Five key ideas exist in the area of Artificial Intelligence: Perception, Representation and Reasoning, Learning, Natural Interaction and Societal Impact. This research project aims to consider the contribution (positive and negative) of AI in the field of education and address the ‘readiness’ of Teacher Education to utilise AI as a tool for supporting student teachers’ development in teaching and learning.

It is acknowledged that Generative-AI (GAI), such as ChatGPT, lacks the ability to provide criticality, depth and accuracy needed for Masters level writing on PME and PGCE programmes, however as a tool for providing formative feedback or acting as an ‘intelligent tutoring system’, AI could offer exciting opportunities in terms of supportive, personalised, ‘just-in-time’ assistance to student teachers if they were taught properly in how to use generative-AI tools. However this goal requires student teachers to be confident and comfortable in the ethical and effective use of AI. Luckin et al. (2022) refer to “AI Readiness” as the journey that students (and faculty) must take to move from a lack of understanding about the nature of AI and its potential, to comprehending AI’s capabilities and shortcomings, with an awareness of the ethical, social and legal implications of engaging with such a complex technology (Harvard Business Review, 2023). This research study addresses DigiComp 2.2 – the European Digital Competence Framework (Vuorikari et al., 2022) - which was updated in 2022 to include a competence focusing on knowledge, skills and attitudes related to citizens interacting with AI systems, as opposed to technical knowledge about AI itself.

● What are student teachers’ attitudes towards AI and GAI?

● What is the connection between AI anxiety and learning motivation?

● What AI is currently be utilised for educational purposes?

This research project aims to investigate the integration of artificial intelligence (AI) in Initial Teacher Education (ITE) programs, focusing on student teachers in two partner institutions in two neighbouring countries. The study will unfold in three phases, employing an exploratory sequential mixed methods approach. In Phase 1, a literature-based review will identify various types of AI implementation in curricula. The analysis will be aligned with the 5 key ideas of AI, guiding the development of materials for the AI Readiness Journey, intended for online delivery. Moving to Phase 2, the AI-Readiness Journey in ITE will commence with a survey gauging student teachers' attitudes towards AI before undertaking the journey. Building on previous work regarding Technology Readiness, the survey will incorporate an AI Attitude scale. This phase aims to correlate AI attitudes with measures of Technology Readiness, following research by Schepman & Rodway (2022). Participants will engage with AI-Readiness Journey materials to enhance their understanding of AI's potential in education. Phase 3 focuses on Generative-AI as an Intelligent Tutoring System (ITS). Student teachers will be trained in utilizing ChatGPT (or other Generative AIs) to support their knowledge development in teacher education. This phase specifically targets core terminology, theory-practice links, applications of Generative AI for planning, and reflection. Throughout the study, an analysis of survey data will be conducted using SPSS, while qualitative comments will undergo thematic analysis based on Braun & Clarke's framework (2020). Any patterns discerned across subject disciplines or between the two countries will be reported. Although the participant pool might not support robust inferential statistical analysis, this option remains open depending on uptake in Phases 2 and 3. The research aims to shed light on the integration of AI in teacher education and its impact on student teachers' attitudes and readiness.

The project's focus on identifying models of AI practice in schools across Northern Ireland (NI) and Ireland is expected to yield valuable insights into the diverse landscape of AI applications in curriculum-based learning. The cross-border cooperation among researchers is crucial in navigating the rapidly changing technological landscape and providing alternative perspectives. The AI-Readiness Journey materials will be instrumental in showcasing how Generative-AI (GAI) can serve as an Intelligent Tutoring System (ITS), supporting student teachers' pedagogical practices during school-based placements. Initial findings suggest the transferability of ITS processes across curricula in both regions and within Europe, emphasising the potential harmonisation of AI implementation in teacher education. The expected outcomes of the project include substantial capacity building in Initial Teacher Education (ITE) programs, primarily benefiting student teachers and potentially extending to teachers in placement schools. Measurable outcomes, such as exemplars of AI in the curriculum, an online AI-Readiness Journey toolkit, and examples of GAI as an ITS, will be shared electronically. These resources aim to modernise ITE programs, providing practical skills in AI and GAI for future educators. Student teachers stand to gain awareness and practical skills in AI and GAI usage, fostering a community of practice within their institutions. Policymakers, including Ireland's Teaching Council and NI's Education Authority, are positioned to receive valuable insights for policy formulation. Institutional benefits extend to the modernization of ITE programs, potentially impacting placement schools through capacity building. The project's outcomes are expected to be well-received, fostering interest and enthusiasm for experimenting with new AI technologies without fear of failure. This approach aligns with the overarching goal of enhancing AI literacy in teacher education, benefiting not only the immediate participants but also the wider academic community across the island of Ireland and Europe.

Braun, V., & Clarke, V. (2020). Thematic Analysis: A Practical Guide. Sage Publications. Luckin, R., Pritchard, A., Ainsworth, S., Akpan, J., & Law, N. (2022). Artificial Intelligence and Education - A summary of the discussions at the Global Education Leaders’ Partnership AI in Education Symposium. Harvard Business Review. https://hbr.org/sponsored/2022/05/artificial-intelligence-and-education Schepman, A., & Rodway, P. (2022). Exploring the Relationship between Attitudes towards Artificial Intelligence and Technology Readiness. Journal of Technology in Human Services, 40(1), 55–75. https://doi.org/10.1080/15228835.2022.2068361 Vuorikari, R., Kankaanranta, M., Ala-Mutka, K., Bacigalupo, M., & Manganello, F. (2022). DigiComp 2.2 - The Digital Competence Framework for Citizens with eight proficiency levels and examples of use (Joint Research Centre Science for Policy Report). Publications Office of the European Union. https://publications.jrc.ec.europa.eu/repository/bitstream/JRC109361/jrc109361_2017%20digcomp%202.2.pdf