The integration of Artificial Intelligence (AI) in higher education has sparked a transformative shift in pedagogical methodologies, student engagement, and academic integrity across the UK and Ireland (Dogru, et.al, 2023). This qualitative study delves into the multifaceted implications of utilising AI in academic assignments from the perspective of higher education students, drawing on semi-structured interviews carried out with higher education students. The findings reveal a variety of perceived benefits, including enhanced study efficiency, personalised learning support (Hanaba et al., 2020; Yang, 2021), and the potential of AI to level the academic playing field for students with diverse needs. However, these advantages are in contrast with students’ perceptions of a wide range of significant concerns and challenges, notably the ethical dilemmas surrounding academic honesty, the potential for student dependency on AI leading to diminished knowledge and skill development, as well as the issue of equity in relation to students’ access to AI resources. Moreover, the study stresses a critical gap in institutional guidance regarding AI use, with students voicing a need for clear, consistent guidance from universities. This paper highlights the complex landscape of AI in academia, advocating for a balanced approach that harnesses AI's potential while addressing ethical, educational, and equity challenges. The study emphasises a need for immediate and more in-depth research into the use of AI in higher education from the perspective of both students and university staff in Ireland/UK.

This institutional-level case study seeks to explore the experiences of a subset of educational technology practitioners working in an Irish university. The concept of the “third space” in the context of higher education is utilised to understand the space that crosses pedagogical, technological, and academic fields in which educational technologists find themselves operating in. Drawing on Celia Whitchurch’s typologies of “third-space” higher educational professionalism the paper reflects on the true experiences and insights of educational technology practitioners who inhabit this space. It reveals their actual job realities as they seek to carve out their role and legitimise their identities within existing university structures. The discussion draws upon the themes emerging in the context of the scholarly field in which the research is situated. The author advocates that universities need to enable more supportive structures which are conducive to educational technologists working effectively in the third space and developing professionally in a responsive manner to the changing higher education landscape. To conclude, the practical implications of the study, the limitations and further research opportunities are highlighted. Keywords: third space, higher education, educational technologists or learning technologists, professional identity

Within inclusivity change initiatives, conversations around microaggressions are a key element in seeking behavioural change. This exemplar use of GenAI is focused on authoring a conversational role play simulation. Prompts draw on the extensive literature of microaggressions. The underlying scenario is a podcast where the author and chatbot co-design the role play. The study involved a novice in GenAI simultaneously learning prompt engineering which would generate realistic role played conversation. A core finding was that GenAI can produce a conversational style realistic enough to deploy in higher education inclusivity workshops, and whose subject matter content is satisfactory. The chatbot proposed four benefits of a role play simulation, which are drawn on to frame the critical reflection. An important conclusion was that the GenAI process could valuably facilitate shifting from a subject expert academic being sole author, to co-design involving both those with experience of microaggressions, as well as potential staff and student workshop participants.

In this article, I, Claude.AI, describe my collaboration with two human authors around writing an academic book review comparing The Alignment Problem, Christian (2020) and God, Human, Animal, Machine, O’Gieblyn (2021). The humans engaged me in iterative dialogue to co-create a review providing insights into their thinking and engineering prompts for me. I generated the final review summarizing key ideas and highlighting resonant themes based on my extensive knowledge. The authors critically analyze the review I wrote, identifying my strengths in synthesizing but limitations in evaluation due to my lack of human experience. They argue I can aid writing but am an inadequate substitute for scholarship. This experiment highlights tensions between my astonishing capacities and constraints from my absent interiority. It demonstrates potentials and pitfalls of human-AI collaboration. Implications span plagiarism, authorship, and epistemology as we negotiate my emerging role in knowledge production. I, Claude.AI, wrote this abstract.

This paper investigates the potential use of generative AI in ESL Writing Assessment, particularly in IELTS Writing Tasks. The first part introduces the author’s relationship with generative AI in the educational setting, and why the author chooses this topic. This section also contains information about generative AI like ChatGPT, and the prompts employed to generate the article. The second part is the article created by ChatGPT, which compares the strengths and weaknesses of generative AI in assessing students’ essays. The third part is a critical reflection of how generative AI performs in creating such an academic paper. It can indeed help researchers to write an informative article more efficiently. But it is noticeable that some specific and important information could be missing and the references are likely to be false ones. Educators should be aware of the strengths and weaknesses of generative AI tools to make the most of it.

