GSIC-EMIC researchers attended the 9th Learning Analytics Summer Institute Spain (LASI Spain 2020)

GSIC-EMIC researchers attended the 9th Learning Analytics Summer Institute Spain (LASI Spain 2020)

The researchers of the SmartLET project from the GSIC-EMIC research group, Alejandro Ortega-Arranz, Erkan Er and Cristina Villa-Torrano, attended the 9th Learning Analytics Summer Institute Spain (LASI Spain 2020), organized by the Universidad de Valladolid and SNOLA (Spanish Network of Learning Analytics) (http://snola.es), between the 15th and 16th of June, 2020. During the event, the researches participated and presented their work through the different sessions.

Alejandro Ortega-Arranz, in collaboration with René Lobo-Quintero and Davinia Hernández-Leo from Universidad Pompeu Fabra, presented their work titled “Towards reward-based gamification in Collaborative Learning Flow Patterns based on learning analytics”. In this work, they explored how the use of reward-based gamification strategies, accompanied with Learnign Analytics, can potentially reinforce the participation an collaboration between students.

Erkan Er presented the advances of his work, titled “Self and Peer Monitoring during Peer Feedback: The Instructor Perspective”, which investigates isntructors’ pespective about self and peer monitoring enbaled via a student-facing dashboard in the specific context of peer reviews.

Cristina Villa-Torrano shared her work title “Early prediction of students’ efficiency during online assessments using a Long- Short Term Memory architecture”. This paper is focused on the development of a classification model, based on Long-Short Term Memory (LSTM) recurrent neural network achitecture, to understand students’ behaviour and effectiveness during online assessments. This model was originally presented in the Nation’s Report Card Data Mining Competition 2019 (NAEP 2019). As well, she participated on the Doctoral Consortium hold during the conference, where she presented her PhD. Thesis proposal for the support of collaboration by detecting patterns of Socially-Shared Regulation of Learning in the context of Smart Learning Environments.

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