Continuously analysing fine-grained student behaviours in an online collaborative learning environment - Shum, Kam Hong; Wah Chu, Samuel Kai; Yeung, Cheuk Yu (Interactive learning environments, 2023)
This study examines the use of data analytics to evaluate students' behaviours during their participation in an online collaborative learning environment called SkyApp. To visualise the learning traits of engagement, emotion and motivation, students' inputs and activity data were captured and quantified for analysis. Experiments were first carried out in a primary school with 66 fifth-grade students. Each participating student collaborated with other group members using SkyApp through a personal computer in a classroom setting. While the students collaboratively solved mathematics questions in two quizzes, data about their learning traits were captured by SkyApp; various patterns of these data were then analysed. The findings based on the data analysis were triangulated with the results of questionnaires, revealing the relationship between student behaviours and collaborative learning as a kind of pedagogical intervention. The correlation between the data from the two approaches - data analytics and questionnaires - shows the potential of understanding students' behaviours through continuous data analysis of learner-produced data without the need to collect self-reported data from the students involved. This study demonstrates that teachers can monitor and identify the effects of specific pedagogical interventions on students' behaviours by looking at different snapshots taken over the course of e-learning activities.