and environmental variables, providing valuable insights into student engagement, comprehension, and educational environments. However, the extensive and continuous data streams generated by these sensors create significant challenges for learning analytics. This paper presents a comprehensive review of research on learning analytics incorporating wearable technology, systematically identifying methods and approaches that address wearable sensor data challenges. We begin with a systematic review of wearable sensor technologies’ historical development and the current state of sensor data in learning analytics. We then examine multimodal sensor applications in learning analytics and propose research and application trends aligned with educational development needs. Our analysis identifies three key challenges: ethical considerations, explainable learning analytics, and technological and data management issues. The paper concludes by outlining seven future development directions for wearable sensors in educational contexts.https://www.mdpi.com/1424-8220/25/9/2714wearable sensorslearning analyticseducational technologyhuman–computer interactionadaptive learning systems |
| spellingShingle | Huaqing Hong Ling Dai Xiulin Zheng Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects Sensors wearable sensors learning analytics educational technology human–computer interaction adaptive learning systems |
| title | Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects |
| title_full | Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects |
| title_fullStr | Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects |
| title_full_unstemmed | Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects |
| title_short | Advances in Wearable Sensors for Learning Analytics: Trends, Challenges, and Prospects |
| title_sort | advances in wearable sensors for learning analytics trends challenges and prospects |
| topic | wearable sensors learning analytics educational technology human–computer interaction adaptive learning systems |
| url | https://www.mdpi.com/1424-8220/25/9/2714 |
| work_keys_str_mv | AT huaqinghong advancesinwearablesensorsforlearninganalyticstrendschallengesandprospects AT lingdai advancesinwearablesensorsforlearninganalyticstrendschallengesandprospects AT xiulinzheng advancesinwearablesensorsforlearninganalyticstrendschallengesandprospects |