A rapid review of using AI-generated instructional videos in higher education

Introduction Generative artificial intelligence (AI) has enabled the rapid emergence of AI-generated instructional videos (AIGIVs) as a new form of learning material in higher education. However, evidence on how they are produced, applied, and the reported benefits and risks remains fragmented, highlighting the need for a systematic synthesis. Methods This study conducted a rapid review following PRISMA principles. Studies published from 2023 onward were searched on the Web of Science, Scopus, IEEE Xplore, and Google Scholar. Fifteen eligible studies were analyzed using qualitative content analysis and thematic synthesis. Results Two production modes were identified: fully AI-based video generation (e.g., Sora, HeyGen, Veo) and AI-assisted human-made production (e.g., DALL·E, ChatGPT). Pedagogical applications included using AIGIVs as instructional alternatives and as tools for reflective pedagogy, particularly ethical and critical reflection. Benefits included efficiency and scalability, improved accessibility and personalization, and enhanced emotional engagement and memory. Risks involved ethical concerns, technical limitations, and inauthentic or unreliable content. Discussion AIGIVs show strong potential for higher education, but their value depends on instructional design, human oversight, and responsible governance.

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Publication Details

Journal
Frontiers in Computer Science
Published
2026-01-06
DOI
https://doi.org/10.3389/fcomp.2025.1721093
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
17.70
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article

A rapid review of using AI-generated instructional videos in higher education

Tran Trieu Hai, Duong Thi Thuy Mai, Nguyen Van Hanh
1 citations
Frontiers in Computer Science
Artificial Intelligence in Healthcare and Education
17.70
article

A rapid review of using AI-generated instructional videos in higher education

Tran Trieu Hai, Duong Thi Thuy Mai, Nguyen Van Hanh
article en
1 citations

Abstract

Introduction Generative artificial intelligence (AI) has enabled the rapid emergence of AI-generated instructional videos (AIGIVs) as a new form of learning material in higher education. However, evidence on how they are produced, applied, and the reported benefits and risks remains fragmented, highlighting the need for a systematic synthesis. Methods This study conducted a rapid review following PRISMA principles. Studies published from 2023 onward were searched on the Web of Science, Scopus, IEEE Xplore, and Google Scholar. Fifteen eligible studies were analyzed using qualitative content analysis and thematic synthesis. Results Two production modes were identified: fully AI-based video generation (e.g., Sora, HeyGen, Veo) and AI-assisted human-made production (e.g., DALL·E, ChatGPT). Pedagogical applications included using AIGIVs as instructional alternatives and as tools for reflective pedagogy, particularly ethical and critical reflection. Benefits included efficiency and scalability, improved accessibility and personalization, and enhanced emotional engagement and memory. Risks involved ethical concerns, technical limitations, and inauthentic or unreliable content. Discussion AIGIVs show strong potential for higher education, but their value depends on instructional design, human oversight, and responsible governance.

Frontiers in Computer ScienceVol. 7
Hanoi University of Science and Technology (VN)
Quality Education
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare and Education
17.70
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A rapid review of using AI-generated instructional videos in higher education — Tran Trieu Hai, Duong Thi Thuy Mai, et al. · Frontiers in Computer Science (2026) | TGRS Research Map | TGRS