Biography
Dr. Supriya Lamba Sahdev is a results-driven academic leader and international education strategist with over 14 years of experience in establishing and managing more than 500 global institutional partnerships across over 80 countries. Her expertise encompasses Transnational Education (TNE) frameworks, MoU/MoA lifecycle management, student and faculty mobility, and regulatory compliance. She has a proven track record of leading teams, fostering international collaborations, and successfully launching global academic programs. A prolific scholar, Dr. Sahdev has authored over 100 publications, including more than 40 Scopus-indexed works, and holds three patents and an h-index of 8. Her research spans quantitative and qualitative methodologies, incorporating advanced analytical tools such as SPSS, NVivo, Structural Equation Modeling (SEM), Python, and R. She also integrates generative artificial intelligence into institutional strategy, academic research, and scholarly productivity. Dr. Sahdev is an internationally recognized keynote speaker and recipient of prestigious awards for excellence in global education, including the International Achievers Award (2023) and the Exemplary Academic Leader of the Year (2019). Her leadership contributions extend to her role as National President of the Global Education Council (WICCI) and her involvement in leading editorial boards for 15 academic journals. At the forefront of educational innovation, she actively leverages generative AI, agentic technologies, and educational technology platforms to advance curriculum design, institutional strategy, and research productivity. Her professional endeavors reflect a strong commitment to academic excellence, internationalization, technological innovation, and the advancement of global higher education.
Conference contributions 1
FROM ADOPTION TO USAGE FOR RESEARCH AND DECISION MAKING:
The evolving role of generative AI in Indian students opting for international transfer programs (master's abroad)
Purpose: This study investigates the evolving role of generative artificial intelligence (GenAI) in the decision-making journey of Indian students who are researching, evaluating, and applying for international master's programs through International Transfer Programs (ITPs). Moving beyond simple adoption metrics, the study examines how GenAI usage transitions from initial curiosity-driven exploration to instrumental reliance for programme research, university shortlisting, scholarship identification, and application strategy and the attendant sentiments, risks, and information quality concerns that emerge across this trajectory. Design/Methodology/Approach: A mixed-methods approach is adopted. Qualitative data are generated through semi-structured interviews with 28 Indian students who used GenAI tools during their ITP application process. Concurrently, thematic analysis of 1,240 Reddit and YouTube discourse segments from Indian student communities is conducted using Leximancer's Topic Guide software. Findings are interpreted through the Technology Acceptance Model (TAM) extended with information quality, trust, and risk constructs. Findings: Three evolutionary phases of GenAI usage are identified: (1) an admiration phase characterized by enthusiasm for GenAI's ability to synthesize complex programme information and personalize shortlisting recommendations; (2) an instrumental phase in which students deploy GenAI for Statement of Purpose (SoP) drafting, scholarship research, and visa documentation guidance; and (3) an apprehension phase marked by emerging concerns over hallucinated programme data, outdated fee structures, ethical ambiguity in SoP co-creation, and reduced engagement with official university counsellors. Social influence from peer networks significantly mediates GenAI adoption intensity, while perceived information risk moderates the transition from adoption to deep usage. Research Limitations/Implications: The study is confined to Indian students targeting English-speaking destination countries. Longitudinal tracking of actual enrolment outcomes via GenAI-informed decisions is a critical future direction. Practical Implications: International offices, education consultants, and destination universities should develop GenAI-aware advising frameworks that complement rather than compete with students' AI-mediated research behaviour. Indian HEIs offering ITP pathways should leverage GenAI's counselling potential while mitigating misinformation risks through verified AI content pipelines. Originality/Value: This is among the first studies to examine the full arc of GenAI usage from adoption to deep decisional reliance in the specific, high-stakes context of international student mobility and transfer program selection in India. It offers a novel three-phase GenAI usage evolution model grounded in TAM and information quality theory, with direct implications for international education advising practice.