Browsing by Author "Pérez, J. C"

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    PublicationOpen Access
    Collaborative learning designs using PyramidApp: computer supported collaborative learning in classroom sessions
    (CIDUI Congrés Internacional de Docència Universitària i Innovació, 2021) Amarasinghe, I; Hernández Leo, D; Manatunga, K; Beardsley, M; Garcia, J. B; Carrió, M; Pérez, J. C; Santos, D. L; Pastor, S. L; Moreno, J. M; Rodríguez, P. S; Vujovic, M
    Designing effective collaborative learning activities for classroom is challenging. The PyramidAppis a tool that facilitates the implementation of the Pyramid pattern, shaping a collaboration structure that promotes the participation of all students and fruitful social interactions. This paper shows how this educational strategy can be applied to different types of tasks and subject matters, shedding light about how computersupported collaborative learning can be incorporated in the classroom.
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    PublicationOpen Access
    Teacher-Led Debriefing in Computer-Supported Collaborative Learning Pyramid Scripts
    (International Society of the Learning Sciences (ISLS), 2022-06-06) Amarasinghe, I; Hernández-Leo, D; Manathunga, K; Pérez, J. C; Dimitriadis, Y
    Debriefing is an integral part of orchestration and provides a space for teachers to review the learning experience. Although this concept is not new, little is known about how debriefing is conducted in scripted computer-supported collaborative learning situations, and its effects on students’ learning gains. Moreover, there is a lack of studies providing evidence of how learning analytics can be effectively utilised to support teacher-led debriefing. The objective of this study is twofold: Firstly, it studies how debriefing impacts students’ learning gains in Pyramid pattern-based learning situations. Secondly, it explores the types of learning analytics indicators that can support debriefing. Results indicated that debriefing can contribute to improve students’ learning gains, however, it does not always lead to the optimal outcomes and the type of task can have a major influence. Mechanisms such as semantic similarity score, knowledge graph visualisations and flag features are scrutinized as options to support debriefing