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Scholars Journal of Arts, Humanities and Social Sciences | Volume-12 | Issue-05 Call for paper
Measuring the Familiarity, Usability, and Concern towards AI-Integrated Education of College Teachers at the Undergraduate Level
Dr. Sahin Sahari
Published: May 15, 2024 | 33 29
DOI: 10.36347/sjahss.2024.v12i05.002
Pages: 166-176
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Abstract
Artificial Intelligence (AI) holds immense potential to revolutionize education globally. This research paper investigates how undergraduate college teachers in India perceive AI’s role in education and examines the key dimensions such as familiarity, usability, concerns, and challenges. To address this complex issue, researcher adopted a mixed-methods research design, combining both quantitative and qualitative research approaches. Data was collected through a structured online google form survey questionnaire that was administered to the randomly selected 441 sample of undergraduate college teachers in India by stratified random sampling technique from the five different states of the country (West Bengal, Bihar, Jharkhand, Gujrat, & Tripura). Here researcher used the basic descriptive statistics such as mean, median and standard deviations to summarize survey responses. On the other side, inferential statistics, such as ‘Confirmatory Factor Analysis’ and chi-square were used. This mixed approach-based investigation revealed distinct patterns in familiarity, usability, concerns, and challenges among the undergraduate college teachers. Notably, male teachers from private institutions exhibited higher familiarity with AI. On the other side, female teachers and private undergraduate college teachers demonstrated more favourable perceptions of AI’s usability in education. But concerns, especially regarding privacy and security, were more pronounced among female teachers. Challenges were also highlighted, with a shared dissatisfaction among undergraduate college teachers concerning institutional support, while technical support and infrastructure issues loomed large. Confirmatory Factor Analysis (CFA) validated positive relationships between familiarity and both usability and concerns, emphasizing the vital role of enhancing AI knowledge to shape perceptions positively and reduce concerns.