The Effect of Artificial Intelligence-Based E-Learning Environment on Students' Attitudes Towards Science Course

Burcu Alan; Fikriye Kırbağ Zengin

doi:10.15869/itobiad.1574248

EN TR

Öz

The Effect of Artificial Intelligence-Based E-Learning Environment on Students' Attitudes Towards Science Course

Abstract

This study aims to examine the effects of e-learning environments prepared according to multiple intelligence fields determined by artificial intelligence in science teaching on the attitudes of 5th-grade students towards the science course and to obtain the students' opinions. The study was conducted within the framework of mixed methods. Conducted in the 2022-2023 academic year, the research involved 130 students (58 girls and 72 boys) from one experimental and three control groups at a secondary school in Elâzığ. Quantitative data were collected using the "Science Course Attitude Scale," while qualitative data were gathered through semi-structured interviews. SPSS 23 package program was utilized for quantitative data analysis, performing a One-Way ANOVA, while qualitative data underwent content analysis. Over eight weeks (four hours weekly), the website created for the study first identified the dominant intelligence types of experimental group students. They then received training on the "Matter and Change" unit in an e-learning environment tailored to their intelligence types. In contrast, control groups followed the standard curriculum with teacher-led lessons. The ANOVA results indicated no statistically significant difference in science course attitude scores between the experimental and control groups. However, interviews with experimental group students revealed that their interest, desire, curiosity, and motivation toward the science course increased. They highlighted that the platform tailored to their dominant intelligence types provided benefits such as personalized learning, ease of learning, enjoyable experiences, a positive attitude towards the subject, and an engaging, that is free of boredom learning environment.

Keywords

Artificial Intelligence , Machine Learning , Multiple Intelligence Theory , Science Education , E-Learning , Science Attitude

Yapay Zeka Tabanlı E-Öğrenme Ortamının Öğrencilerin Fen Dersine Yönelik Tutumları Üzerine Etkisi

Öz

Bu çalışmanın amacı, fen öğretiminde yapay zekâ ile belirlenen çoklu zekâ alanlarına göre hazırlanmış e-öğrenme ortamlarının, 5.sınıf öğrencilerinin fen dersine yönelik tutumlarına etkisinin incelenmesi ve öğrencilerin görüşlerinin alınmasıdır. Çalışma, karma yöntem çerçevesinde yürütülmüştür. Çalışma, 2022-2023 eğitim öğretim yılı Elâzığ iline bağlı bir ortaokulda öğrenim görmekte olan biri deney, üçü kontrol olmak üzere 58 kız, 72’si erkek toplamda 130 öğrenci ile gerçekleştirilmiştir. Çalışmanın nicel verileri “Fen Dersine Yönelik Tutum Ölçeği” ile toplanırken, nitel verileri yarı yapılandırılmış mülakat ile toplanmıştır. Nicel verilerin analizinde SPSS 23 paket programı kullanılmıştır ve Tek Yönlü Varyans Analizi (ANOVA) yapılmıştır. Çalışmanın nitel verileri ise içerik analizi ile değerlendirilmiştir. Çalışma sekiz haftada (haftada dört saat) tamamlanmıştır. Çalışmaya özel olarak tasarlanan web sitesinde öncelikle deney grubu öğrencilerinin her birinin baskın zekâ türü belirlenmiş ardından ise baskın zekâ türlerine uygun olarak hazırlanmış e-öğrenme ortamında “Madde ve Değişim” ünitesine yönelik eğitim almaları sağlanmıştır. Kontrol gruplarında ise mevcut öğretim programına uygun, öğretmen eşliğinde dersler normal seyrinde işlenmiştir. Çalışmanın ANOVA sonuçlarına göre; deney grubu öğrencilerinin fen dersine yönelik tutumları ile kontrol gruplarının fen dersine yönelik tutumlarının arasında deney grubu lehine anlamlı bir farklılık tespit edilmemiştir. Uygulama sonrasında deney grubu öğrencileri ile yapılan mülakat sonuçlarında ise öğrenciler fen bilimleri dersine yönelik; ilgi, istek, merak ve motivasyonlarının arttığını sıklıkla dile getirmişlerdir. Ayrıca, platformun baskın zekâ tipine uygun olarak hazırlanmış olmasının kişiselleştirilmiş öğrenme, kolay öğrenme, eğlenerek öğrenme, derse karşı olumlu tutum geliştirme, başarıya katkı sağlama, dikkat çekici olma ve sıkılmadan öğrenme gibi birçok açıdan avantaj sağladığını da belirtmişlerdir.

Anahtar Kelimeler

Yapay Zekâ , Makine Öğrenmesi , Çoklu Zekâ Kuramı , Fen Bilimleri Eğitimi , E-Öğrenme , Fen Tutum

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Details

Primary Language

English

Subjects

Turkish and Social Sciences Education (Diğer)

Journal Section

Research Article

Authors

Burcu Alan ^*
0000-0003-3429-0942
Türkiye

Fikriye Kırbağ Zengin
0000-0002-0547-8746
Türkiye

Early Pub Date

September 15, 2025

Publication Date

September 30, 2025

Submission Date

October 26, 2024

Acceptance Date

September 8, 2025

Published in Issue

Year 2025 Volume: 14 Number: 3

DOI

https://doi.org/10.15869/itobiad.1574248

IZ

https://izlik.org/JA46AN78KG

APA

Alan, B., & Kırbağ Zengin, F. (2025). The Effect of Artificial Intelligence-Based E-Learning Environment on Students’ Attitudes Towards Science Course. İnsan Ve Toplum Bilimleri Araştırmaları Dergisi, 14(3), 1253-1274. https://doi.org/10.15869/itobiad.1574248

Cited By

Sosyal Bilimlerde Yapay Zekâ İzleri: Bibliyometrik Bir Analiz

İnsan ve Toplum Bilimleri Araştırmaları Dergisi

https://doi.org/10.15869/itobiad.1731080

Journal of the Human and Social Science Researches is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY NC).

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