The Impact of Generative Artificial Intelligence on Learning Outcomes of College Students: A Meta-Analysis Based on Instructional Design

Abstract

The rapid iteration of generative artificial intelligence has provided a technological driver for innovation in higher education. However, there is still controversy among researchers regarding whether generative artificial intelligence can improve college students' learning outcomes, and it is unclear how generative artificial intelligence can be effectively integrated into instructional design. Therefore, this study systematically analyzed 32 relevant experimental or quasi-experimental studies from the instructional design perspective using the meta-analysis approach. The results showed that the teaching application of generative artificial intelligence had a moderately positive impact on the learning outcomes of college students. It has shown certain positive effects under different teaching content, teaching resources, teaching modes and teaching evaluation. Moreover, the learning organization form, teaching period and sample size had a significant moderating effect on the learning outcomes of generative artificial intelligence. Based on this, the study put forward some suggestions on the integration of generative artificial intelligence into teaching, in order to provide reference for educators to further practice.

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