Felipe Tessarolo

This paper introduces the First TMA Intervention Framework, a practice-informed model for supporting students during their first tutor-marked assignment (TMA) in distance higher education. Developed through a narrative institutional review of 93 documented interventions and practices, the framework maps institutional and tutor-led support to 12 critical checkpoints across the first assignment lifecycle, from early engagement and preparation to feedback and post-assessment reflection. Drawing on institutional data and practitioner insight, the framework offers a structured and transferable way to analyse and organise first-assignment support practices.

This conceptual paper theorises Generative AI (GenAI) as a structural gatekeeper in higher education, advancing gatekeeping theory through a synthesis of media studies and educational governance. It positions GenAI not as a neutral tool but as an epistemic actor that reshapes control over knowledge production, curriculum design, and institutional autonomy. The paper introduces two constructs: the GenAI Algorithmic Gatekeeping Model, modelling recursive algorithmic influence; and the Human–AI Gatekeeping Model, a normative framework for sustaining academic integrity and epistemic diversity. Drawing on policy discourse, literature analysis, and illustrative cases, it develops a comparative lens for examining how algorithmic mediation reconfigures authority and standardisation in educational contexts. It concludes by setting a research and policy agenda for governing AI in education, inviting further inquiry into the conceptual architecture and normative implications of algorithmic gatekeeping.

As GenAI tools become more pervasive in learning, the ways in which educators can influence the behaviour of these systems should be a focus for research and innovation. As part of designing and trialling an institutional AI digital assistant for study, we are exploring where and how educators’ technological, pedagogical and content expertise could be brought to bear in the way in which the assistant behaves. In this paper, we draw on feedback from 20 educators and education researchers who took part in a trial of a prototype of the system and reflect on the process of designing the system to be embedded into the study of online courses. We highlight six methods through which educators can exert influence over the behaviour of such assistants and reflect on the alignment, possibilities and limitations of these to meet educator goals. This contributes to opening up a space for educators to think strategically and creatively about teaching with AI.

In Industry 5.0 it is essential that humans are in the loop of technology integration of industry processes. With the advancements of Generative Artificial Intelligence (GenAI), a lot of new opportunities and challenges for learning and teaching are present. Many students already use publicly available AI Digital Assistants (p-AIDA) like ChatGPT for academic purposes. However, there are concerns around the use of such p-AIDA tools, particularly in terms of academic integrity, data privacy, intellectual property, and the impact on the quality of education. Furthermore, many higher education institutions have substantial learning materials and data about students that they may not want to share with p-AIDA. Therefore, using the Technology Acceptance Model (TAM) and following a Design-Based Research (DBR) approach, we explored the perspectives and experiences of a beta-test of an institutionally developed AIDA (i-AIDA) with 18 UK students using multiple methods and data sources (including pre-post-test, interviews, think-aloud, and prompt analysis). Our research underscores the potential benefits and limitations of in-house i-AIDA in enhancing learning experiences without compromising academic integrity or privacy, and how higher education institutions can prepare themselves for Industry 5.0.

The rapid evolution of Generative AI (Gen AI) and its integration into higher education necessitates a critical evaluation of teaching and learning practices. Many students already use publicly available AI Digital Assistants (p-AIDA) such as ChatGPT for academic purposes. However, there are concerns around the use of such p-AIDA tools, in particular in terms of data privacy, academic integrity, Intellectual Property (IP), and the impact on the quality of education. We therefore explored the perspectives of AI usage with 106 students in two consecutive studies using a Design-Based Research (DBR) approach. Study 1 explored the lived experiences a demoed prototype of an institutional AI Digital Assistant (i-AIDA) with ten distance learning students. Building on these findings, in Study 2 the preliminary results were validated with a cohort of 96 students using an online survey on whether the development of an i-AIDA might mitigate some of these concerns. By comparing i-AIDA with p-AIDA in two studies our research underscores the potential benefits and limitations of in-house Gen AI tools in enhancing learning experiences without compromising academic integrity, IP or privacy.

This mixed methods study explores 315 distance learning students’ perceptions of artificial intelligence digital assistants (AIDAs) over an 11-month period in three distinct studies. The research investigates student perspectives on both a publicly available AI digital assistant (p-AIDA), such as ChatGPT, and a potential institutionally developed AI digital assistant (i-AIDA). Findings indicate that students highly valued 24/7 immediate academic feedback and the personalisation of the i-AIDA, and these perspectives remained largely stable across the three studies. However, concerns about academic integrity, data privacy, and ethical implications persisted across the studies. A cluster analysis identified three distinct student groups of highly critical, supportive, and keenly supportive learners, with key differences based on prior GenAI experience, educational background, and age. This study underscores both the potential and challenges of developing institutional AI solutions to enhance student learning while addressing privacy and ethical concerns.

Accessibility, inclusive teaching, and student support are multi-faceted; they are dependent on wider institutional factors, such as leadership, resource, systems, and culture. To be truly inclusive requires a whole institution approach, with voices, perspectives, and stakeholder buy-in sought from across the institution. This can be extremely challenging because these can be sensitive to myriad institutional, sector, and societal changes that can influence working practices, resource management, and capacity. In this paper, we analyse responses from three iterations of a biennial staff survey conducted in 2017, 2019, and 2021 at the Open University (OU), capturing views on accessibility and inclusion before and during the COVID-19 pandemic and other challenging circumstances. These responses, from tutors, module and programme teams, educational technologists, library staff, and student support teams, reveal crucial insight into the (in)accessibility of support and practice across the institution, as well as insight into staff skills, attitudes, and knowledge around accessibility, and the fitness for purpose of the systems and structures in place. In this analysis, we explore how staff practices and perceptions change over time; identify the themes that remain constant over time, despite global circumstances; and explore how these themes can inform a whole-institution approach to accessibility and inclusion.

The sudden transition from face-to-face into distance learning activities in higher education during the Covid-19 pandemic has highlighted the need to improve student induction and transition into distance learning settings. This study explores the experiences of first-year students at a distance learning university. Semi-structured interviews were conducted with students, aged 18-19, who transitioned from a face-to-face environment (school, college or another university) to distance-learning higher education. Thematic analysis yielded themes related to students’ early perceptions on distance-learning, experiences with learning and assessment, and social interactions. Noteworthy findings include students’ early misconceptions of distance-learning, distance-learning as a shelter for students with mental health issues, views on hybrid learning and continuous assessment, and approaches to socialising. Insights from this study have implications for how universities with new and existing distance learning practices design their induction and support programmes to facilitate student transition and enhance the first-year student experience.