ExplainED: Enhancing Feedback Precision in Education Using NLP and Explainable AI

Project Overview:

This collaborative project focuses on employing advanced Natural Language Processing (NLP) and Explainable AI (XAI) techniques to enhance feedback systems in education. The primary objectives include:

Automating the feedback process for assignments and discussions to save educators time and enhance precision.

Ensuring transparency through explainable AI mechanisms for actionable insights.

Analyzing student engagement to identify and address learning gaps effectively.

Deliverables:

1. AI-Powered Feedback System: A model trained on existing datasets for automated feedback generation.

2. Explainable Dashboards: Interactive tools for educators to review AI recommendations and validate their accuracy.

3. Student Insights Platform: A portal providing students with personalized feedback and improvement suggestions.

4. Impact Assessment Report: Analysis of the effectiveness of the system in improving educational outcomes.

Impact:

Educators: Significant time savings on repetitive feedback tasks and improved feedback quality.

Students: Clearer understanding of their strengths and weaknesses, with actionable steps for improvement.

Education System: Enhanced engagement and equity through personalized interventions and data-driven insights.