AI evidence extraction

Generative AI: is it a paradigm shift for higher education?

Xianghan O’Dea · Studies in Higher Education · 2024

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10

Relevance

1/4

Quality (LMQS)

Evidence

110

Citations

38.62

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1080/03075079.2024.2332944

Methodology & findings

Study design

Narrative review and special issue introduction synthesizing literature on Generative AI in higher education; includes literature overview, gap identification, and thematic organization of contributed papers.

Main result

The paper identifies that "GenAI has become increasingly popular with many staff and students" and provides an overview of both the "opportunities and challenges of using Generative AI (GenAI), in particular, text generators in higher education learning and teaching." The special issue aims to serve as a resource for understanding the current state of GenAI in higher education.

Reports effect sizes.

Research paradigm

Interpretivist/Critical realism

Author conclusions

The authors conclude that "this special issue aims to serve as a valuable resource for higher education stakeholders, such as students, practitioners, researchers and managers" and "We hope this collection will help advance knowledge and future research, encourage innovation and inform evidence-based policy and practices in the field of Generative AI in higher education."

Open questions raised

The paper identifies gaps in understanding GenAI applications in higher education, noting the need for "insights into future research" and stating that "this special issue provides an overview of the current state of the field" to address these gaps.
The paper identifies gaps in understanding GenAI in higher education by "identifying the gap and framing the special issue relating to the gaps." The authors note that despite GenAI's increasing popularity, there is a need for systematic exploration of opportunities and challenges, and call for future research to advance knowledge in this emerging field.
The paper identifies a gap in the literature regarding Generative AI applications in higher education and frames the special issue as addressing this gap. It notes the need for future research to advance knowledge in how GenAI can be effectively integrated into higher education learning and teaching.

Data: not_statedCode: not_statedExtracted from: pdfAgreement 74%

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