Informing the Design of Collaborative Activities in MOOCs using Actionable Predictions

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Er E., Gomez-Sanchez E., Bote-Lorenzo M. L., Asensio-Perez J. I., Dimitriadis Y.

6th ACM Conference on Learning @ Scale (L@S), Illinois, Amerika Birleşik Devletleri, 24 - 25 Haziran 2019 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1145/3330430.3333640
  • Basıldığı Şehir: Illinois
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

With the aim of supporting instructional designers in setting up collaborative learning activities in MOOCs, this paper derives prediction models for student participation in group discussions. The salient feature of these models is that they are built using only data prior to the learning activity, and can thus provide actionable predictions, as opposed to post-hoc approaches common in the MOOC literature. Some learning design scenarios that make use of this actionable information are illustrated.