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From Coders to Critics: Empowering Students through Peer Assessment in the Age of AI Copilots

Project Overview

The document explores the transformative role of generative AI tools, such as ChatGPT and GitHub Copilot, in programming education, addressing both the opportunities and challenges they present, particularly concerning academic integrity and traditional assessment practices. It highlights a study focused on structured peer assessment within a programming course, which demonstrated its effectiveness in closely mirroring instructor evaluations while enhancing student engagement and critical thinking skills. The findings indicate that peer assessment can be a valuable pedagogical strategy in an AI-assisted learning environment, although it acknowledges ongoing issues regarding the reliability of feedback and the level of student participation. Overall, the document underscores the potential of generative AI to reshape educational approaches while also necessitating the adaptation of assessment methods to maintain academic standards.

Key Applications

Peer assessment in programming courses

Context: Large introductory programming course for first-semester students without prior programming knowledge

Implementation: Anonymized peer review process where students evaluated each other's projects using a detailed rubric

Outcomes: Peer evaluations correlated moderately with instructor grades, fostering student engagement and critical thinking; students reported a sense of fairness and enjoyment in the evaluation role.

Challenges: Variability in peer grading accuracy, skepticism about peer feedback, and low engagement in voluntary review processes.

Implementation Barriers

Reliability

Potential biases or inconsistencies in peer grading due to novice reviewers lacking experience.

Proposed Solutions: Clear assessment rubrics, training for reviewers, and anonymization of submissions to reduce bias.

Engagement

Low student participation in peer reviews without proper incentives.

Proposed Solutions: Integrating reward mechanisms or gamification elements to motivate student engagement.

Project Team

Santiago Berrezueta-Guzman

Researcher

Stephan Krusche

Researcher

Stefan Wagner

Researcher

Contact Information

For information about the paper, please contact the authors.

Authors: Santiago Berrezueta-Guzman, Stephan Krusche, Stefan Wagner

Source Publication: View Original PaperLink opens in a new window

Project Contact: Dr. Jianhua Yang

LLM Model Version: gpt-4o-mini-2024-07-18

Analysis Provider: Openai

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