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Quizzit - Recommender

This project utilizes user profiling, adaptive presentation and other researched topics like Open Social User Modeling and Visualizations, content recommendation, etc. to build an adaptive system that will help users learn topics in Java in a user-centric way.

Implementations:

  • Recommendation algorithm for quizes based on user's performance, question type and difficulty
  • User Login / Sing-up
  • Quiz Page
  • Discussion Forum
  • Recommendations based on Performance
  • Leaderboard
  • User History
  • Friend Requests/adding friends
  • User activity visualizations
    • Heat map: Which gives user answering frequency based on the date, which helps them in deciding on what days their activity was low and on what day activity was high
    • Time series: This visualization indicates the overall performance of users over the time i.e., how good or bad the performance is over time
    • Stacked bar plot: Two elements considered here are #questions and #recommendation links referred. These two are the major key factors indicating the user activity. Here we are pushing the open social student model element by comparing the activity of every user over the time.
    • Pie Chart: Every user might ultimately want to understand his/her performance along with the coverage. Coverage indicates how well they progressed in all the areas. So, this visualization helps the user in understanding the progress in all the areas