Tips For Markers On Spotting Potential AI Usage
Tips for Spotting Incorrect AI Usage in Mathematics and Statistics Assignments
- Home
- 1.Formal Report
- 1.1 Introduction to Project
- 1.2 The Emergence of ChatGPT and Limitations of GPT-3.5
- 1.3 Understanding LLMs and Evolution of AI Models
- 1.4 Extending LLM Capabilities and Introduction of ChatGPT o1
- 1.5 A Step Change in AI Capabilities and Key Findings
- 1.6 Performance of AI Models and Urgency for Institutional Action
- 1.7 Recognising the Problem and Specific Regulations
- 1.8 Recommendations and Conclusion
- 2. Student Conversations
- 3. How ChatGPT Performed on University-Level Work
- 4. Suggested Changes and Future Direction of Regulations
- 4.1 Developing Clear Policies on AI Use
- 4.2 Enhancing Student Support and Guidance
- 4.3 Emphasising Skills That AI Cannot Replicate
- 4.4 Adapting Pedagogy and Innovating Assessments
- 4.5 Encouraging Collaborative Solutions Among Stakeholders
- 4.6 Allocating Resources for Training and Support
- 4.7 Adopting Alternative Assessment Methods
- 4.8 Relying on Honour Codes and Academic Integrity Pledges
- 4.9 Designing AI-Resistant Assignments
- 4.10 Using AI Detection Software
- 4.11 Implementing Oral Examinations (VIVAs)
- 5 Opportunities AI Presents
- 6 Tips For Markers on Spotting Potential AI Usage
These are tips which may indicate AI-generate content. It is important to note that currently at Warwick University, students can use AI provided they maintain intellectual ownership of the work and reference where they have used AI. Students should also be able to give screenshots of prompts and outputs of any AI tools they may have used.
- Repetition: AI may repeat phrases or explanations unnecessarily.
- Simple Arithmetic Mistakes: While AI can handle complex calculations, it may make unexpected errors in basic arithmetic.
- Over-explanation of Trivial Steps: AI might provide unnecessarily detailed explanations for simple steps.
- Missing Steps: Conversely, AI might skip important steps in a proof or calculation without explanation.
- Disconnected Definitions and Theorems: AI may state definitions, theorems, or lemmas without clearly connecting them to the question.
- Out-of-Scope Knowledge: Be wary of solutions that use concepts or techniques not covered in your module.
- Inconsistent Academic Level: The work's style and complexity should match university-level expectations. AI might produce work that's either too simplistic or unnecessarily complex.
- Unnatural Language: Look for awkward phrasing or an unnatural tone in written explanations.
- Confidently Incorrect Answers: AI might present wrong answers with a high degree of confidence.
- Inconsistent Work Patterns: Compare the submission with the student's previous work. Significant changes in style, quality, or approach could indicate AI usage.
Remember: These indicators aren't definitive proof of AI usage, but they can help you identify assignments that may require closer scrutiny or a conversation with the student.