Browsing by Author "Gasevic, Dragan"

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    An overview of the LALA project
    (2020) Muñoz-Merino, Pedro J.; Delgado Kloos, Carlos; Tsai, Yi-Shan; Gasevic, Dragan; Verbert, Katrien; Pérez Sanagustín, Mar; Hilliger, Isabel; Zúñiga-Prieto, Miguel Ángel; Ortiz-Rojas, Margarita; Scheihing, Eliana
    The LALA project (“Building Capacity to Use Learning Analytics to Improve Higher Education in Latin America”) is a project that aims at building capacity about the use of data in education for improving education in Latin America. This article presents a general overview of the LALA project including the LALA framework (as a set of guidelines, recommendations and patterns for enabling adoption of learning analytics), the adaptation of learning analytics tools (mainly three different tools used in Europe) and the pilots with learning analytics experiences. The results of this project could serve as an example for other institutions in the Latin American region or other under-represented regions to adopt Learning Analytics as part of their processes.
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    Analytics of Learning Strategies: Role of Course Design and Delivery Modality
    (2020) Matcha, Wannisa; Gasevic, Dragan; Uzir, Nora'ayu Ahmad; Jovanovic, Jelena; Pardo, Abelardo; Lim, Lisa; Maldonado-Mahauad, Jorge; Gentili, Sheridan; Perez-Sanagustin, Mar; Tsai, Yi-Shan
    Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning analytics method proposed for detecting learning tactics and strategies from trace data. The method was applied to the datasets collected in three different course designs and delivery modalities, including flipped classroom, blended learning, and massive open online course. The proposed method combines process mining and sequence analysis. The detected learning strategies are explored in terms of their association with academic performance. The results indicate the applicability of the proposed method across different learning contexts. Moreover, the findings contribute to the understanding of the learning tactics and strategies identified in the trace data: learning tactics proved to be responsive to the course design, whereas learning strategies were found to be more sensitive to the delivery modalities than to the course design. These findings, well aligned with self-regulated learning theory, highlight the association of learning contexts with the choice of learning tactics and strategies.
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    Trustworthy remote assessments: A typology of pedagogical and technological strategies
    (2022) Hilliger Carrasco, Isabel; Ruiperez-Valiente, Jose A.; Alexandron, Giora; Gasevic, Dragan