Contribution short abstract:

The article explores ChatGPT in anthropological teaching, focusing on 3 key areas: teacher preparation, student homework, and supervision. It advocates a techno-constructivist approach informed by affordance theory and critical pedagogy that emphasizes active and critical engagement with technology.

Contribution long abstract:

The integration of Large Language Models (LLMs) like ChatGPT into anthropological teaching presents a host of possible changes to educational practices and paradigms. This article identifies three primary avenues of LLM application: teacher preparation, student homework, and student supervision, each offering unique opportunities and challenges. Firstly, the ease of teacher preparation using ChatGPT underscores a tension between educational quality and institutional efficiency. Secondly, ChatGPT can act as a democratizing force in student homework, aiding students in contextualizing theoretical concepts with their lived experiences, yet raises concerns about academic integrity such as the potential for misuse in completing assignments. Thirdly, the potential of ChatGPT in personalized supervision positively echoes traditional apprenticeship models but brings forth questions about the extent to which AI can responsibly guide student learning. To navigate this new digital turn in anthropological education, this paper advocates for a techno-constructivist approach, integrating active learning principles with the transformative role of digital technology. This framework, informed by affordance theory and critical pedagogy, emphasizes critical engagement with technology, understanding its potential and limitations while being acutely aware of its role in shaping new social and political contexts for learning and teaching. Through this lens, the article calls for a balanced, ethically-informed integration of AI in academia, aligning technological advancements with the core values of anthropological education and exploring hybrid educational models.