Combining Human and Artificial Intelligence for Enhanced AI Literacy in Higher Education

This paper seeks to contribute to the emergent literature on Artificial Intelligence (AI) literacy in higher education. Specifically, this convergent, mixed methods case study explores the impact of employing Generative AI (GenAI) tools and cyber-social teaching methods on the development of higher education students’ AI literacy. Three 8-week courses on advanced digital technologies for education in a graduate program in the College of Education at a mid-western US university served as the study sites. Data were based on 37 participants’ experiences with two different types of GenAI tools–a GenAI reviewer and GenAI image generator platforms. The application of the GenAI review tool relied on precision fine-tuning and transparency in AI-human interactions, while the AI image generation tools facilitated the participants’ reflection on their learning experiences and AI's role in education. Students’ interaction with both tools was designed to foster their learning regarding GenAI's strengths and limitations, and their responsible application in educational contexts. The findings revealed that the participants appeared to feel more comfortable using GenAI tools after their course experiences. The results also point to the students’ enhanced ability to understand and critically assess the value of AI applications in education. This study contributes to existing work on AI in higher education by introducing a novel pedagogical approach for AI literacy development showcasing the synergy between humans and artificial intelligence.

• Tzirides, Anastasia Olga (Olnancy), Gabriela Zapata , Nikoleta Polyxeni Kastania, Akash K. Saini, Vania Castro, Sakinah Abdul Rahman Ismael, Yu-ling You, Tamara Afonso dos Santos, Duane Searsmith, Casey O’Brien, Bill Cope and Mary Kalantzis, "Combining Human and Artificial Intelligence for Enhanced AI Literacy in Higher Education,” Computers and Education Open, CAEO 100184, 2024, doi: https://doi.org/10.1016/j.caeo.2024.100184.
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AI Literacy in Higher Education

The Future of Feedback: Integrating Peer and Generative AI Reviews to Support Student Work

This paper explores the integration of generative artificial intelligence (AI) in education to enhance feedback processes and improve learning experiences. The main goal of the study is to investigate the potential of generative AI for feedback, specifically in complementing peer feedback practices among graduate students enrolled at a US-based university during the 2023 academic term. Drawing on existing literature, the study examines the application of generative AI and its implications for feedback mechanisms. Employing an exploratory research design, the study gathers both quantitative and qualitative data through post-course surveys to address key research questions regarding the quality, usefulness, and actionability of peer and AI reviews, as well as their respective advantages and disadvantages. Findings indicate that peer reviews were consistently perceived slightly higher across all three dimensions compared to AI reviews, with thematic analysis revealing the unique strengths and limitations of each review type. This research underscores the importance of integrating human expertise with AI technology in feedback mechanisms, offering practical insights for educators, instructional designers, and policymakers seeking to enhance feedback experiences through emerging digital technologies.

• Saini, Akash K., Bill Cope, Mary Kalantzis and Gabriela C. Zapata, "The Future of Feedback: Integrating Peer and Generative AI Reviews to Support Student Work,” EdArXiv, 2024, doi: https://doi.org/10.35542/osf.io/x3dct.
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  Future of Feedback