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T0020


Integrating AI tools in Teaching and Research in Central Asian Higher Education: Its Pitfalls and Prospects  
Convenors:
Mary Bernadette Conde (American University of Central Asia)
Aijamal Sarybaeva (American University of Central Asia)
Aida Aidarova (American University of Central Asia)
Jarkyn Shadymanova (American University of Central Asia)
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Chair:
Chynarkul Ryskulova (American University of Central Asia)
Format:
Roundtable
Theme:
Education

Abstract:

Artificial Intelligence is transforming not only many industries but also education. While its rapid development and applications in business and other sectors of the society are implemented and harnessed, AI in education may seem to have posed a dilemma or a paradox instead: whether or not it supplements or disrupts the existing educational infrastructure and system. In the past year or two, the GenAI tools usage has become a contested issue among colleges and universities across the globe. In Kyrgyzstan, integrating GenAI tools and technologies in instruction and research have become a new normal in many disciplines. Whereas in some liberal arts programs or courses, they require a regulation or policy to limit or allow its usage. Despite its multiple advantages and recent successes in its applications in many courses and fields of disciplines, educators, students, and researchers are often confronted with challenging issues ranging from plagiarism, instructive nature, to ethical issues. This roundtable gathers professors and educators to discuss and share their experiences, perspectives, and insights on how the GenAI tools have impacted their research and pedagogy in the field of liberal arts, history, political science, and sociology in Central Asia. It offers a platform of engagement, explores and details the potential pitfalls and implications, and discusses strategies responsive to some major growing concerns of AI usage, real and perceived. Lastly, the roundtable seeks to explore a framework of mechanisms on how teachers, researchers, and administrators address expectations, issues, and challenges that AI has driven academic or research institutions to keep up with advancing knowledge and skills.