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A Learning Analytics-Based Leaderboard Feedback Approach for Promoting Student Cognitive Engagement and Learning Performance in Online Collaborative Learning

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Title: A Learning Analytics-Based Leaderboard Feedback Approach for Promoting Student Cognitive Engagement and Learning Performance in Online Collaborative Learning
Language: English
Authors: Shuang Yu (ORCID 0009-0007-5780-6389), Junmin Ye, Xinghan Yin, Linjing Wu (ORCID 0000-0003-1820-9665), Shufan Yu (ORCID 0000-0001-6845-0065), Mengting Nan, Sheng Luo
Source: British Journal of Educational Technology. 2026 57(2):579-605.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 27
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Learning Analytics, Learner Engagement, Academic Achievement, Electronic Learning, Cooperative Learning, Gamification, Feedback (Response), Learning Experience
DOI: 10.1111/bjet.70028
ISSN: 0007-1013
1467-8535
Abstract: Cognitive engagement is crucial for achieving positive learning outcomes. However, it is often inadequate in online collaborative learning. While learning analytics feedback can promote learners' engagement, it may have limitations in motivating students to continue participating. As a gamification element, the leaderboard has been shown to boost learning motivation, but its effects in conjunction with learning analytics feedback have not been extensively investigated. This study proposed a learning analytics-based leaderboard feedback approach (LALF) and conducted a quasi-experimental study involving 32 engineering students to assess the impact of this approach on student cognitive engagement and their learning performance. The experimental group received LALF, while the control group only received the learning analytics feedback. Utilizing chi-squared tests, epistemic network analysis (ENA) and auto-recurrence quantification analysis (aRQA), we examined the effects of LALF on the distributions, patterns, and dynamics of cognitive engagement. The results indicated that students in the experimental group exhibited significantly higher high-level cognitive engagement behaviours than those in the control group. Furthermore, students in the experimental group who engaged with the LALF tended to exhibit stronger connections among high-level cognitive engagement behaviours and more stable cognitive engagement patterns than those in the control group. Additionally, the results showed that students in the experimental group achieved higher learning performance than those in the control group. These findings reveal the critical role of combining learning analytics feedback with leaderboards in enhancing cognitive engagement in online collaborative learning, providing important guidance for designing efficient online learning experiences and improving educational quality.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1496236
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Shuang+Yu%22">Shuang Yu</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0007-5780-6389">0009-0007-5780-6389</externalLink>)<br /><searchLink fieldCode="AR" term="%22Junmin+Ye%22">Junmin Ye</searchLink><br /><searchLink fieldCode="AR" term="%22Xinghan+Yin%22">Xinghan Yin</searchLink><br /><searchLink fieldCode="AR" term="%22Linjing+Wu%22">Linjing Wu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-1820-9665">0000-0003-1820-9665</externalLink>)<br /><searchLink fieldCode="AR" term="%22Shufan+Yu%22">Shufan Yu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6845-0065">0000-0001-6845-0065</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mengting+Nan%22">Mengting Nan</searchLink><br /><searchLink fieldCode="AR" term="%22Sheng+Luo%22">Sheng Luo</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22British+Journal+of+Educational+Technology%22"><i>British Journal of Educational Technology</i></searchLink>. 2026 57(2):579-605.
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: <searchLink fieldCode="DE" term="%22Learning+Analytics%22">Learning Analytics</searchLink><br /><searchLink fieldCode="DE" term="%22Learner+Engagement%22">Learner Engagement</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+Learning%22">Electronic Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Gamification%22">Gamification</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+Experience%22">Learning Experience</searchLink>
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  Data: 10.1111/bjet.70028
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  Data: Cognitive engagement is crucial for achieving positive learning outcomes. However, it is often inadequate in online collaborative learning. While learning analytics feedback can promote learners' engagement, it may have limitations in motivating students to continue participating. As a gamification element, the leaderboard has been shown to boost learning motivation, but its effects in conjunction with learning analytics feedback have not been extensively investigated. This study proposed a learning analytics-based leaderboard feedback approach (LALF) and conducted a quasi-experimental study involving 32 engineering students to assess the impact of this approach on student cognitive engagement and their learning performance. The experimental group received LALF, while the control group only received the learning analytics feedback. Utilizing chi-squared tests, epistemic network analysis (ENA) and auto-recurrence quantification analysis (aRQA), we examined the effects of LALF on the distributions, patterns, and dynamics of cognitive engagement. The results indicated that students in the experimental group exhibited significantly higher high-level cognitive engagement behaviours than those in the control group. Furthermore, students in the experimental group who engaged with the LALF tended to exhibit stronger connections among high-level cognitive engagement behaviours and more stable cognitive engagement patterns than those in the control group. Additionally, the results showed that students in the experimental group achieved higher learning performance than those in the control group. These findings reveal the critical role of combining learning analytics feedback with leaderboards in enhancing cognitive engagement in online collaborative learning, providing important guidance for designing efficient online learning experiences and improving educational quality.
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