Assessing the Effectiveness of Artificial Intelligence in the Implementation of Teaching Methods in Primary Education

Document Type : Original Article

Authors

1 Assistant Professor, Department of Mathematics Education, Farhangian University, Tehran, Iran

2 Assistant Professor, Department of Persian Language and Literature Education, Farhangian University, Tehran, Iran.

10.22091/jrim.2025.13691.1363

Abstract

The aim of this study is to investigate the impact of artificial intelligence (AI) on the implementation of teaching methods. The main research question is whether AI can effectively assist primary school teachers as an intelligent assistant in carrying out the stages of instructional methods. This study was designed and conducted using a mixed-methods approach in three phases. In the first phase, ten modern teaching methods were selected based on specific criteria such as active learning, student participation, group activities, and continuous feedback; their characteristics were extracted. In the second phase, the effectiveness of AI as a teacher assistant in implementing instructional methods was qualitatively examined and analyzed. Given that the research focuses on the facilitating role of AI in supporting teachers’ instructional tasks, a series of questions were posed to AI chatbots involving the provision of strategies and suggestions for each teaching stage. The AI's performance was then analyzed through the lens of this teacher-AI interaction. In the third phase, both qualitative and quantitative findings were analyzed and interpreted. Findings revealed that out of 55 instructional stages examined, AI demonstrated the ability to provide effective collaboration and useful suggestions in 32 stages (58%). An analysis of content generated by AI chatbots in the context of teaching sixth-grade mathematics and first-grade Persian demonstrated that this technology can provide meaningful and effective support to educators across various stages of instructional implementation.

Keywords

References

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History

  • Receive Date: 26 August 2025
  • Revise Date: 07 September 2025
  • Accept Date: 10 September 2025

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