AI ‐mediated sensemaking in higher education students’ learning processes: Tensions, sensemaking practices, and AI ‐assigned purposes
Open accessAbstract
Despite a proliferation of research on generative artificial intelligence (GenAI) and its applications in higher education (HE), our understanding of the transformative processes where students create productive and ethically grounded uses of GenAI and how AI mediates students' sensemaking is still limited. Based on an empirical investigation of bachelor's degree students from educational sciences ( N = 22) carrying out an inquiry‐based course assignment, we analysed students' reflective essays to explore how GenAI mediated their sensemaking throughout the academic writing process. We selected an abductive analysis as the main approach to examine the AI‐mediated construction of new understanding. Cross‐tabulation analysis complemented qualitative analysis, addressing differences in AI‐mediated sensemaking processes based on students' age. Our findings capture a multidimensional constellation of AI‐mediated sensemaking processes. We found three central dynamics that guided students' sensemaking process: assessing and adapting the textual characteristics of AI‐mediated writing, adjusting and improving interactions with GenAI, and contextualising AI‐mediated academic writing experiences around everyday study practices. The tensions and ambiguities highlighted the ethical aspects of adopting AI‐mediated academic writing practices, although students did not overcome all of these tensions during their sensemaking processes. Our study contributes theoretically by developing the notion of an AI‐mediated sensemaking approach, therefore adding to existing understanding about the dialogical trajectories of AI‐mediated writing processes through which students create new meanings and understandings of GenAI use as a learning resource. Further, we discuss the collective aspects of AI‐mediated sensemaking.
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Interventions in skill development focus on training students to assess the credibility, relevance, and appropriateness of AI-generated content.
“Interventions in this category focus on training students to assess the credibility, relevance, and appropriateness of AI-generated content (Alghazo et al., 2025; Huang et al., 2024; Silvola et al., 2025).”
From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Silvola et al., 2025
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- Authors
- Silvola, A., Kajamaa, A., Merikko, J., & Muukkonen, H.
- Affiliations
- Utrecht University (NL)
- University of Oulu (FI)
- University of Helsinki (FI)
- Corresponding author
- Silvola, Anni
- Venue
- British Journal of Educational Technology
- Publisher
- Wiley
- Published
- 2025-05-21
- Volume
- 56
- Issue
- 5
- Pages
- 2001-2018
- ISSN
- 0007-1013 (ISSN-L)
- 1467-8535
- OpenAlex
- W4410561374
- Cited by
- 24
- References
- 29
- Citations by year
- 2026: 21 · 2025: 3
- FWCI
- 24.85
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- British Journal of Educational Technology (publishedVersion, cc-by-nc)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Työväentutkimus Vuosikirja (submittedVersion)
- Funders
- Suomen Kulttuurirahasto
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Information Systems › Digital Education and Society
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, university students, academic writing, inquiry-based learning, reflective essays, AI ethics, student-AI interaction, age differences, collective sensemaking, dialogical learning
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