Conceptualizations of GenAI and students’ professionalization: Within the multi-layered environment of learning for higher education

As Generative Artificial Intelligence (GenAI) becomes increasingly integrated into higher education, there is a limited understanding of how students perceive this technology and how such perceptions influence learning and the associated systems. This study investigates how students metaphorically conceptualize GenAI, e.g., as a social actor, technique, learning material, or structure, particularly when engaging with a GenAI system designed to enhance intercultural competence, and how these conceptualizations relate to students’ reported learning and professionalization-related reflections. Utilizing a triangulation of qualitative methodologies, namely Content Analysis and Grounded Theory, we identify key metaphors within student reflections and examine their relation to professionalization. In addition, an exploratory quantitative analysis was conducted on a subset of the data to identify structural patterns in metaphor use and professionalization domains. Our findings indicate that students with different orientations toward professional learning tend to incorporate different axial categories when reflecting on their learning experiences with GenAI. Notably, the axial codes related to socio-emotional and technical conceptualizations of GenAI emerged as salient elements in our analysis. The deployment of these codes is associated with more differentiated reflective accounts, in terms of scope and focus, than those observed among students who perceive AI solely as a socio-emotional partner. These findings suggest patterns in how students frame their learning experiences when interacting with GenAI, both as a functional tool and a socio-emotional partner, highlighting variations in how students frame their learning experiences in relation to professional practice. As such, further development of this framing offers implications for the design of learning environments in higher education, in the GenAI era, by promoting more personalized and targeted professional development initiatives.