The Research of Applying Educational Big Data and Learning Analytics to Improve Self-Regulated Learning in Programming(3/3)

Project Details


This project focus on the research topic of learning analysis for a large amount of data in the field of education. It is hoped that the results revealed by learning analysis will assist teachers in teaching and improve students' learning effectiveness. For programming courses, this project will explore the impact of Self-Regulation Learning (SRL) on the learning performance in programming course. This project is based on student learning history collected from an integrated learning environment. It aims to explore student learning patterns and identify high-risk students early, and then provides a real-time learning dashboard to provide teachers with information about student learning and help teachers intervene and guide students adjust their learning. To achieve the above goals, this project will develop (1) real-time learning dashboards, (2) students' learning performance prediction model, and (3) learning patterns extraction model. In an integrated learning environment, a real-time learning dashboard is used to demonstrate student participation in classroom learning activities. According to students learning patterns, the predicted student's learning performance, and students' self-regulation learning capabilities, this project will propose appropriate and effective learning adjustment suggestions for various types of students in order to provide students with personalized intervention to achieve the goal of adaptive learning and then to improve learning performance.The project will carry out the learning activity in an autonomous SRL programming flipped classroom. In the first year, a pilot study of autonomous SRL programming flipped classrooms will be conducted. Participants in the project are students of the Python programming course offered by the National Central University General Education Center in the 109 academic year. This course has approximately 50 students. The second year of the project is a large-scale data validation analysis, and its participants will be extended to all students at the 110 academic year at National Central University who will take Calculus courses and practical training for programming. Finally, in the third year of this project, the participates are the students at the 110 academic year in National Central University who took Calculus and join practical training for programming. They will conduct interventional SRL programming flipped classroom. This project aims to explore whether the intervention activities based on the results of learning analysis to adjust students' SRL ability can be effective Improve students' learning performance.
Effective start/end date1/08/2231/07/23

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 4 - Quality Education


  • Educational big data
  • learning analytics
  • programming
  • self-regulated learning
  • at-risk students prediction
  • early intervention
  • reading patterns


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