AI evidence extraction

Artificial intelligence in higher education, opportunities, and challenges: a review

Sharifa AlBlooshi · Frontiers in Education · 2026

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

8/10

Relevance

1/4

Quality (LMQS)

Evidence

Citations

25.26

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.3389/feduc.2025.1683968

Methodology & findings

Study design

Narrative review of literature examining AI's role in higher education, synthesizing research on pedagogical, assessment, ethical, psychological, and institutional governance implications.

Main result

The paper finds that "AI technologies advance rapidly, they present a combination of significant opportunities and complex challenges" in higher education. Key findings include that "Technologies used in new areas, such as adaptive AI-based systems, intelligent tutoring platforms, and generative AI tools, create new opportunities for accessibility and personalization of learning experiences, thereby increasing student motivation." Additionally, "while progress has been made, numerous open questions remain regarding the detection of AI-generated content, including the incorporation of fake narratives into generative AI tools, biases, privacy concerns, and the impact of the technology on our environment."

Research paradigm

Interpretivist/Constructivist

Author conclusions

The authors conclude that "The use of artificial intelligence (AI) presents new opportunities in the field of education, research, and administration. It delivers a more individualized approach to learning for students through accessibility, personalization, and interaction." They further state that "Thus, it is necessary to incorporate comprehensive policymaking that is continually updated for new situations, ethical guidelines that are compelling enough for adoption by everyone in all roles and capacities, teachers who are adequately prepared, a new type of assessment tailored to the AI era, and targeted institutional investments. If these steps are taken, we can sensibly integrate new AI into our teaching environment while equipping students with the skills they need to thrive in an AI-oriented future."

Risk of bias

Selection bias in literature reviewed (narrative review not systematic); Publication bias in cited studies; Potential bias in AI detection tools against non-native English speakers; Confirmation bias in interpretation of AI capabilities and limitations; Selection bias in literature chosen for narrative review (non-systematic approach, no explicit search strategy documented); Potential publication bias (narrative reviews may preferentially cite published studies with positive findings); Author's use of generative AI for grammar checking may influence framing of AI benefits; Single-author review increases risk of interpretive bias without triangulation; Bias in AI detection tools against non-native English speakers; Publication bias in literature selection (non-systematic narrative review); Selection bias inherent in narrative review methodology; Potential institutional bias toward published, English-language sources

Limitations

The paper acknowledges that "Detecting AI-generated texts remains a significant hurdle, as conventional detection systems like Turnitin usually do not perform well in identifying AI texts and often result in false positives or negatives." Furthermore, "a globally applicable detection method is still not available, although research is ongoing and tools are being developed." Additionally, the review notes that "Generative AI detection tools themselves present issues, including false accusations and potential biases" and that "AI detection is fallible due to the variety of writing genres, resulting in both false positives and negatives."

Open questions raised

Detection of AI-generated content and incorporation of fake narratives into generative AI tools
Bias in AI detection systems
Privacy concerns and environmental impact of AI technologies
Policy maturation in many higher education institutions regarding AI governance
Training and preparation of faculty for AI integration
Assessment redesign for the AI era

Extracted from: pdfAgreement 67%

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