Predicting student performance on an e-learning platform
E-learning is the process of providing online courses on the Internet for students so that they can study and learn from any place and computing device. Predicting student performance on an e-learning platform is a critical feature that can be beneficial for taking corrective actions. For example the system would be used to provide course content for a particular subject in K-12 curriculum. The system would then be used to predict student’s performance in the final exam for that subject. Data mining techniques can be used to achieve this by analysing students’ usage, interaction and assessment data. The student’s usage data would be compared with historical data of other student’s in the system and various machine learning approaches like clustering/classification can be used to predict student performance.
Testing and data analysis
Applicant's Learning Objectives:
- Technical development
- Use of existing tools
- Communication skills