Learning from student browsing data on e-learning platforms: case study

• Autorzy: Cansiz Sergen , Sudan Berk , Ogretici Emre , Siddik Aktas Mehmet

Identyfikatory

DOI

10.15439/2020F138

• Konferencja: Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

Interpretation of the behaviors of students in e-learning platforms with machine learning models has become an emerging need in recent years. Increase in the number of registered students on e-learning platforms is one of the reasons for choosing machine learning models. Tracking, modeling and understanding student activities gets more complex when the number of students is increased. This study is focusing modeling student activities on e-learning platforms with Complex Event Processing (CEP), Association Rule Mining (ARM) and Clustering methods based on distributed software architecture. Within the scope of this study, different modules that work real-time have been developed. An admin panel has been also developed in order to control all modules and track the student actions. Performance results of modules also obtained and evaluated on distributed system architecture.

Słowa kluczowe

EN

e-learning; complex event processing; association rule mining; clustering

PL

e-learning; złożone przetwarzanie zdarzeń; reguły asocjacyjne; grupowanie; klasteryzacja

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 22
• Strony: 37--44
• Opis fizyczny: Bibliogr. 41 poz., rys., tab., wykr.

Twórcy

autor

Cansiz Sergen

• Morpa R&D Center, Istanbul, Turkey

autor

Sudan Berk

• Morpa R&D Center, Istanbul, Turkey

autor

Ogretici Emre

• Morpa R&D Center, Istanbul, Turkey

autor

Siddik Aktas Mehmet

• YTU Computer Engineering Dept, Istanbul, Turkey

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Uwagi

1. This study was supported by Tubitak Teydeb Project ID: 3189164 Grant.

2. Track 4: Information Systems and Technology

3. Technical Session: 26th Conference on Knowledge Acquisition and Management

4. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).