JMIR Publications

ABSTRACT

Background:

The rapid development of artificial intelligence (AI) has significantly reshaped the landscape of higher education. While AI offers transformative potential, increasing reliance on these tools by educators raises concerns related to teaching autonomy, decision-making, and the erosion of pedagogical identity. Most existing research has been conducted in Western or Chinese contexts, with limited exploration of cross-cultural perspectives.

Objective:

This study aimed to: (1) explore the underlying causes of educators’ overreliance on AI; (2) investigate the impact of this reliance on teaching autonomy, professional decision-making, and long-term pedagogical practices; and (3) identify challenges associated with AI dependency while proposing strategies to foster balanced AI integration.

Methods:

A qualitative research design was employed. Data were collected from a total of 46 participants through semi-structured interviews and focus group discussion sessions. Participants were selected to represent diverse medical sciences backgrounds and institutional contexts. Thematic analysis was used to interpret the data and identify recurring patterns and themes.

Results:

The analysis revealed several key factors contributing to educators' AI dependency, including pressure to maintain academic reputation, low self-efficacy in adapting to new teaching demands, and institutional policies encouraging AI adoption. The consequences of this dependency included professional skill atrophy, increased procrastination, and reduced interpersonal engagement, leading to social fragmentation within academic communities. However, participants also acknowledged the potential of hybrid intelligence and the value of integrating AI into teaching in a balanced and reflective manner.

Conclusions:

The study highlights the nuanced implications of AI reliance in higher education, emphasizing the need for intentional, balanced approaches to AI use that preserve human agency and pedagogical integrity. Although the sample size was limited, the findings offer valuable insights and set the stage for future research across broader and more diverse educational contexts.AI dependency, Generative AI, procrastination, AI reliance, hybrid intelligence