TY - GEN
T1 - Leveraging Learning Analytics Dashboards for Monitoring Student Learning
T2 - 14th International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2025
AU - Xin, Luo
AU - Wan, Han
AU - Yue, Shiyang
AU - Lu, Jing
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - In blended learning, the learning management system (LMS) records various data related to learning behavior. In most cases, the data extracted from LMS can be used to integrate a learning analytics dashboard (LAD). However, current research focuses more on LAD design and less on the quantitative analysis of the impact of user behavior. To fill this void, the study aims to reveal the correlation between viewing frequency of LAD and learning engagement. In this research, we conducted a learning behavior-based pedagogical intervention for a course in the fall of 2024 and delivered LAD to 325 undergraduates. During the intervention period, the course platform updated the dashboard every week based on the latest learning behavior data, and the data were analyzed based on propensity score matching (PSM). The findings showed that the viewing frequency is positively related to learning engagement. Additionally, the view frequency is independent of the two dashboard interfaces we proposed.
AB - In blended learning, the learning management system (LMS) records various data related to learning behavior. In most cases, the data extracted from LMS can be used to integrate a learning analytics dashboard (LAD). However, current research focuses more on LAD design and less on the quantitative analysis of the impact of user behavior. To fill this void, the study aims to reveal the correlation between viewing frequency of LAD and learning engagement. In this research, we conducted a learning behavior-based pedagogical intervention for a course in the fall of 2024 and delivered LAD to 325 undergraduates. During the intervention period, the course platform updated the dashboard every week based on the latest learning behavior data, and the data were analyzed based on propensity score matching (PSM). The findings showed that the viewing frequency is positively related to learning engagement. Additionally, the view frequency is independent of the two dashboard interfaces we proposed.
KW - blended learning
KW - data mining
KW - learning analytics dashboards
KW - learning management system
KW - pedagogical intervention
UR - https://www.scopus.com/pages/publications/105033222103
U2 - 10.1109/TALE66047.2025.11346753
DO - 10.1109/TALE66047.2025.11346753
M3 - 会议稿件
AN - SCOPUS:105033222103
T3 - TALE 2025 - 2025 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Proceedings
BT - TALE 2025 - 2025 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 4 December 2025 through 7 December 2025
ER -