The Impact of Dashboard Feedback Type on Learning Effectiveness, Focusing on Learner Differences

Author:

Wang Han1,Huang Tao1,Zhao Yuan12,Hu Shengze1

Affiliation:

1. Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China

2. Faculty of Education, Jiujiang University, Jiujiang 332005, China

Abstract

With the exponential growth of educational data, increasing attention has been given to student learning supported by learning analytics dashboards. Related research has indicated that dashboards relying on descriptive analytics are deficient compared to more advanced analytics. However, there is a lack of empirical data to demonstrate the performance and differences between different types of analytics in dashboards. To investigate these, the study used a controlled, between-groups experimental method to compare the effects of descriptive and prescriptive dashboards on learning outcomes. Based on the learning analytics results, the descriptive dashboard describes the learning state and the prescriptive dashboard provides suggestions for learning paths. The results show that both descriptive and prescriptive dashboards can effectively promote students’ cognitive development. The advantage of prescriptive dashboard over descriptive dashboard is its promotion in learners’ learning strategies. In addition, learners’ prior knowledge and learning strategies determine the extent of the impact of dashboard feedback on learning outcomes.

Funder

National Natural Science Foundation of China

State Key Program of National Natural Science of China

Central China Normal University National Teacher Development Collaborative Innovation Experimental Base Construction Research Project

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Developing and validating an AI-supported teaching applications’ self-efficacy scale;Research and Practice in Technology Enhanced Learning;2024-03-28

2. Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students' Achievement, Motivation, Participation and Attitude;Proceedings of the 14th Learning Analytics and Knowledge Conference;2024-03-18

3. Assessment Analytics: Feedback, Feedup, Feedforward on Bayesian Network;Advances in Analytics for Learning and Teaching;2024

4. User Requirements for Learning Analytics Dashboard in Maritime Simulator Training;2023 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM);2023-12-18

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