Can Machine Learning Be Taught to Pre-service Teachers in the STEM Fields?

Year 2024, Volume: 5 Issue: 2, 23 - 45

Esma Nur Özen , Elif Polat , Yavuz Samur

https://doi.org/10.52911/itall.1458322

Abstract

Machine Learning (ML) trainings provide students with 21st century skills and enable students to find solutions to their own problems. The purpose of this study is to design, implement, and evaluate ML training for pre-service teachers in the STEM field in order to contribute to the future workforce in the field of computer science. The participants of the study were 74 pre-service teachers who are studying in the departments of Computer Education and Instructional Technology (CEIT), science education, and mathematics education (STEM fields) at a state university in Istanbul. Convenience sampling method was used in the study. In the research, a single-group pre-test-post-test weak quasi-experimental design was used by using the quantitative method in order to evaluate the training by giving ML training. The training was implemented on the online platform for 3 hours for 8 weeks. "Pretest - Posttest Achievement Test," "Online Student Engagement Scale," "Moodle Activity Data," “Demographic Form,” and "Attendance Forms" were used to collect data. There is a significant difference between the pre-test and post-test averages in favor of the post-test. There is a significant difference between the pretest and posttest scores according to the departments. It has been concluded that the provided training is effective in the success of pre-service teachers. It can be suggested to offer training to different branches and to select participants from elementary and middle school students.

Keywords

Machine learning, machine learning instruction, STEM, artificial intelligence, preservice teachers

STEM Alanındaki Öğretmen Adaylarına Makine Öğrenmesi Öğretilebilir mi?

Abstract

Makine öğrenmesi eğitimleri, öğrencilere 21. yüzyıl becerileri kazandırır ve kendi problemlerine çözüm bulmalarını sağlar. Bu çalışmanın amacı, bilgisayar bilimi alanında gelecekteki iş gücünün oluşturulmasına katkıda bulunmak amacıyla STEM alanındaki öğretmen adaylarına yönelik makine öğrenmesi öğretimini planlamak, uygulamak ve değerlendirmektir. Çalışmanın katılımcıları, İstanbul'da bir devlet üniversitesinde 2020-2021 akademik yılında bilgisayar ve öğretim teknolojileri eğitimi, fen eğitimi ve matematik eğitimi (STEM alanları) bölümlerinde öğrenim gören 74 öğretmen adayıdır. Çalışmada elverişli örnekleme yöntemi kullanılmıştır. Araştırmada, makine öğrenmesi eğitimi verilerek eğitimin değerlendirilmesi amacıyla nicel yöntem kullanılarak tek gruplu ön-test-son-test zayıf yarı deneysel tasarımı kullanılmıştır. Eğitim, 8 hafta boyunca çevrimiçi platformda haftada 3 saat olacak şekilde uygulanmıştır. Veri toplama araçları olarak "Ön Test - Son Test Başarı Testi", " Çevrimiçi Öğrenci Bağlılık Ölçeği", "Moodle Etkinlik Verileri", "Demografik Form" ve "Katılım Formları" kullanılmıştır. Ön-test ve son-test ortalamaları arasında son-test lehine anlamlı bir fark vardır. Bölümlere göre ön test ve son test puanları arasında anlamlı bir fark bulunmaktadır. Verilen eğitimin öğretmen adaylarının başarısında etkili olduğu sonucuna ulaşılmıştır. Farklı branşlara eğitim vermek ve katılımcıların ilkokul ve ortaokul öğrencilerinden seçilmesi önerilebilir.

Keywords

Makine öğrenmesi, makine öğrenmesi eğitimi, STEM, yapay zeka, öğretmen adayları.

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