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Generative Artificial Intelligence in Instructional System Design

Dae Seok Chai et al.

Human Resource Development Review2025https://doi.org/10.1177/15344843251320256article
ABDC B
Weight
0.53

Abstract

The current study aims to present and synthesize extant studies across various fields that have discussed the use of generative artificial intelligence (GAI) in instructional procedures or processes. This study adopted the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model since it is the most widely used instructional and training design model. An integrative literature review of 71 articles was conducted as the primary methodology. We analyzed and summarized information about (a) the integration and implementation of GAI in each stage of the ADDIE model and (b) suggested uses of GAI based on the model to further leverage what it can offer. Potential ethical concerns and recommendations are also examined for future research and practice using GAI in ADDIE. The study concludes with a discussion and implications for future research and practice.

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https://doi.org/https://doi.org/10.1177/15344843251320256

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@article{dae2025,
  title        = {{Generative Artificial Intelligence in Instructional System Design}},
  author       = {Dae Seok Chai et al.},
  journal      = {Human Resource Development Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/15344843251320256},
}

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Evidence weight

0.53

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.70 × 0.15 = 0.10
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.