Using Educational Data Mining to Identify and Analyze Student Learning Strategies in an Online Flipped Classroom

Davies, Randall; Allen, Gove N.; Albrecht, Conan; Bakir, Nesrin; Ball, Nick

doi:10.3390/educsci11110668

Cited by 13 publications

(11 citation statements)

References 17 publications

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“…However, the vast majority of the papers considered employing a model-driven approach (33 papers), which could qualify as a positive tendency. constructionism (Haya et al, 2015), cognitivism (Davies et al, 2021;Rayyan et al, 2016), praxeology educology (Frick et al, 2022), visualisation theory (de Leng & Pawelka, 2020), social comparison theory (Kokoç & Altun, 2021), and so forth. It is important to note that certain publications that went more deeply into the issue of LA-LD theoretical background were not included in the final selection owing to their theoretical nature or lack of empirical evidence.…”

Section: Discussionmentioning

confidence: 99%

“…or 'How does X function'? For example, Davies et al (2021) intended to demonstrate how information could be data mined in an unobtrusive manner from a learning management system. The studies guided by these questions examined some commonly-used and applied tools or methods (and, therefore, tested them for efficiency)…”

Section: Rq1: What Research Questions Were Stated?mentioning

confidence: 99%

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Learning analytics driven improvements in learning design in higher education: A systematic literature review

Drugova,

Zhuravleva,

Zakharova

et al. 2023

Computer Assisted Learning

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BackgroundDriven by the ongoing need to provide high‐quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear.ObjectivesThis study is aimed to evaluate the maturity of research discussing LA‐driven LD improvements in higher education.MethodsThe systematic review analyses 49 empirical papers, assesses their quality and suggests further research directions. The review elaborates on methodological (research questions, strategy and methods, LA‐LD integration theoretical backgrounds) and substantial (LA‐driven LD improvements, types of data used, LA software development) features of the papers.Results and ConclusionsThe findings demonstrated the lack of theoretical alignment between LA and LD, with research tending towards user experience studies. The most frequently used research strategy was a case study; experiments were very rare. Researchers predominantly used parsing for collecting data and AI methods for analysing it; mostly used data types related to registering learners' engagement with learning activities as well as resources and tools provided in digital learning environments.TakeawaysThe research area discussing LA‐driven LD improvements still has a way to go before attaining the level of full maturity. Only a third of the papers reported actual LA‐driven LD improvements; moreover, only three papers measured their effectiveness. The presented LA software was mostly at the beta or implementation stages and did not assess the impact of using this software.

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Section: Discussionmentioning

confidence: 99%

Section: Rq1: What Research Questions Were Stated?mentioning

confidence: 99%

Learning analytics driven improvements in learning design in higher education: A systematic literature review

Drugova,

Zhuravleva,

Zakharova

et al. 2023

Computer Assisted Learning

View full text Add to dashboard Cite

show abstract

“…Analyzing the data of a course with learning analytics provides insights that can affect instructional design decisions (Davies et al, 2021). In this respect, it is thought that it will be helpful to base the research findings on the planning of distance education and determining the preferred teaching materials.…”

Section: Originality/valuementioning

confidence: 99%

Büyük Veriden Öğrencilerin Öğretim İçerik Tercihlerinin Başarıya Etkisinin Belirlenmesine Yönelik Veritabanlarından Bilgi Keşfi Yöntemi: OULAD Veri Seti Örneği

Meşe

2023

Anadolu Üniversitesi Sosyal Bilimler Dergisi

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Sanal öğrenme ortamlarında öğrencilerin öğrenme içerikleri ile etkileşimlerinden dolayı çok sayıda veri ortaya çıkmaktadır. Bu veriler eğitsel veri madenciliği algoritmaları ile sanal öğrenme ortamlarının tasarımında yol gösterici nitelikte olmaktadır. Ancak öğrencilerin sanal öğrenme ortamında etkileşimde bulundukları öğretim materyallerinin başarı durumlarına etkisinin incelenmesine ihtiyaç duyulmaktadır. Bu tür ihtiyaçlara yönelik yapılan eğitsel veri madenciliği uygulamalarına yönelik izlenmesi gereken bilimsel süreçlerin de ortaya konulması gerekmektedir. Bu araştırmada öğrencilerin sanal öğrenme ortamında farklı öğrenme materyalleri ile etkileşimlerinin başarı durumuna etkisinin ortaya konulmasında veritabanından bilgi keşfi yönteminin kullanılması amaçlanmıştır. Araştırmada büyük veri olarak The Open University Öğrenme Analitiği Veri Seti kullanılmıştır. Bu veri seti ile veritabanından bilgi keşfi yöntemine göre süreç izlenmiş ve karar ağacı algoritmalarından CART algoritması ile araştırma sorularına yanıt aranmıştır. Araştırmanın bulgularına göre öğrencilerin öğretim materyalleri ile etkileşimlerinin başarının bir belirleyicisi olduğu görülmüştür. Bu doğrultuda öğretim tasarımcılarının uzaktan eğitim ortamlarında standartların oluşturulmasına ve etkili bir öğretim tasarımı için tercih edilecek öğretim materyallerinin belirlenmesine yönelik alacakları kararda araştırma bulgularının yol gösterici nitelikte olması öngörülmektedir.

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“…The performance of the students in the virtual lab was also monitored to identify opportunities to improve the virtual lab for future cohorts. The possibility to monitor the students' performance while doing their out-of-class work is a unique advantage of flipped classroom and blended learning [24].…”

Section: Description Of the Virtual Experimentsmentioning

confidence: 99%

Comparison of In-Person and Virtual Labs/Tutorials for Engineering Students Using Blended Learning Principles

2022

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The paper compares the effectiveness of in-person and virtual engineering laboratory sessions. The in-person and virtual laboratory sessions reported here comprise six experiments combined with short tutorials. The virtual lab combined enquiry-based learning and gamification principles. The integration of the virtual labs with in-person teaching created a blended learning environment. The effectiveness of this approach was assessed based on (i) the student feedback (i.e., a questionnaire with open-ended questions and Likert scale feedback), (ii) the students’ engagement with the virtual lab, and (iii) the impact on the academic performance (i.e., class test results). The students reported greater confidence in the understanding of theory in the virtual lab than the in-person lab. This is interesting given that the instruction for the virtual lab and the in-person lab of one experiment is identical (i.e., same instructor, same enquiry-based learning techniques, and same explanations). The students also appreciated the ability to complete the virtual lab anytime, anywhere, for as long as they needed, and highlighted the benefits of the interactivity. The median class test scores of the students who completed some or all the virtual lab experiments was higher than those who did not (83–89% vs. 67%).

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Using Educational Data Mining to Identify and Analyze Student Learning Strategies in an Online Flipped Classroom

Cited by 13 publications

References 17 publications

Learning analytics driven improvements in learning design in higher education: A systematic literature review

Learning analytics driven improvements in learning design in higher education: A systematic literature review

Büyük Veriden Öğrencilerin Öğretim İçerik Tercihlerinin Başarıya Etkisinin Belirlenmesine Yönelik Veritabanlarından Bilgi Keşfi Yöntemi: OULAD Veri Seti Örneği

Comparison of In-Person and Virtual Labs/Tutorials for Engineering Students Using Blended Learning Principles

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