Evolving Roles
Comparative Analysis of Feedback on Written Assignments: Google Gemini vs. Co-Pilot and the Role of Prompt Engineering View Digital Media
Paper Presentation in a Themed Session
Irum Naz,
Rodney Robertson
This study compares the effectiveness of two leading AI platforms, Google Gemini and Co-Pilot, in providing feedback on written assignments. As AI tools become integral in education, understanding their strengths and limitations is essential. Grounded in Constructivist Learning Theory, Cognitive Load Theory, and Feedback Intervention Theory, this research evaluates the feedback mechanisms of each AI system. The study also examines the impact of prompt engineering on feedback quality. Using a mixed-methods approach, combining quantitative analysis and qualitative insights from user experiences, the research identifies distinct characteristics of each platform. The findings reveal varying degrees of alignment with educational principles, highlighting the critical role of prompt design in optimizing AI-generated feedback. This study provides valuable insights for educators, developers, and policymakers on utilizing AI technologies to enhance student learning outcomes.
Featured AI as Co-trainer: Exploring the Boundaries of Human-AI Pedagogical Collaborations
Paper Presentation in a Themed Session
Francisca Onaolapo Oladipo
The rise of artificial intelligence (AI) in education presents unprecedented opportunities for transforming teaching and learning processes. As AI shifts from a tool to a collaborator, its potential to co-form, guide, and enhance educational experiences raises essential questions about its role in pedagogy. This paper examines the boundaries of human-AI pedagogical collaborations, discussing how AI can support human educators, adapt to diverse learner needs, and redefine the essence of teaching and mentorship. Case studies and frameworks are presented to highlight the opportunities and challenges in integrating AI as a co-formator in education. The paper answers the following questions: (1) How can AI act as a co-formator in education? (2) What boundaries exist in human-AI pedagogical collaborations? (3) How do we preserve the essence of human mentorship in an AI-enhanced system?
AI in Early Learning Environments: Enhancing Development While Safeguarding Ethics View Digital Media
Paper Presentation in a Themed Session
Jessie Ming Sin Wong
Artificial intelligence (AI) is transforming early childhood education, offering innovative ways to personalize learning, foster inclusivity, and empower educators. This study examines the practical applications of AI in early learning environments, grounded in established theoretical frameworks such as constructivist learning theory, ecological systems theory, and developmentally appropriate practice. It highlights how AI can support diverse learners, detect developmental challenges early, and enhance play-based learning, while also addressing pressing ethical concerns like privacy, algorithmic bias, and the developmental impacts of excessive technology use. Drawing on practice research, the paper provides actionable strategies for integrating AI responsibly. These strategies emphasize developmentally appropriate design, cultural competence, transparency, and ongoing ethical oversight. Through this balanced approach, the study envisions a future where AI enriches early childhood education while safeguarding the rights and well-being of young learners.
Lecturer Perspectives in Using ChatGPT: Insights from Different Generations View Digital Media
Paper Presentation in a Themed Session
Serkan Boyraz
The integration of artificial intelligence (AI) in education is rapidly transforming teaching and learning practices. Among AI tools, ChatGPT has gained significant attention for its potential to assist in content generation, student engagement, and instructional design. However, lecturers’ perspectives on its use may vary depending on generational differences in technology adoption, pedagogical approaches, and digital literacy. This study explores how lecturers from different generations perceive and utilize ChatGPT in higher education. Drawing on qualitative data from semi-structured interviews with lecturers across diverse age groups, we examine their attitudes, concerns, and strategies for integrating AI into their teaching. Findings indicate that while younger lecturers tend to embrace ChatGPT as an interactive and time-saving tool, more experienced lecturers often approach it with caution, emphasizing academic integrity and critical thinking challenges. Additionally, differences emerge in the perceived benefits, such as workload reduction, student support, and curriculum design. The study also highlights concerns regarding AI’s impact on authentic learning and assessment reliability. These insights provide a nuanced understanding of how generational factors influence AI adoption in academia, offering recommendations for professional development and institutional policies. By fostering dialogue between generations, universities can create a balanced approach to AI integration that supports both innovation and academic rigor.
