The Effect of Artificial Intelligence–Based Instruction of Geographical Concepts on the Cognitive and Affective Performance of Secondary School Students: A Quasi-Experimental Study in Kirkuk, Iraq

Marwan  Khalaf Mohammed Mohammed; Yousef Adib; Hossein  Dehghanzadeh; Davood  Tahmasebzadeh

Authors

Marwan Khalaf Mohammed Mohammed PhD Student, Department of Curriculum Planning, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran Author https://orcid.org/0009-0001-9217-0802
Yousef Adib Professor, Department of Educational Sciences, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran https://orcid.org/0000-0002-3329-6202
Hossein Dehghanzadeh Assistant Professor, Department of Educational Sciences, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran Author https://orcid.org/0000-0002-0561-113X
Davood Tahmasebzadeh Professor, Department of Educational Sciences, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran Author https://orcid.org/0009-0001-2149-464X

Keywords:

Artificial Intelligence, Geography Education, Cognitive Performance, Affective Performance, Secondary School Students, Quasi, Experimental Study, Kirkuk

Abstract

Purpose: This study aimed to investigate the effect of artificial intelligence–based instruction of geographical concepts on the cognitive and affective performance of secondary school students in Kirkuk, Iraq.

Methods and Materials: A quasi-experimental pretest–posttest design with an experimental and a control group was employed. The study population consisted of third-grade secondary school students at Halwa School in Kirkuk during the 2025–2026 academic year. Using convenience sampling, 70 students were selected and assigned to an experimental group (n = 35) and a control group (n = 35). The experimental group received an eight-session AI-based geography instructional program incorporating educational chatbots, digital maps, interactive activities, map analysis, geographic problem solving, GPS and GIS concepts, and immediate feedback, while the control group received conventional instruction. Cognitive performance was assessed using a 30-item researcher-developed Geography Achievement and Geographical Thinking Test with a maximum score of 40 (CVR = 0.84, CVI = 0.90, Cronbach's α = 0.86). A 15-item five-point Likert Affective Performance Questionnaire was used to assess interest and motivation, academic self-efficacy, learning anxiety, participation, and positive attitudes (CVR = 0.82, CVI = 0.89, Cronbach's α = 0.85). Data were analyzed using MANCOVA and ANCOVA after verifying relevant statistical assumptions.

Findings: After controlling for pretest scores, ANCOVA revealed a significant effect of instructional group on cognitive performance, F(1, 67) = 65.34, p < .001, partial η² = .494. A significant effect was also found for affective performance, F(1, 67) = 62.51, p < .001, partial η² = .483. Pretest scores were significant covariates for both cognitive performance, F(1, 67) = 14.87, p < .001, partial η² = .182, and affective performance, F(1, 67) = 13.24, p < .001, partial η² = .165.

Conclusion: AI-based instruction of geographical concepts significantly improved both cognitive and affective performance compared with conventional teaching, indicating that structured integration of AI-supported tools, digital geographic resources, interactive problem solving, and immediate feedback can enhance learning outcomes in secondary geography education.

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The Effect of Artificial Intelligence–Based Instruction of Geographical Concepts on the Cognitive and Affective Performance of Secondary School Students: A Quasi-Experimental Study in Kirkuk, Iraq

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