The Effectiveness of an Artificial IntelligenceBased Learning Environment in Developing Academic Achievement, Decision-Making Skills and Attitude towards Technology Among the Female Students of the College of Education at King Khalid University Considering of Kolb's Model

Author

Associate professor of Education Technology College of Education King Khalid University- Kingdom Saudi Arabia

Abstract

The current study aimed to identify the effectiveness and impact of a learning environment based on artificial intelligence in the light of the Kolb model in developing achievement and in developing decision-making skills and the trend towards technology among female students of the College of Education at King Khalid University.
    To achieve the objectives of the research, the quasi-experimental approach was applied using two groups, one of them was a control group consisting of (30) students and the other was an experimental group consisting of (32) students, with the use of achievement test tools, decision-making scale, and technology orientation scale.
The results resulted in the presence of a statistically significant difference at the level of significance (0.05) between the mean scores of the experimental group students who studied in the learning environment based on artificial intelligence in the light of the Kolb model and the scores of the control group students who studied in the traditional way in each of the achievement test, decision-making skills and direction towards technology.
The results also revealed a statistically significant difference for the level of influence of the independent variable, the learning environment based on artificial intelligence, in the light of Kolb's model, on each of the dependent variables on cognitive achievement, decision-making, and attitude toward technology.

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Volume 96, Issue 96 - Serial Number 1
مناهج وطرق التدریس ( اللغة العربیة- الإنجلیزیة – الفرنسیة – الریاضیات – العلوم- الفنون- الاقتصاد المنزلی- التجاری ... )
April 2022
Pages 1-45
  • Receive Date: 05 March 2022
  • Revise Date: 07 March 2022
  • Accept Date: 27 March 2022