Objective

To develop a platform that automatically analyzes student feedback on courses, instructors, and learning materials, determining sentiment (positive, negative, neutral) to provide actionable insights for educators and administrators.

Key Features

 Student Panel:

• Submit feedback for courses, instructors, and study materials

• Provide textual feedback and optional ratings (1–5 stars)

• View previous feedback submissions

 Instructor Panel:

• Access sentiment analysis reports for their courses

• Identify strengths and weaknesses based on student sentiment

• Compare feedback trends across different courses or semesters

 Admin Panel:

• Manage users and feedback submissions

• Generate reports and dashboards summarizing overall sentiment

• Filter feedback by course, department, instructor, or time period

• Flag inappropriate or irrelevant feedback

Tech Stack

Workflow (Step-by-Step)

1. Feedback Collection

• Students submit textual feedback along with optional ratings

• Feedback is stored in the database for processing

2. Preprocessing

• Remove stop words, punctuation, and irrelevant characters

• Tokenize and normalize text

• Handle multiple languages if multilingual support is enabled

3. Sentiment Analysis

• Use NLP models (TextBlob, spaCy, or Transformers) to classify feedback as:

  • Positive

  • Negative

  • Neutral

• Extract key topics and recurring keywords using topic modeling

4. Reporting & Insights

• Aggregate sentiment scores by course, instructor, or semester

• Display trends in dashboards (graphs, pie charts, heatmaps)

• Identify top positive and negative feedback points

5. Actionable Recommendations

• Suggest areas for course improvement

• Highlight instructor performance strengths and weaknesses

• Track improvements over time based on sentiment trends

6. Optional Advanced Features

• Real-time feedback sentiment updates during the semester

• Predictive analytics to foresee student dissatisfaction

• Automatic alert system for highly negative feedback

• Integration with email or notification systems to respond to feedback