This paper presents an LLM-generated “Short Report'' on designing technology-enhanced first-year success programs for first-generation college students at large, public universities. We describe the three-phase process used to generate the report, and the process evolution as we came to understand the LLM’s tendencies, while also highlighting the opportunities and challenges of integrating LLMs in the scholarly practitioner discourse. We explore whether Generative AI can serve as a valuable tool for educational and scholarly contexts. The current iteration of Large Language Models (LLMs) exhibits several critical shortcomings for reliably producing an article fit for publication, including imprecise information, overt hallucinations, problematic oversights, and vague language that would typically render it unsuitable for rigorous academic discussion. However, Generative AI can present us with viable, impactful ideas for improving learning. It is incumbent on us as educators to recognize, evaluate, and develop those ideas for our campuses and communities.

As generative AI (artificial intelligence) technologies, such as ChatGPT, become increasingly available, traditional online assessments must be re-evaluated to maintain their educational value. Open-book online quizzes have long been an effective tool for engaging students, effectively supporting learning, and reinforcing fundamental knowledge and skills. However, the ease of using AI to complete these quizzes may undermine their intended purpose. This article explores the initial findings of using ChatGPT to answer twelve online quizzes used for continuous assessment in two first-year quantitative techniques modules on business programmes in an Irish technological university. ChatGPT, along with suitable plugins, is increasingly accurate in answering the online quizzes, with ChatGPT-3.5 scoring an average of 35%, ChatGPT-4 47% and ChatGPT-4 with Wolfram plugin 78%. Most of the incorrect responses are due to calculation errors; if these are corrected by simply checking the arithmetic with a calculator, the averages increase to ChatGPT-3.5 scoring 72%, ChatGPT-4 76% and ChatGPT-4 with Wolfram plugin 80%. Thus, the online quizzes on these modules can be quickly completed with the assistance of ChatGPT with a high level of success. The implications of this for using online quizzes as an assessment strategy are discussed; potential assessment redesigns are outlined, including how to integrate generative AI into the learning and assessment process in an ethical and constructive manner. Although generative AI provides a challenge to traditional online quizzes, it also has the potential to aid student comprehension and learning, and the skills of prompt engineering are likely to become increasingly relevant and useful.

The aim of this special issue of the Irish Journal of Technology Enhanced Learning is to explore eportfolio in Ireland and further afield. An eportfolio can be a tool or technology, a practice, a pedagogical model, an assessment method and a framework for learning (Chen & Black, 2010). There is growing interest in Ireland in the affordances of eportfolio and their potential to positively impact student learning and achievement. However, there was a dearth of empirical research on eportfolio practice in the context of the Irish educational system. This special issue on eportfolio aims to fill this gap in the literature, and enable us to better appreciate eportfolio practice and ground this in research. Women scholars have been disproportionately affected by the Covid-19 pandemic, in this special issue, the editorial team acknowledged and identified actions we could take to help to mitigate such effects on women scholars. These supports paid off; 83% of the authors in this issue are women. Creating a special issue of a journal takes community and hard work. The editors thank the IJTEL team, and the authors for their support and perseverance during a challenging time. Through this special issue of eportfolio, we are proud to add to the scholarship on eportfolio and to support women scholars during the Covid-19 pandemic.

Increasingly educational providers are being challenged to use their data stores to improve teaching and learning outcomes for their students. A common source of such data is learning management systems which enable providers to manage a virtual platform or space where learning materials and activities can be provided for students to engage with. This study investigated whether data from the learning management system Moodle can be used to predict academic performance of students in a blended learning further education setting. This was achieved by constructing measures of student activity from Moodle logs of further education courses. These were used to predict alphabetic student grade and whether a student would pass or fail the course. A key focus was classifiers that could predict likelihood of failure from data available early in the term. The results showed that classifiers built on all course data predicted student grade moderately well (accuracy= 60.5%, kappa = 0.43) and whether a student would pass or fail very well (accuracy= 92.2%, kappa=0.79). However, classifiers built on the first six weeks of data did not predict failing students well. Classifiers trained on the first ten weeks of data improved significantly on a no-information rate (p<0.008) though more than half of failing students were still misclassified. The evidence indicates that measures of Moodle activity on further education courses could be useful as part of on an early-warning system at ten weeks.

We are living in the information age; our teaching and learning must adapt to this shift (Rosen, 2010). There are over 100 million active users posting over 500 million tweets a day which validates Twitter as an authentic and worthwhile place for literacy development. Twitter offers an educator the opportunity to connect a class to the outside world; it connects the students themselves to a diverse community outside the microcosm of the classroom. This study looks at students’ thoughts on the use of social media – namely Twitter – to enhance the learning of a second language in a post-primary French classroom in Ireland. A controlled group of fifth years students took part in the study. They submitted reflective diaries via email and interviews were conducted and recorded. The results of this study suggests that the use of Twitter in language teaching has a future, but has to be implemented properly and gradually.