Effects of intelligent feedback on online learners' engagement and cognitive load: The case of research ethics education
Abstract
The current study developed an intelligent learning environment for online education of research ethics and investigated how encouragement and warning intelligent feedback influenced learners’ engagement (behavioural, emotional, and cognitive) and cognitive load (mental load and mental effort). Participants included 191 graduate students in Taiwan who were randomly assigned into four groups: a non-feedback group, a warning feedback group, an encouragement feedback group, and an encouragement plus warning feedback group. The intelligent feedback was established on the basis of learning analytics from a database of prior learners’ online learning of off- or on-task behaviours. The system detected students’ sequential behavioural patterns and provided instant intelligent feedback. The results showed that encouragement plus warning feedback caused higher emotional and cognitive engagement, whereas warning feedback led to higher mental load. The study suggests that when designing intelligent learning environments, encouragement, and warning intelligent feedback should be used jointly to enhance the appeal of the learning journey and to boost emotional engagement, thereby increasing students’ willingness to learn. It is important to avoid using only warning feedback to reduce interference in learning.
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LA-based feedback underpinned by survey data can affect student cognitive load, community of inquiry, reflective thinking skills, motivation, transactional distance, and engagement.
“Reviewed publications revealed that LA-based feedback underpinned by survey data can affect student cognitive load (Sun et al., 2019; Zheng et al., 2021), the community of inquiry, reflective thinking skills (Yilmaz, 2020), motivation, and transactional distance (Yilmaz & Yilmaz, 2020), and engagement (Sun et al., 2019; Yilmaz & Yilmaz, 2021, pp. 1 -12).”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Sun et al., 2019
LA services increase students' motivation for learning engagement.
“increase their motivation for learning engagement (e.g. Lewis et al., 2021; Sun et al., 2019)”
From A systematic review of the role of learning analytics in enhancing feedback practices in higher education (2022) · cites this paper as Sun et al., 2019
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Banihashem, S. K., Noroozi, O., van Ginkel, S., Macfadyen, L. P., & Biemans, H. J. A. (2022) · Educational Research Review · doi:10.1016/j.edurev.2022.100489 · Cited by 246 · see citing works
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- Authors
- Sun, J. C.-Y., Yu, S.-J., & Chao, C.-H.
- Affiliations
- National Yang Ming Chiao Tung University (TW)
- Corresponding author
- Sun, Jerry Chih-Yuan
- Venue
- Educational Psychology
- Publisher
- Informa UK Limited
- Published
- 2018-11-14
- Volume
- 39
- Issue
- 10
- Pages
- 1293-1310
- ISSN
- 0144-3410 (ISSN-L)
- 1469-5820
- OpenAlex
- W2900654385
- Cited by
- 49
- References
- 48
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 6 · 2023: 9 · 2022: 9 · 2021: 4 · 2020: 2 · 2019: 2
- FWCI
- 1.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational Psychology (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Online and Blended Learning
- Keywords
- intelligent feedback, online learning, student engagement, cognitive load, research ethics training, emotional engagement, mental workload, cognitive effort, learning analytics, behavioral patterns, smart learning environments, graduate students
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