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

Burcu Alan; Fikriye Kırbağ Zengin

Makale detayları

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

Yazarlar:

Burcu Alan | Fikriye Kırbağ Zengin

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Türkçe ve Sosyal Bilimler Eğitimi (Diğer)

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.1253-1274

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001358028

pISSN:

2147-1185

Anahtar kelimeler:

Özet:

 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.

 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.

 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.

 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, 72si 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.

Makale detayları

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

Yazarlar:

Burcu Alan | Fikriye Kırbağ Zengin

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Türkçe ve Sosyal Bilimler Eğitimi (Diğer)

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.1253-1274

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001358028

pISSN:

2147-1185

Artificial Intelligence

Machine Learning

Multiple Intelligence Theory

Science Education

E-Learning

Science AttitudeYapay Zekâ

Makine Öğrenmesi

Çoklu Zekâ Kuramı

Fen Bilimleri Eğitimi

E-Öğrenme

Fen Tutum

Sayı

Makale detayları

Yazarlar: Burcu Alan | Fikriye Kırbağ Zengin

Yayıncı: Mustafa Süleyman ÖZCAN

Ana Başlıklar: Türkçe ve Sosyal Bilimler Eğitimi (Diğer)

Dergi: İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.1253-1274

Belge Tipi: Makale

Yayın Tarihi: 9/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001358028

pISSN: 2147-1185

Sayı

Yazarlar:

Burcu Alan | Fikriye Kırbağ Zengin

Yayıncı:

Mustafa Süleyman ÖZCAN

Ana Başlıklar:

Türkçe ve Sosyal Bilimler Eğitimi (Diğer)

Dergi:

İnsan ve Toplum Bilimleri Araştırmaları Dergisi Vol.14 Issue 3, pp.1253-1274

Belge Tipi:

Makale

Yayın Tarihi:

9/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001358028

pISSN:

2147-1185