Journal of Applied Learning and Teaching

Artificial intelligence in higher education database (AIHE V1): Introducing an open-access repository

Wed, 17 Apr 2024 00:00:00 -0700

Generative artificial intelligence (GenAI) has fired the world’s imagination. The higher education sector is not immune from the GenAI hype, panic, and mania. The emergence of artificial intelligence, in its newest form, into curriculum, student life, and learning has created an entanglement of technology, people, and learning. Yet, there is still a lack of cohesive accounts of the emergent literature used to inform practical learning and teaching decisions. Our manuscript responds with the deployment of a previously published systematic literature review to create the first version of the Artificial Intelligence in Higher Education Database (AIHE V1). Published in conjunction with this article, we pioneer an open-access resource to support learning and teaching scholars to gain timely access to pre-examined literature on AI and higher education. This first version documents 160 manuscripts published between 30 November 2022 and 31 December 2023. Using a rigorous systematic review method, engaging in the PRISMA approach, we offer a first glance at the metadata of articles published on AI and higher education during the first year of ChatGPT.

Artificial intelligence in higher education database (AIHE V1): https://doi.org/10.37074/jalt.2024.7.1.35D

The Great Resignation: The simple joys of not belonging

Martin Benedict Andrew — Sun, 14 Apr 2024 00:00:00 -0700

As the 2020s march on into a post-COVID age, an increasing trend for academics to exit their current academic positions or to leave academia altogether can be observed internationally and locally. Consequently, a sizeable body of experts accessible to higher education but geographically beyond its ivory towers and psychologically outside its neoliberal grip has come to exist. These para-academics and public intellectuals continue to contribute to communities of teaching, learning, and researching but do so often without affiliation. This study explores the relational link between the archaic notion of affiliation and what it means to ‘belong’ to a university as staff. The study problematises belonging as an assimilative designator of an organisation’s culture and suggests that belonging, as employed in teaching and learning discourse, as a trust-based mode of building community, is a different beast than that conceived by neoliberal universities. Using vignettes as narrative enquiry, the paper retells and curates six accounts of academics making transitions out of academic positions and finding fresh educational contexts for belonging. These emancipatory narratives move through spaces of trauma into authentic places of reclaimed identity, most notably as independent public intellectuals within a broader context of global citizenship. The narratives show us what life after being academically affiliated can look like when individuals exercise critical resilience to establish academic identities beyond the neoliberal university.

Book review of Benedict du Boulay, Antonija Mitrovic, & Kalina Yacef (Eds., 2023). Handbook of artificial intelligence in education. Edward Elgar.

Jürgen Rudolph — Tue, 02 Apr 2024 00:00:00 -0700

Book review of Lindgren, Simon (Ed., 2023). Handbook of critical studies of artificial intelligence. Edward Elgar.

Jürgen Rudolph — Mon, 01 Apr 2024 00:00:00 -0700

Student engagement and fostering ownership of learning

Ajay Khatter, Krishna Thalaachawr, Mark Blyth — Thu, 18 Apr 2024 00:00:00 -0700

This research was undertaken to find pedagogical solutions that help teachers design engaging learning activities and assessments. These solutions aim to increase student engagement, encourage them to take responsibility for their learning in practical training and education settings and effect positive classroom change. An action research methodology was utilised for the researchers to learn through action, increase student engagement, and develop professionally and personally. Action research is a family of research methodologies that pursue action (or change) and research (or understanding) simultaneously using a cyclic or spiral process that alternates between action and critical reflection. This methodology involved action, evaluation, and reflection to gather evidence to implement classroom change. The research found that adopting student-centred teaching practices, such as project-based learning and collaborative activities, has substantially improved student involvement with the learning process. The students who participated in the activities showed increased interest, motivation, and active participation in their educational experiences.

Exploring the future of learning and the relationship between human intelligence and AI. An interview with Professor Rose Luckin

Rose Luckin , Jürgen Rudolph, Martin Grünert , Shannon Tan — Mon, 25 Mar 2024 00:00:00 -0700

Professor Rose Luckin, a pioneer in the integration of artificial intelligence with education, holds the position of Professor of Learner Centred Design at the UCL Knowledge Lab, University College London. Her trailblazing research has profoundly deepened our understanding of AI in education (AIEd). Rose Luckin has authored over 50 peer-reviewed articles and key works, including “Machine learning and human intelligence: The future of education for the 21st century.” As the Director of EDUCATE, she merges academic insights with ed-tech industry innovation. She is the co-founder of the Institute for Ethical AI in Education.

In our interview, Rose Luckin shares her educational awakening and her personal journey into AIEd, addressing gender bias and the unique challenges faced by women in the AI field. She delves into the ethical dimensions of AI deployment in educational settings, underscoring the Institute for Ethical AI in Education’s pivotal role in fostering ethical standards. Professor Luckin advocates for AI’s potential to bolster learner-centred methodologies and stresses the critical importance of forging robust partnerships between educators and technology developers. She evaluates the impact of generative AI on assessment, learning and teaching within K-12 and higher education. She provides insights into AI’s evolving role in education and the imperative of lifelong learning. Emphasising a collaborative ethos among educators, researchers, and developers, Professor Luckin argues for AI’s integration into education within strategically crafted ethics and governance frameworks. Our interview sheds light on AIEd’s current landscape, highlighting the critical need for ongoing research and collaborative efforts in navigating its considerable dangers while seizing opportunities.