The Role of Generative Artificial Intelligence in Supporting Student Learning in Postsecondary Education

Dear Colleagues,

With the availability and popularity of generative artificial intelligence (GenAI), the relationship between technology and education has evolved significantly in recent years. This Special Issue explores the multifaceted ways in which GenAI can support student learning, enhance pedagogical practices and transform the educational landscape in postsecondary education.

With its capacity to analyze data, generate content and personalize learning experiences, GenAI has the potential to reshape how students engage with course materials, interact with instructors and navigate their educational journey. The topics explored in this Special Issue aim to capture the breadth of this technological impact, from theoretical perspectives to practical applications, including the following:

• The use of GenAI in enhancing student learning experiences: How can GenAI tools facilitate personalized learning pathways, provide feedback and support student progress?
• Pedagogical strategies integrating GenAI: How are educators leveraging or integrating GenAI to design curriculum, deliver content and evaluate student outcomes?
• Integration of GenAI in formative and summative assessment activities: How can AI tools be integrated into formative and summative assessment activities, and how can they support personalized feedback and understand assessment criteria?
• Ethical considerations and challenges: What ethical considerations arise with the integration of GenAI in postsecondary education, and how can they be addressed?
• Comparative studies: How do different educational institutions and disciplines utilize GenAI to support teaching and learning? How do different types of students (for instance, neurotypical vs. neurodiverse) experience and interact with GenAI tools?

This Special Issue welcomes empirical research, qualitative, quantitative or mixed-methods analysis, systematic reviews and case studies that explore the integration of GenAI in postsecondary education.

We hope that this Special Issue will promote dialogue and innovation, and provide a platform for exploring the transformative potential of GenAI in postsecondary education.

You may choose our Joint Special Issue in Education Sciences.

Dr. Rebecca Upsher
Dr. Claire Heard
Dr. Sumeyra Yalcintas
Guest Editors

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• generative artificial intelligence
• pedagogy
• postsecondary
• higher education
• curriculum design
• student learning
• assessment

Title: the context of a psychology-oriented MSc at a UK university
Authors: Alex F. Martin1,2*, Svitlana Tubaltseva3, Anja Harrison1, G James Rubin1,2
Affiliation: 1 King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK; 2 NIHR Health Protection Research Unit in Emergency Preparedness and Response, London, UK; 3 Richmond American University London, School of Liberal Arts, London, UK. *Corresponding author: [email protected]
Abstract: Background: Generative AI tools offer new opportunities for enhancing learning and assessment but also raise concerns about equity, academic integrity, and the ability to critically engage with AI-generated content. This study explores these issues within the context of a psychology-oriented MSc at a UK university. Aims: This project will explore and co-produce a novel approach to assessment that aims to improve the critical AI literacy of students and staff (pre-registration: https://osf.io/jqpce). Methods: The study involves a pilot trial which integrates generative AI into an existing assessment method. Students are divided into two groups: the ‘honest’ group uses AI tools to write a blog, then critique the AI-generated content and submit a refined blog, while the 'cheating’ group has free rein to use AI to produce the entire assessment. Teaching staff will mark the blogs using an adapted rubric. Data collection includes focus groups, interviews, and workshops to evaluate the acceptability and feasibility of the assessment approach and to co-produce a final set of assessment materials. Results: The study will provide insights into the acceptability of the new assessment method and materials, and the feasibility of implementing this approach in higher education. Conclusion: This pilot study aims to enhance critical AI literacy in students and staff and develop an assessment framework that can be scaled across various courses. The findings will inform future practices in integrating AI tools in educational assessments.

Title: Exploring the Utility and Perception of AI-Assistant Chatbots in Medical Education
Authors: Mandeep Gill Sagoo; Isaac Ng
Affiliation: King's College London
Abstract: The integration of artificial intelligence (AI) in medical education is rapidly advancing, offering novel opportunities to enhance learning experiences and outcomes. However, the effectiveness of AI-driven tools in supporting medical education, as well as students' perceptions of these tools, remains underexplored. This study seeks to evaluate the utility of AI chatbots in medical education by focusing on their effectiveness in facilitating learning and exploring the perceptions of preclinical medical students regarding these tools.

Title: Processfolio: designing an assessment of students' writing processes with GenAI.
Authors: Jayne Pearson; Brenda Williams
Affiliation: King’s College London, London SE1 1UL, UK
Abstract: GenAI in higher education has caused concern in the area of assessment validity, and is a catalyst for re-examining our understandings of authenticity. This article explores a potential incarnation of an assessment called processfolio (Pearson, 2017, 2021), in which students reflect explicitly and comment on their use of GenAI in the process of creating a written piece of work for summative assessment. Based on staff and student focus groups as part of a co-created design, this article will critically evaluate the potential of the processfolio for metacognitive engagement with learning alongside GenAI, disrupting conceptualisations of academic integrity and the writing process itself.

Title: Getting the guidance right: student views on balancing innovation and integrity in Generative AI Use in Higher Education
Authors: Ioana Rusnac*, Katherine Haselton*, Claire Heard; Sumeyra Yalcintas; James Findon; Jayne Pearson; Rebecca Upsher *Joint first
Affiliation: Department of Psychology, King’s College London, London SE1 1UL, UK
Abstract: This qualitative study explores undergraduate psychology students' perspectives on the ethical, academic, and practical implications of using generative artificial intelligence (GenAI) in university assessments. Conducted through two focus groups at a large UK Russell Group university, the study highlights two primary themes: student concerns with GenAI and effective communication and guidance. Participants expressed a need for clear, accessible guidance from university staff to help navigate ethical use, with suggestions for adaptive assessment strategies to better support student engagement with GenAI. Findings underscore the importance of empathetic facilitation, and the involvement of both student and staff perspectives in creating balanced AI-related policies within higher education.