Conceptualizations of GenAI and Students' Professionalization: Within the Multi-Layered Environment of Learning for Higher Education

Synthesis: Bohmer, Dillig, Andronache, Beshlei, Bolaji, Isso, Kovaliuk, Mason, Laza Medina, Stanescu, and Yaroshenko (2026) investigate 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 (Content Analysis and Grounded Theory), they identify key metaphors within student reflections and examine their relation to professionalization. An exploratory quantitative analysis identified structural patterns in metaphor use and professionalization domains. Findings indicate that students with different orientations toward professional learning tend to incorporate different axial categories when reflecting on their learning experiences with GenAI, with socio-emotional and technical conceptualizations emerging as salient.

Key Findings

• Students metaphorically conceptualize GenAI in multiple ways — as a social actor, technique, learning material, or structure.
• Students with different orientations toward professional learning incorporate different axial categories when reflecting on their learning with GenAI.
• Socio-emotional and technical conceptualizations of GenAI emerged as salient elements in the analysis.
• Deployment of these codes is associated with more differentiated reflective accounts than those observed among students who perceive AI solely as a socio-emotional partner.
• Findings suggest patterns in how students frame their learning and professionalization in relation to GenAI.

What this means for practice

• Instructors. Have students articulate what GenAI is for them — social actor, technique, learning material, or structure — because students who framed it solely as a socio-emotional partner produced less differentiated reflections on their professional learning.
• Instructors. Design reflection tasks that push beyond the socio-emotional register toward technical and structural framings, since deploying both axial categories accompanied accounts with greater scope and focus.
• Designers. Surface students' conceptualizations inside the learning environment itself, because those framings shape how students frame engagement, trust, and responsibility.
• Faculty developers. Treat metaphor analysis as a diagnostic for professional development: the study's framing supports more personalized and targeted initiatives rather than uniform AI orientation.
• Researchers. Treat cohort-level metaphor counts as exploratory indicators; the study's own quantitative component reports patterns within the dataset rather than generalizable relationships.

Limitations

• The primary data are 67 written student reflections drawn from three countries (United States n = 19, Ukraine n = 4, Germany n = 30) plus one in-person German course (n = 14), and the authors note the representation of these countries is not balanced.
• The authors state the exploratory research rests on a relatively small sample of participants sourced exclusively from three Western countries, so the statistical findings indicate patterns within this dataset rather than generalizable relationships.
• The analyzed groups differ in level — a graduate course versus first-year undergraduates — so observed cohort differences may reflect contextual and linguistic factors rather than differences related to professional practice.
• Coding relied on collaborative efforts within the coder team to establish negotiated agreement; no independent inter-rater reliability statistic is reported for the metaphor categories.

Connected Concepts

• Generative AI
• Learner Identity
• Student Experience
• Higher Education
• Workplace Learning
• Career Development and Readiness
• AI Literacy

Connected Articles

• [fear-awe-genai-metaphor-workshops-2025] — making sense of GenAI through metaphor workshops
• [genai-use-usefulness-student-experience-australia-2026] — student experience of GenAI usefulness
• [lodge-adaptive-capabilities-genai-future-2026] — adaptive capabilities for a GenAI-integrated future

Citation

Bohmer, A., Dillig, M., Andronache, D.-C., Beshlei, O., Bolaji, S., Isso, I., Kovaliuk, Y., Mason, J., Laza Medina, A., Stanescu, M.-H., & Yaroshenko, O. (2026). Conceptualizations of GenAI and students' professionalization: Within the multi-layered environment of learning for higher education. Computers and Education: Artificial Intelligence, 11, 100636.