A learning analytics-based leaderboard feedback approach for promoting student cognitive engagement and learning performance in online collaborative learning

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.

Practitioner notes

What is already known about this topic?

• Cognitive engagement is essential for achieving positive learning outcomes, particularly in online collaborative learning environments.
• Learning analytics feedback can enhance learner engagement, but may lack elements that stimulate motivation among students.
• The leaderboard is considered a gamification element, potentially boosting learning motivation by fostering a competitive atmosphere.

What this paper adds?

• This study introduces a learning analytics-based leaderboard feedback approach (LALF), which combines learning analytics feedback and leaderboards.
• It provides empirical evidence from a quasi-experimental design involving 32 engineering students, indicating that students who engaged with the LALF demonstrated higher levels of cognitive engagement behaviours compared to those who only received traditional learning analytics feedback.
• The study employs various analytical methods, including chi-squared tests, epistemic network analysis (ENA) and automated recurrence quantification analysis (aRQA), to explore the distributions, patterns and dynamics of cognitive engagement associated with the LALF.

Implications for practice and policy

• Educators may want to consider integrating leaderboards with learning analytics feedback to foster a competitive yet supportive online learning environment that has the potential to enhance cognitive engagement.
• The study highlights the importance of using diverse analytical methods such as ENA and aRQA. Researchers may consider employing these methods to gain deeper insights into student engagement patterns and the efficacy of different instructional strategies.
• Institutions could consider offering professional development programs focused on the effective use of learning analytics and various analytical methods. Training educators on how to interpret and apply these analyses can enhance their instructional strategies and improve student engagement.