Evaluating Trust in AI, Human, and Co-produced Feedback Among Undergraduate Students
Project Overview
The document explores the impactful role of generative AI in improving feedback mechanisms within education, emphasizing students' perceptions of AI-generated, human-created, and co-produced feedback. A study involving 91 undergraduate psychology students revealed a preference for AI and co-produced feedback over traditional human feedback, particularly regarding perceived usefulness and objectivity. However, the research also uncovered trust issues and biases that students held against AI-generated feedback, indicating a need for caution in its implementation. These findings underscore the importance of developing evidence-based guidelines for the integration of AI into higher education feedback systems and highlight the necessity of enhancing AI literacy among students to better navigate these technologies. Overall, the study points to the potential of generative AI to transform educational feedback while also identifying challenges that need addressing to ensure effective adoption.
Key Applications
AI-generated feedback and co-produced feedback
Context: Higher education, undergraduate psychology students
Implementation: Within-subject experimental design comparing AI, human, and co-produced feedback types
Outcomes: Students preferred AI and co-produced feedback for usefulness and objectivity; improved ability to identify feedback types with educational AI experience.
Challenges: Trust issues towards AI feedback, biases against AI as a feedback provider, and concerns about the genuine nature of AI feedback.
Implementation Barriers
Trust and Bias
Students exhibit distrust towards AI-generated feedback due to biases and concerns about algorithmic reliability.
Proposed Solutions: Implement co-produced feedback approaches to combine human oversight with AI capabilities, enhancing trust and credibility.
Implementation Complexity
Challenges in ensuring effective human-AI coordination and communication in feedback processes.
Proposed Solutions: Develop training and clear guidelines for instructors to effectively integrate AI into feedback practices.
Project Team
Audrey Zhang
Researcher
Yifei Gao
Researcher
Wannapon Suraworachet
Researcher
Tanya Nazaretsky
Researcher
Mutlu Cukurova
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Audrey Zhang, Yifei Gao, Wannapon Suraworachet, Tanya Nazaretsky, Mutlu Cukurova
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