AI evidence extraction

Conversational AI agents in education: an umbrella review of current utilization, challenges, and future directions for ethical and responsible use

Amrita Ganguly, Nafisa Mehjabin, Aqdas Malik, Aditya Johri · AI and Ethics · 2025

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

6/10

Relevance

0/4

Quality (LMQS)

Evidence

Citations

6.72

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1007/s43681-025-00916-0

Methodology & findings

Study design

Umbrella review following PRISMA framework.

Primary method

Systematic review methodology (umbrella review with thematic analysis)

Main result

The results show that "CAI utilization is concentrated in pedagogical applications such as teaching support, psychological engagement, and metacognitive development, while administrative functions, research assistance, and specialized training remain underdeveloped." Additionally, "Technical limitations and concerns with educational impact dominate discussions. Ethically, human-AI relationship concerns persist across all CAI generations, while academic integrity and data privacy represent emerging areas of concern."

Research paradigm

Positivist/systematic evidence synthesis

Author conclusions

"The article concludes by proposing a roadmap for ethical CAI implementation in education and identifying priority areas for future research." The authors emphasize that while CAI has significant potential in educational contexts, there is a critical need for comprehensive frameworks to guide ethical and responsible deployment, particularly given persistent concerns about human-AI relationships, academic integrity, and data privacy.

Risk of bias

Publication bias (reviews may favor published studies); Selection bias in included review articles; Heterogeneity in reviewed studies' methodologies; Language bias (database restrictions may exclude non-English sources)

Open questions raised

Lack of end-to-end design guidance for CAI in education
Weak CAI-specific usability methods
Unclear pedagogical guidance and classroom implementation strategies
Limited AI literacy support
Underdeveloped administrative functions and research assistance applications
Need for ethical CAI implementation roadmaps

Data: not_statedCode: not_statedExtracted from: pdfAgreement 70%

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