Learning Analytics to the Rescue? A Personalized Learning Dashboard

I prototyped an innovative dashboard using R to transform how university teachers approach statistics education. This tool offers a comprehensive view of student performance and engagement, empowering instructors to provide targeted support and enhance learning outcomes.

Key Features:

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1. Predictive Analytics: Forecasts student performance to enable proactive intervention.
2. At-Risk Learner Detection: Identifies students who may need additional support.
3. Personalized Recommendations: Suggests tailored readings and activities for each student.
4. Performance Assessment: Evaluates both student progress and teaching effectiveness.

   

   The dashboard provides instructors with valuable insights, such as:

• Questions students frequently struggle with
• A less performance-oriented view of student states
• The ability to adjust time estimates for tasks

High-struggle questions identified, with most common error laid over.

Long-term goals include:

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• Normalizing and highlighting common misconceptions
• Offering a holistic, sympathetic overview of student performance and challenges
• Helping students self-regulate their effort levels

By presenting high-struggle questions alongside common errors, the dashboard helps instructors address widespread issues efficiently. This personalized approach has shown significant increases in learner engagement, paving the way for more effective statistics education.

Our project aims to create a more supportive, understanding learning environment while equipping teachers with the tools they need to guide their students to success.