Research Article
Ravi Sankar Pasupuleti, Deevena Charitha Jangam, Sai Manideep Appana, Venkateswarlu Nalluri, Deepthi Thiyyagura
CONT ED TECHNOLOGY, Volume 18, Issue 1, Article No: ep621
ABSTRACT
The advent of artificial intelligence (AI) has had a profound impact on the education sector, resulting in a transformative change in higher education worldwide. One such change is the usage of AI tools by teachers to enhance their teaching practices, including content creation, sharing, and personalized learning. Those certain obstacles persist for teachers while fully exploring the potential of AI and its adoption in teaching practices. An extensive review of the literature revealed a significant research gap in developing a comprehensive study to examine the influence of AI relevance and its readiness, performance expectancy (PE), and effort expectancy (EE) in shaping behavioral intention (BI) for AI adoption in teaching. Therefore, drawing cues from the unified theory of acceptance and use of technology a research framework was developed to examine these intricate relationships. We gathered data by administering a survey to higher education teachers across various educational organizations in India. Structural equation modeling (SEM) was employed to analyze the collected data and test the hypothesized relationships. The results uncovered a positive association between teacher’s perceptions of AI’s relevance and their readiness to adopt AI, with both factors positively influencing their BI. Furthermore, this study found that EE exhibited a significant positive effect on both BI and PE. This study discusses theoretical and practical implications, underscoring the importance of raising awareness about AI’s relevance, and lays the groundwork for further exploration in this emerging area, intending to inform strategies and interventions to support successful AI adoption in educational organizations.
Keywords: artificial intelligence, AI adoption, relevance, readiness, SEM, higher education
Research Article
Filomachi Spathopoulou, Konstantinos M. Pitychoutis, Stavros Papakonstantinidis
CONT ED TECHNOLOGY, Volume 17, Issue 4, Article No: ep600
ABSTRACT
The rapid advancement of artificial intelligence (AI) is transforming higher education, impacting pedagogical practices, administrative processes, and faculty engagement with technology. While AI holds promise to enhance learning and streamlining operations, its adoption remains complex and debated. This study examines faculty perceptions of AI integration, focusing on factors such as teaching experience, institutional context, and disciplinary specialization. Using a quantitative survey, the research explores AI engagement across institutions and disciplines, analyzing how demographic factors influence adoption. Findings suggest that junior faculty and those in technology-driven environments demonstrate higher AI confidence and adoption, whereas senior faculty engage in AI leadership yet express skepticism about its pedagogical applications. Disciplinary differences reveal that faculty in content-based fields view AI as a teaching tool, while those in applied disciplines utilize it more strategically for administrative and leadership functions. The study also addresses ethical and institutional challenges, including concerns over data privacy, algorithmic bias, and institutional readiness. By identifying these barriers, the research highlights strategies for fostering AI literacy, professional development, and ethical implementation in higher education. This study contributes to the discourse on AI in academia by presenting an educator-centered perspective, bridging the gap between technological advancement and pedagogical practice. The findings provide academic leaders and policymakers with insights on creating AI-inclusive environments that align with faculty needs, uphold ethical standards, and enhance student learning outcomes.
Keywords: artificial intelligence, faculty perceptions, pedagogical practices, AI adoption, ethical challenges, institutional readiness