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Volume 113, Euroissues 2024
 
 
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Proceedings, 2025, AdaptEdu 2024

Online Workshop on Adaptive Education: Harnessing AI for Academic Progress

Online | 12 April 2024

Volume Editors:
Juliana Gerard, Ulster University, UK
Morgan Macleod, Ulster University, UK
Adina Camelia Bleotu, University of Bucharest, Romania
Muskaan Singh, Ulster University, UK

Number of Papers: 6
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Cover Story (view full-size image): Adaptive Education: Harnessing AI for Academic Progress was an online workshop held on 14 April 2024 that was dedicated to exploring the innovative and transformative role of generative AI in [...] Read more.
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13 pages, 1035 KiB  
Proceeding Paper
Revolutionising Digital Marketing Education with Generative Artificial Intelligence Integration: An Asynchronous Approach
by John Bustard and Mihaela Ghisoiu
Proceedings 2025, 114(1), 1; https://doi.org/10.3390/proceedings2025114001 - 14 Feb 2025
Viewed by 475
Abstract
The discipline of marketing has seen a significant shift toward the use of AI over the past 10 years, with generative AI such as ChatGPT exponentially accelerating the impact of this technology due to its accessibility and relevance in helping meet organisational and [...] Read more.
The discipline of marketing has seen a significant shift toward the use of AI over the past 10 years, with generative AI such as ChatGPT exponentially accelerating the impact of this technology due to its accessibility and relevance in helping meet organisational and practitioners’ objectives. The objective of this project was to innovatively incorporate generative pretrained transformers (GPTs) into digital marketing education as a means of asynchronously exposing learners to advances in this domain but also provide insights into managing AI use in this field more effectively. This pilot study focused on supporting tourism enterprises in less developed countries (LDCs), specifically Botswana, Uganda, and Zambia. Full article
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8 pages, 170 KiB  
Proceeding Paper
Cómo Entrenar tu Dragón: A European Credit Transfer System Module to Develop Critical Artificial Intelligence Literacy in a PGCERT Programme for New Higher Education Lecturers
by Mari Cruz García Vallejo
Proceedings 2025, 114(1), 2; https://doi.org/10.3390/proceedings2025114002 - 19 Feb 2025
Viewed by 164
Abstract
This paper summarizes the findings and main conclusions from the first presentation of the module “CETD23: Cómo entrenar a tu dragón: la inteligencia artificial generativa como herramienta para mejorar el aprendizaje en entornos online e híbridos”. This is an optional module accredited through [...] Read more.
This paper summarizes the findings and main conclusions from the first presentation of the module “CETD23: Cómo entrenar a tu dragón: la inteligencia artificial generativa como herramienta para mejorar el aprendizaje en entornos online e híbridos”. This is an optional module accredited through the ECTS (European Credit Transfer System) and delivered as part of the “Plan de Formación de Docencia y Personal Investigador 2021–2025” of the Universidad de Las Palmas de Gran Canaria (ULPGC). The Plan de Formación is a development programme offered by Spanish universities to new and existing teaching staff, aimed at improving the quality of their teaching practises in line with Aneca’s Docencia regulations (like the PGCERT and PGCAPT programmes in the UK). The aim of module CETD23 is to explore the use of Generative AI (GenAI) to enhance learning and teaching and to build the AI literacy of ULPGC’s teaching staff. The module received high student satisfaction, with an average score of 4.84 on the Likert Scale, and achieved a 100% completion rate for the final summative project. The final conclusions highlight the need for universities to establish reglamentos (policies and guidance) on how to use GenAI to enhance learning and assessment, as well as to involve students as equal partners in the design and assessment of methods that use AI. Full article
10 pages, 173 KiB  
Conference Report
Harnessing AI for Academic Progress: Common Themes and Future Directions
by Juliana Gerard, Kelly Norwood, Muhammad Usman Hadi, Aisling Reid, Antoine Rivoire and Muskaan Singh
Proceedings 2025, 114(1), 3; https://doi.org/10.3390/proceedings2025114003 - 26 Feb 2025
Viewed by 244
Abstract
This paper presents a reflection on the workshop topics and on further implications for different subject areas across higher education. We identify five overarching themes which emerged from the workshop presentations and reflect on the discussion of each respective theme. Next, we consider [...] Read more.
This paper presents a reflection on the workshop topics and on further implications for different subject areas across higher education. We identify five overarching themes which emerged from the workshop presentations and reflect on the discussion of each respective theme. Next, we consider these themes in the contexts of different undergraduate courses across subject areas. We focus on one course each from STEM, Social Sciences, and the humanities (engineering, linguistics, and English, respectively) and identify a component of each course which has been influenced by the increasing presence of generative AI in HE. We link these components to the overarching themes and conclude with some common themes across the subject areas. Full article
9 pages, 206 KiB  
Proceeding Paper
The Double-Edged Sword of Anthropomorphism in LLMs
by Madeline G. Reinecke, Fransisca Ting, Julian Savulescu and Ilina Singh
Proceedings 2025, 114(1), 4; https://doi.org/10.3390/proceedings2025114004 - 26 Feb 2025
Viewed by 371
Abstract
