Effects of a learning analytics‐based real‐time feedback approach on knowledge elaboration, knowledge convergence, interactive relationships and group performance in CSCL

Abstract

AbstractLearning analytics (LA) has been widely adopted in research on education. However, most studies in the area have conducted LA after computer‐supported collaborative learning (CSCL) activities rather than during CSCL. To address this problem, this study proposed a LA‐based real‐time feedback approach based on a deep neural network model to improve CSCL performance. In total, 72 university students participated in the study and were randomly assigned to an experimental or control group. The students in the experimental group learned with the LA‐based real‐time feedback approach, whereas the students in the control group learned with the conventional online collaborative learning approach. To analyse the data, both quantitative and qualitative methods were adopted. The results indicated that the LA‐based real‐time feedback approach significantly promoted knowledge convergence, knowledge elaboration, interactive relationships and group performance. The interview results also confirmed the effectiveness of the proposed approach. Practitioner notesWhat is already known regarding this topic Learning analytics (LA) has been widely used in education. Most studies in the area have presented LA results only after collaborative learning and have lacked real‐time analysis and feedback. What this paper adds A LA‐based real‐time feedback approach was proposed and validated in the computer‐supported collaborative learning (CSCL) context. The experimental results indicated that the LA‐based real‐time feedback approach significantly promoted knowledge elaboration, knowledge convergence, interactive relationships and group performance. Implications for practice and/or policy To shed light on progress in CSCL, real‐time LA are recommended. Deep neural network models, such as bidirectional encoder representations from transformers, can be adopted to automatically analyse online discussion transcripts. Real‐time feedback based on LA results can promote CSCL performance.