AI Integration
Asynchronous Session
Artificial Intelligence in Teacher Education: Exploring Pre-Service Teachers' Perspectives Through Creative Music Projects View Digital Media
Paper Presentation in a Themed Session Sandrina Milhano
This study examines the use of Artificial Intelligence (AI) in the initial training of teachers through the development of creative musical projects. The integration of AI into pedagogy has emerged as a significant trend, and the field of teacher education is no exception. This research adopts an interpretive and exploratory approach to examine how pre-service teachers and educators perceive the contributions of AI to their creative music practices. As part of their training program, pre-service teachers used software tools and AI music generators to experiment with sound and compose music for their creative music projects. Thematic analysis was conducted, focusing on insights drawn from individual reflections at the end of the training process and from group e-portfolios documenting their collaborative work. The study addresses three main research focuses: a) the challenges encountered during group music creation processes, comparing work with and without the use of generative music AI; b) the contributions and opportunities these music creation processes provided for professional teacher development; and c) how generative music AI may influence pedagogical practices in music education, particularly regarding its potential to foster creativity and autonomy, as well as its limitations. The implications of this study aim to contribute to the ongoing reflection and discussion on knowledge construction and professional learning processes in teacher education. Moreover, the study provides insights into pedagogical approaches for integrating AI into music education within teacher training programs.
AI as a Means to Enrich Language Acquisition and Engage Learners: Harnessing AI to Personalize and Better Language Learning View Digital Media
Paper Presentation in a Themed Session Tal Levy
As language instructors, we constantly seek new and better ways to support the acquisition of target languages. We know that each student is different and has different needs. We also know that intrinsic motivation alone is not enough, but due to technological developments, today we can deliver a better learning and teaching experience. A few years ago, I was fortunate enough to come across an AI-powered tool for learning English as a foreign language, which provides a personalized and engaging experience for learners, MagniLearn (ML). The tool utilizes an adaptive curriculum that adjusts to the individual needs and abilities of each student, ensuring that the material is always challenging but not overwhelming. One of the key features of the tool is its nano-learning approach, which breaks down the learning process into small, manageable chunks. This allows students to make rapid progress and see the results of their efforts in a short amount of time. The tool also uses data-driven insights to track the progress of each student and provide customized feedback and recommendations. This helps students identify areas where they need to focus their efforts and provides them with the support they need to succeed. I demonstrate how ML is designed to provide a highly effective and engaging experience for learners of all levels. I suggest how to combine it with existing course content and will show some of its features. My research also demonstrates students’ insights as well as best practices.
Harnessing GenAI: Harnessing GenAI: Integrating AI tools in Academic Writing View Digital Media
Paper Presentation in a Themed Session Karen Eini
The rise of AI in education offers both challenges and opportunities. While students risk becoming overly dependent on AI, potentially diminishing their academic writing and critical thinking abilities, educators can harness these tools to enhance feedback, personalize learning, and improve assessments. This workshop aims to help participants find a balance by using AI to augment the writing process and provide meaningful feedback, ensuring students maintain their roles as independent writers and thinkers. The session will focus on practical applications of GenAI tools, specifically ChatGPT and Brisk, integrated within Google Documents for academic writing instruction. Participants will learn pedagogical workflows developed and tested by the presenter, which facilitate seamless integration of AI-enhanced and teacher feedback in student-created Google Doc portfolios. This approach not only supports continuity and deeper reflection but also provides a comprehensive view of student progress, enriching the writing and revision process. Attendees will learn to use the AI tool Brisk to provide targeted, rubric-aligned feedback directly in Google Docs, making the assessment process more efficient and fostering student development. These methods are based on the presenter’s experiences and continual experimentation in higher education. By combining sound pedagogy with personal and AI-supported assessment, the workshop aims to increase student engagement, boost confidence, and enhance writing skills, while also improving inter-rater reliability and fostering sustained academic interactions. This tested model offers a pathway to responsibly integrating AI in academic writing, optimizing teacher effectiveness and scalability
Beyond the Hype: AI Tools in ESL/EFL Classroom - A Bibliometric Analysis of Research Trends, Ethical Implications, and Evidence-Based Pedagogical Practice View Digital Media
Paper Presentation in a Themed Session Amreet Kaur Jageer Singh
The rapid proliferation of artificial intelligence tools in ESL/EFL classrooms has generated considerable excitement alongside concerns about unsubstantiated claims and promotional hype. While ChatGPT and similar technologies promise revolutionary changes to English language instruction, the field lacks systematic frameworks for distinguishing evidence-based research from marketing-driven discourse. This study addresses the critical need for quality assessment tools to support informed pedagogical decision-making in ESL/EFL contexts. This bibliometric analysis examined 502 peer-reviewed journal articles (2015-2024) from the Scopus database, focusing on AI applications in ESL/EFL classroom settings. Using an integrated approach combining biblioMagika, Biblioshiny, VOSviewer, and AI-enhanced content analysis tools, publication trends, citation patterns, research methodologies, author affiliations, and claim substantiation patterns were analyzed. The multi-tool methodology enabled comprehensive examination of quantitative bibliometric indicators alongside qualitative content analysis, where terminology evolution, evidence-based practice indicators, and promotional language detection across the decade were examined. The findings revealed distinct patterns between evidence-based research and promotional discourse, with significant implications for technology adoption decisions. The analysis identified key bibliometric indicators that distinguish rigorous, classroom-validated studies from potentially inflated claims. Post-ChatGPT publication patterns (2022-2024) showed dramatic volume increases alongside concerning methodological trends. Geographic and institutional analysis revealed varying research quality standards and commercial influence patterns across different contexts. This study provides ESL/EFL educators and administrators with practical frameworks for evaluating AI research credibility, supporting evidence-based technology adoption decisions while offering concrete tools for moving beyond promotional hype toward genuine pedagogical innovation.
