Plagiarism Among Students

Requirements Clarification & Assessment

1. Understanding the Problem Scope:

   • Detect plagiarism among 200 students initially, with scalability to handle up to 1,000,000 students.
   • Focus is on identifying collaboration or copying among students rather than external sources.

2. Key Objectives:

   • Accurately identify instances of plagiarism or collaboration in essay submissions.
   • Ensure the solution is scalable, efficient, and maintains a high level of accuracy.
   • Minimize false positives and false negatives in detection.

3. Constraints and Challenges:

   • Handling large datasets efficiently, especially in the 1M-essay scenario.
   • Balancing between computational efficiency and detection accuracy.
   • Ensuring the system is adaptable to different essay topics and writing styles.

4. Data Requirements:

   • Access to a corpus of student essays for analysis.
   • Labeled data indicating known instances of plagiarism for training purposes.

5. Performance Metrics:

   • Detection accuracy: True positive rate vs. false positive rate.
   • Scalability: Ability to process and analyze large volumes of data efficiently.
   • Response time: Time taken to analyze and flag potential plagiarism cases.