Nurun Nahar

This paper investigates the relationship between artificial intelligence (AI) technology and educational policy in higher education, highlighting key research and implementation. The paper focuses on critical considerations for AI policy development with a view to producing a roadmap focused on contextual higher education AI policies. The rapid development of AI presents both significant opportunities and challenges for higher education institutions in Europe and globally. As AI technologies become ubiquitous, integrated into teaching, learning, and administrative functions, it is essential to identify critical considerations at the core of the AI integration process, namely: (1) regulatory framework, (2) stakeholder-specific guidelines, (3) AIED research, and (4) AI literacy. As a starting point, the paper presents a review of existing AI policy frameworks within higher education, drawing on recent empirical research, identifying four design and implementation priorities for higher education stakeholders aiming to create responsible AI governance frameworks. As a result, we propose a roadmap designed to be used as strategic planning instrument for higher education stakeholders developing AI policies and guidance. In proposing a strategic roadmap for AI policy development, the work offers valuable insight into how higher education can effectively leverage the potential of AI whilst ensuring ethical considerations, equity, and maintaining academic integrity. Additionally, the paper contributes to the ongoing discourse regarding AI’s role in higher education in proposing research pathways that will benefit all stakeholders involved in the academic ecosystem.

The integration of Artificial Intelligence (AI) in educational settings has opened new avenues for enhancing student learning. This study investigated the use of a generative AI chatbot, trained to provide feedback using the Socratic Method, in a Business Management programme. Recent literature highlights the transformative potential of AI in education, particularly in fostering personalised learning experiences and supporting critical thinking (Gökçearslan et al., 2024; Lee and Moore, 2024; Mustafa et al., 2024). Understanding student perspectives on AI-generated feedback is crucial for optimising its use in learning development. This study aimed to evaluate the effectiveness of AI feedback in promoting critical thinking and its acceptance among students. Previous research has shown that AI chatbots can enhance learning by providing timely and relevant feedback, though challenges such as limited interaction and potential for misleading guidance remain (Banihashem et al., 2024; Gökçearslan et al., 2024; Guo et al., 2024). A qualitative approach was employed, utilising a focus group with n=14 final-year undergraduate students on a Business Management pathway. The generative AI tool was piloted to provide feedback on student drafts for summative coursework. The quality of feedback was assessed based on its accuracy, relevance, timeliness, and effectiveness in fostering critical thinking. Data was analysed using thematic analysis, a method well-suited for identifying and interpreting patterns within qualitative data (Nowell et al., 2017; Braun and Clarke, 2022). The Socratic Method, known for its effectiveness in promoting critical thinking through questioning, was employed as the feedback mechanism (Buckingham Shum, 2024). The study revealed that students found AI-generated feedback useful and relevant for improving their work and identifying knowledge gaps, thereby promoting deep learning. The Socratic Method used by the AI encouraged deeper engagement with their work, unlike the straightforward answers typically provided by other chatbots. However, students preferred tutor feedback.

This paper analyses 15 AI policies for higher education from eight European countries, drawn from individual universities, from consortia of universities and from government agencies. Based on an overview of current research findings, it focuses the comparison of different aspects among the selected AI policies. The analysis distinguishes between four potential target groups, namely students, teachers, education managers and policy makers. The paper aims at contributing to the further development and improvement of AI policies for higher education through the identification of commonalities and gaps within the existing AI policies. Moreover, it calls for further and in particular evidence-based research to identify the potential and practical impact of AI in higher education and highlights the need to combine AI use in (higher) education with education about AI, often called as AI literacy.

Collaboration between students and staff has increasingly gained recognition as a powerful avenue for enhancing the overall learning experience in Higher Education. Student-staff partnership projects offer a unique opportunity for students to actively engage with their programme of studies, influencing decision-making processes and contributing to the improvement of the learning environment. This reflective practice piece delves into the lived experiences of four students who embraced student-staff partnership in unique ways, each contributing their perspectives and invaluable insights to projects they were involved in. With an aim to shed light on the significance of reflecting upon these lived experiences, recognising the immense value they hold for students, staff and the institution as a whole, a critical narrative enquiry approach was used in addition to vignettes to understand the intricacies and dynamics of student-staff partnerships, unravelling the complexities and capturing the transformative effects of these collaborations on students. By examining the challenges and triumphs faced by these four student partners, we gain insights into the multifaceted nature of student-staff partnerships, their potential for growth, and the resulting impact on the higher education landscape.

In order to enable learners to take control of their learning needs and actively contribute in their learning processes, educators can partner with students in various reciprocal student-staff partnership (SSP) settings where students can be co-creators, co-producers, curators or co-deliverers of the curriculum. This case study, undertaken to enhance the curriculum as part of teaching qualification, places emphasis on educators partnering with first-year undergraduate students over e-content creation within an existing module using readily accessible digital applications in order to promote active learning in students and improve student engagement. The extent to which SSP as an approach to the creation of e-learning materials using digital applications, enhanced learning and student engagement in an existing module, was evaluated. Results indicated, students’ perceived SSP to be an excellent platform for learning, actively engaging in the classroom as well as for developing various skills. However, some concerns were expressed with regards to overcoming the power hierarchy barrier within an SSP initiative.

The present research looked at the importance of the concept of grit in University students based on a mixed-method approach. Study 1 comprised 440 University students. All were given the Grit Scale, the Perceived Stress Scale, the short Warwick– Edinburgh MentalWell-being Scale, the Office of National StatisticsWell-being items and the Self-Control Scale. Levels of grit were significantly higher in female students, older students and postgraduates. Grit correlated highest with self-control. Study 2 looked at 340 University students. In addition to measuring self-control, mental well-being and grit, measures of resilience and mindsets were also added. A construct validity test of the Grit Scale showed that high grit scorers had significantly higher levels of selfcontrol and mental well-being, were more resilient and were more likely to have a more growth oriented mindset. Grit varies with age and is most closely associated with the concept of self-control. The third study was a qualitative investigation with 10 successful graduates. Semi-structured interviews were coded using thematic analysis. Three broad themes emerged. The first, Passion and Perseverance, included themes of having short and long terms goals, resilience, dedication, and endurance. The second, Self-Control, included time management, self-awareness, prioritizing tasks and knowing strengths and weaknesses. The third theme identified was Positive Mindsets. This included having a positive attitude toward learning, the importance of feedback and constructive criticism and that success is not materialistic. The qualitative research has helped “unpack” concepts from the grit research and may enable University tutors to guide students better. Though these studies were only conducted in one English University, they have been stepping stones in our quest to discover what are the most important factors in determining student academic success? The development and piloting of our new Uni-Stride Scale, is the next step in this process.