ÖĞRENME ANALİTİĞİ DÜZEYLERİ BAĞLAMINDA ÖĞRENME PANELİ TASARIMINA YÖNELİK ÖĞRENEN BEKLENTİLERİNİN BELİRLENMESİ

Yıl 2023, Cilt: 13 Sayı: 1, 161 - 184, 25.01.2023

Mustafa Tepgeç , Halil Yurdugül

https://doi.org/10.17943/etku.1124933

Öz

Bu çalışma, öğrenenlerin öğrenme analitiği düzeyleri bağlamında öğrenme panelinde yer almasını bekledikleri öğeleri keşfetmeyi ve buna uygun tasarım ilkeleri ortaya koymayı amaçlayan bir durum çalışmasıdır. Bu kapsamda daha önce e-öğrenme deneyimi olan 20 lisansüstü öğrencisiyle odak grup görüşmeleri gerçekleştirilmiştir. Odak grup görüşmeleri 5 farklı oturumda gerçekleştirilmiş ve her oturum ortalama 53 dakika sürmüştür. Görüşmelerden elde edilen veriler içerik analizi yöntemiyle çözümlenmiştir. Araştırma sonucunda elde edilen bulgular; dördü öğrenme analitiği düzeyleri (betimleyici analitikler, tanılayıcı analitikler, yordayıcı analitikler, öngörü analitikleri) kapsamında öğrenme panelinde yer alması gereken bilgilere yönelik beklentiler, biri ise bu bilgilerin öğrenme panelinde ne şekilde organize edilip sunulacağına ilişkin beklentiler olmak üzere beş alt başlık altında analiz edilip yorumlanmıştır. Katılımcılar betimleyici analitikler kapsamında öğrenme hedeflerine göre ne durumda olduklarına, gruba/sınıfa göre performanslarının nasıl olduğuna ilişkin bilgiler görmek istediklerini belirtmişlerdir. Tanılayıcı analitikler kapsamında ise katılımcılar öğrenme eksikliklerinin tespiti, performanslarındaki değişimlerin saptanması ve performans ile harcanan zaman ilişkisinin gösterimi ile ilgili bilgileri görmek istediklerini ifade etmişlerdir. Yordayıcı analitikler kapsamında başarı kestirimlerinin sunulması yaygın olarak beklenirken öngörü analitikleri kapsamında buna ek olarak başarılı olmak için nasıl bir yol izlemesi gerektiğine ilişkin bilgiler sunulması beklenmiştir. Çalışmada ayrıca öğrenme analitiği düzeylerinden bağımsız olarak öğrenenlerin öğrenme paneli tasarımına yönelik genel beklentileri sunulmuştur. Son olarak öğrenme analitiği düzeyleri bağlamında öğrenme panelinin tasarımına yönelik tasarım ilkeleri sunulmuştur.

Anahtar Kelimeler

öğrenme paneli, betimleyici analitikler, tanılayıcı analitikler, yordayıcı analitikler, öngörü analitikleri

Destekleyen Kurum

TÜBİTAK

Proje Numarası

119K430

IDENTIFYING LEARNERS’ EXPECTATIONS FROM LEARNING ANALYTICS DASHBOARDS IN THE CONTEXT OF ANALYTICS TYPES

Öz

This case study aims to discover elements that learners expect from learning analytics dashboards and propose design principles based on these expectations. Focus group interviews were conducted with 20 graduate students with previous e-learning experience to inform design principles for learning analytics dashboards. Interviews were conducted with 5 groups, lasting an average of 53 minutes. The gathered information was analyzed through content analysis. The research findings were divided into five themes: four were expectations for information within the scope of learning analytics types (descriptive analytics, diagnostic analytics, predictive analytics, predictive analytics), and one theme was generic expectations for how the learning analytics dashboard should be designed. For descriptive analytics, respondents indicated that they would like to see information on how they were performing in relation to their learning objectives, as well as how their performance compared to the group/class average. For diagnostic analytics, respondents indicated that they would like to see information about learning deficiencies, performance anomalies, as well as the relation between time spent on a topic and performance. Although estimations of success within the context of predictive analytics are widely expected, information on how to follow a path to be successful within the context of prescriptive analytics is also expected. The study also presented the general expectations of learners from the learning analytics dashboards. Finally, design principles for learning analytics dashboards in the context of learning analytics types are presented.

Anahtar Kelimeler

learning analytics dashboards, descriptive analytics, diagnostic analytics, predictive analytics, prescriptive analytics

Proje Numarası

119K430

Kaynakça

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