arbiter
JournalsAccount

Generative Artificial Intelligence in Higher Education: Mediating Learning for Literacy Development

Sarah Hönigsberg et al.

Communications of the Association for Information Systems2025https://doi.org/10.17705/1cais.05640article
AJG 2ABDC A
Weight
0.44

Abstract

We investigate the integration of generative artificial intelligence (GAI), such as ChatGPT, into higher education courses and assignments to understand how GAI tools mediate learning and support the development of students’ subject and GAI literacy. By investigating the embedding of GAI into educational contexts, we address both the opportunities and challenges of GAI in higher education teaching. Utilizing technology-mediated learning (TML) theory, our case study explores how incorporating ChatGPT and other GAI tools into courses and assignments can enhance learning outcomes, foster interactive and collaborative learning, support critical thinking, and prepare students for professional use of GAI. We examine the role of GAI tools in facilitating learning and reflect on the implications for teachers and higher education institutions. Our findings demonstrate that GAI tools can mediate learning by bridging subject knowledge gaps, enabling adaptive and scalable support, and fostering GAI literacy through hands-on engagement while underscoring the continued importance of human educators in providing critical, ethical, and contextual guidance.

3 citations

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.17705/1cais.05640

Or copy a formatted citation

@article{sarah2025,
  title        = {{Generative Artificial Intelligence in Higher Education: Mediating Learning for Literacy Development}},
  author       = {Sarah Hönigsberg et al.},
  journal      = {Communications of the Association for Information Systems},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.17705/1cais.05640},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Generative Artificial Intelligence in Higher Education: Mediating Learning for Literacy Development

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.