Studying the Effect of Artificial Intelligence on the Performance of Integrated Teaching of StudentTeachers at Farhangian University

Authors

1 PhD in Artificial Intelligence and Robotics,Assistant Professor Farhangian University kashan, Tehran,iran

2 Assistant Professor Farhangian University kashan, Tehran,iran

10.48310/istt.2026.22676.1224

Abstract

Background and Objectives: The growth of digital technologies in recent decades has led to a fundamental transformation in teaching-learning methods and has provided new paths for teacher training. The aim of this study is to study the effect of artificial intelligence on the academic performance of students in integrated education.

Methods: This study was a quasi-experimental study with a pre-test-post-test design with a control group and was an applied research in terms of its purpose. The statistical population of this study included 375 students at Farhangian University of Kashan in the academic year 1404-1405. To select the sample, 60 undergraduate students were selected through convenience sampling. This number of people were randomly assigned to two experimental groups (30 people) and a control group (30 people). The data collection tool was the integrated education test (theoretical knowledge, production skills, and professional knowledge). The use of artificial intelligence in this study was implemented on the students of the experimental group during 10 sessions of 60 minutes. The analysis of covariance test was used to analyze the data and test the hypotheses.

Findings: The results of the findings showed that the use of artificial intelligence has a positive effect on the performance of blended teaching of students.
Conclusion: This research presents how to teach artificial intelligence in a practical way to students for the use of professors in teaching and reveals the opportunities and limitations of the use of artificial intelligence in education.

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History

  • Receive Date: 09 April 2026
  • Revise Date: 21 May 2026
  • Accept Date: 06 June 2026
  • First Publish Date: 06 June 2026
  • Publish Date: 22 May 2026

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