The Descriptive Analysis of the Articles Published in the Web of Science Database Between the Years 2016-2019 Context on Learning Analytics

Abstract

Big data is regarded as one of the fundamental factors that can play a role in the future of education. While the data can reveal what the underlying reasons for the student's failure are; It can also provide guidance on what paths successful students should follow to be even more successful. While the concept of analytics in education can be interpreted as understanding learning and optimizing it for education in 2008; Since 2010, learning analytics (LA) has been considered as an independent field within the analytics field within the concept of learning analytics. In this study, articles published in the field of Education / Educational research in SSCI, SCI-Expanded, and A&HCI indexes of the keyword "Learning Analytics" published in Web of Science between 2016-2019 were evaluated. In this context, 575 articles were identified. After the book chapter, the studies that could not be found on the internet and were not considered as articles, 529 articles were examined. Among the review criteria, parameters such as the type of the article, research method, data collection techniques, sample profiles, fields of study, frequently used keywords, suggestions, dependent / independent variables, number of authors / the distribution of languages in which they were written were considered. After the examination, it was determined that the number of experimental studies in the field of learning analytics is high and the field of computer / informatics is preferred primarily as a field of study. The determination of keywords along with the most frequently used dependent and independent variables provided an idea of which subjects the LA studies focused on.

Keywords

• Learning analytics
• Trends in research
• Article review
• Descriptive analysis

Öğrenme Analitikleri Kapsamında 2016-2019 Yıllar Arasında Web of Science Veritabanında Yayınlanan Makalelerin Betimsel Analizi

Abstract

Büyük veri, eğitimin geleceğinde, rol oynayabilecek temel faktörlerden kabul edilmektedir. Veriler, sınıf tekrarına kalan öğrencinin başarısızlığının altında yatan sebeplerin neler olduğunu gün yüzüne çıkarabilirken; aynı zamanda başarılı öğrencilerin daha da başarılı olması için hangi yolları izlemeleri gerektiğine dair yol gösterebilmektedir. Eğitimde analitik kavramı 2008 yılında, eğitime yönelik olarak öğrenmeyi anlama ve onu optimize etme olarak ifade edilirken; 2010 yılından günümüze ise öğrenme analitikleri (ÖA), konsepti dahilinde, bağımsız bir alan olarak değerlendirilmektedir. Bu çalışmada, 2016-2019 yılları arasında “Learning Analytics” anahtar kelimesinin Web of Science’da yayınlanan SSCI, SCI-Expanded, ve A&HCI indekslerinde Eğitim/Eğitim araştırmaları alanında yayınlanan makaleler değerlendirilmiştir. Bu kapsamda 575 makale tespit edilmiştir. Kitap bölümü, internet ortamında bulunamayan ve makale olarak ele alınmayan çalışmalar çıkartıldıktan sonra 529 makale incelenmiştir. İnceleme kriterleri arasında makalenin türü, araştırma yöntemi, veri toplama teknikleri, örneklem profilleri, çalışma alanları, sık kullanılan anahtar kelimeler, öneriler, bağımlı/bağımsız değişkenler, yazar sayıları/yazıldığı dillerin dağılımı gibi parametreler ele alınmıştır. İnceleme sonrasında öğrenme analitikleri alanında deneysel çalışma sayısının yüksek olduğu, bilgisayar/bilişim alanının öncelikle çalışma alanı olarak tercih edildiği tespit edilmiştir. En sık kullanılan bağımlı ve bağımsız değişkenlerle birlikte anahtar kelimelerin tespiti de ÖA çalışmalarının hangi konular üzerine yoğunlaştığına dair bilgi sahibi olunmasını sağlamıştır.

Keywords

• Öğrenme analitikleri
• Araştırmalardaki eğilimler
• Makale incelemesi
• Betimsel Analiz

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