Understanding AI-Driven Teaching: Key Factors Shaping Adoption in Higher Education

Konyn Tuba Lappay, Nimit Sharma, Dr. Shubha A.

Abstract: AI plays a major role in enhancing teaching effectiveness in higher education institutions. The Study aims to identify the major factors leading to adoption of AI-enabled teaching process. The paper explores the various Technological factors, Pedagogical factors, social factors, ethical factors and institutional factors which will influence the teachers in higher education level to adopt AI enabled course content, simulation learning, curated assessments and classroom engagement. It will also be defining the impact of AI in higher education. The study has conceptualized two variables that is independent variable which is Factors like facilitating conditions, awareness, ethical aspects, attitude, faculty perception towards AI enabled class room engagement and independent variable that is effective work management. The study is descriptive in nature and the primary data is used to collect the data, The respondents for the study are Teachers working in institute, college and university level. The data collected is analysed using data analysis tools like Descriptive statistics, Two-way Anova, Spearman rank Correlation, the data will be analysed using SPSS. The findings reveal that factors like awareness, attitude, behavior and facilitating conditions are highly positively related to effective work management whereas ethical aspects has shown lower relationship comparatively.

Keywords: Awareness level, Attitude, facilitating conditions, behavior, Ethical aspects and work engagement