Machine Learning Meets Pedagogy: ChatGPT's Transformative Potential in Higher Education Learning Spaces - FX. Risang Baskara (Hasanuddin University, 2024)
In an era marked by rapid technological advancements intersecting with educational practices, the current inquiry focuses on the transformative potential of machine learning models, specifically ChatGPT, within higher education learning environments. Central to the discourse is the question: To what extent can ChatGPT function as a transformative tool in these educational spaces? While existing literature ventures into the capabilities of ChatGPT for simplistic tasks such as text generation, a comprehensive argumentative review that scrutinises its pedagogical applications remains conspicuously absent. This lacuna in academic scholarship necessitates the present study, which employs a multidisciplinary framework incorporating active learning theories, blended pedagogical models, and critical pedagogy. Through a meticulous dissection of empirical evidence, the investigation reveals ChatGPT's potential to enhance student engagement, enriching the curriculum and posing new ethical considerations. Significance emanates from the nuanced understanding and critical appraisal of ChatGPT's role, limitations, and ethical dilemmas in higher education, thereby contributing to a burgeoning field at the intersection of machine learning and pedagogy.