Humans may have evolved to be “hyperactive agency detectors”. Upon hearing a rustle in a pile of leaves, it would be safer to assume that an agent, like a lion, hides beneath (even if there may ultimately be nothing there). Can this evolutionary [...] Read more.
Humans may have evolved to be “hyperactive agency detectors”. Upon hearing a rustle in a pile of leaves, it would be safer to assume that an agent, like a lion, hides beneath (even if there may ultimately be nothing there). Can this evolutionary cognitive mechanism—and related mechanisms of anthropomorphism—explain some of people’s contemporary experience with using chatbots (e.g., ChatGPT, Gemini)? In this paper, we sketch how such mechanisms may engender the seemingly irresistible anthropomorphism of large language-based chatbots. We then explore the implications of this within the educational context. Specifically, we argue that people’s tendency to perceive a “mind in the machine” is a double-edged sword for educational progress: Though anthropomorphism can facilitate motivation and learning, it may also lead students to trust—and potentially over-trust—content generated by chatbots. To be sure, students do seem to recognize that LLM-generated content may, at times, be inaccurate. We argue, however, that the rise of anthropomorphism towards chatbots will only serve to further camouflage these inaccuracies. We close by considering how research can turn towards aiding students in becoming digitally literate—avoiding the pitfalls caused by perceiving agency and humanlike mental states in chatbots. Full article
14 pages, 1919 KiB  
Proceeding Paper
Insights Gained from Using AI to Produce Cases for Problem-Based Learning
by Enjy Abouzeid and Patricia Harris
Proceedings 2025, 114(1), 5; https://doi.org/10.3390/proceedings2025114005 - 27 Feb 2025
Viewed by 361
Abstract
Ulster University’s School of Medicine embraces a problem-based learning (PBL) approach, yet crafting scenarios for this method poses challenges, requiring collaboration among medical and academic experts who are often difficult to convene. This obstacle can compromise scenario quality and ultimately impede students’ learning [...] Read more.
Ulster University’s School of Medicine embraces a problem-based learning (PBL) approach, yet crafting scenarios for this method poses challenges, requiring collaboration among medical and academic experts who are often difficult to convene. This obstacle can compromise scenario quality and ultimately impede students’ learning experiences. To address this issue, the school trialed the use of AI technology to develop a case scenario focusing on headaches caused by cerebral haemorrhage. The process involved a dialogue between a single “author” and ChatGPT, with their outputs combined into a complete clinical case adhering to the school’s standard template. Six experienced PBL tutors conducted quality checks on the scenario. The tutors did not immediately endorse its use, recommending further enhancements. Suggestions included updating terminology, names, spelling, and protocols to align with current best practices, providing additional explanations such as interventions and improvements post-initial stability, incorporating real scans instead of descriptions, reviewing symptoms and timelines for realism, and addressing comprehension issues by refraining from directly providing answers and including probing questions instead. From this trial, several valuable lessons were learned: AI can assist a single author in crafting medical scenarios, easing the challenges of organizing expert teams. However, the author’s role shifts to reviewing and enhancing depth, guided by a template, with clinician input crucial for authenticity. ChatGPT respects patient data privacy and confidentiality by abstaining from providing scanned images, and while AI can generate discussion questions for tutorials, it may require modification to enhance specificity and provoke critical thought. Furthermore, AI can generate multiple-choice questions and compile reading resources to support self-directed learning. Overall, adopting AI technology can improve efficiency in the case-writing process. Full article
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8 pages, 886 KiB  
Proceeding Paper
Best Practices for the Responsible Adoption of Generative AI in Higher Education
by Alexander Mikroyannidis, Audrey Ekuban, Joseph Kwarteng and John Domingue
Proceedings 2025, 114(1), 6; https://doi.org/10.3390/proceedings2025114006 - 6 Mar 2025
Viewed by 260
Abstract
In this paper, we propose a set of best practices for the responsible adoption of Generative Artificial Intelligence (AI) in higher education. These best practices provide a comprehensive framework for higher education institutions to effectively and ethically integrate Generative AI into their teaching [...] Read more.
In this paper, we propose a set of best practices for the responsible adoption of Generative Artificial Intelligence (AI) in higher education. These best practices provide a comprehensive framework for higher education institutions to effectively and ethically integrate Generative AI into their teaching and learning practices. The framework prioritises a responsible and human-centred approach, alongside pedagogical soundness, careful planning, transparency, as well as content quality. By exploring the responsible adoption of Generative AI in higher education, we seek to provide scalable, personalised learning experiences for large cohorts of students. Our research focuses on harnessing Generative AI to offer tailored educational content and generate constructive feedback for students. Additionally, by adhering to responsible AI practices, we aim to address challenges such as misinformation, copyright violations, and bias. Full article
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