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DC Field | Value | Language |
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dc.contributor.author | Alario Hoyos, Carlos | |
dc.contributor.author | Pérez Sanagustín, Mar | |
dc.contributor.author | Delgado Kloos, Carlos | |
dc.contributor.author | Maldonado Mahauad, Jorge Javier | |
dc.date.accessioned | 2023-01-24T17:28:08Z | - |
dc.date.available | 2023-01-24T17:28:08Z | - |
dc.date.issued | 2022 | |
dc.identifier.isbn | 978-303118271-6 | |
dc.identifier.issn | 1865-0929 | |
dc.identifier.uri | http://dspace.ucuenca.edu.ec/handle/123456789/40855 | - |
dc.identifier.uri | https://www.scopus.com/record/display.uri?eid=2-s2.0-85140770407&doi=10.1007%2f978-3-031-18272-3_9&origin=inward&txGid=df26b279c77de1993c2790d194ca35ca | |
dc.description.abstract | The study of learners’ behaviour in Massive Open Online Courses (MOOCs) is a topic of great interest for the Learning Analytics (LA) research community. In the past years, there has been a special focus on the analysis of students’ learning strategies, as these have been associated with successful academic achievement. Different methods and techniques, such as temporal analysis and process mining (PM), have been applied for analysing learners’ trace data and categorising them according to their actual behaviour in a particular learning context. However, prior research in Learning Sciences and Psychology has observed that results from studies conducted in one context do not necessarily transfer or generalise to others. In this sense, there is an increasing interest in the LA community in replicating and adapting studies across contexts. This paper serves to continue this trend of reproducibility and builds upon a previous study which proposed and evaluated a PM methodology for classifying learners according to seven different behavioural patterns in three asynchronous MOOCs of Coursera. In the present study, the same methodology was applied to a synchronous MOOC on edX with N = 50,776 learners. As a result, twelve different behavioural patterns were detected. Then, we discuss what decision other researchers should made to adapt this methodology and how these decisions can have an effect on the analysis of trace data. Finally, the results obtained from applying the methodology contribute to gain insights on the study of learning strategies, providing evidence about the importance of the learning context in MOOCs | |
dc.language.iso | es_ES | |
dc.publisher | Springer Science and Business Media Deutschland GmbH | |
dc.source | Communications in Computer and Information Science | |
dc.subject | Learning strategies | |
dc.subject | Massive open online courses | |
dc.subject | Learning behaviour | |
dc.subject | Process mining | |
dc.subject | Learning analytics | |
dc.title | Adaptation of a process mining methodology to analyse learning strategies in a synchronous massive open online course | |
dc.type | ARTÍCULO DE CONFERENCIA | |
dc.description.city | Cuenca | |
dc.ucuenca.idautor | 0000-0001-9854-9963 | |
dc.ucuenca.idautor | 1102959051 | |
dc.ucuenca.idautor | 0000-0002-3082-0814 View this author’s ORCID profile | |
dc.ucuenca.idautor | 57226068561 | |
dc.identifier.doi | 10.1007/978-3-031-18272-3_9 | |
dc.ucuenca.embargoend | 2050-12-30 | |
dc.ucuenca.version | Versión publicada | |
dc.ucuenca.embargointerno | 2050-12-30 | |
dc.ucuenca.areaconocimientounescoamplio | 06 - Información y Comunicación (TIC) | |
dc.ucuenca.afiliacion | Alario, C., Universidad Carlos III de Madrid, Leganés, España | |
dc.ucuenca.afiliacion | Delgado, C., Universidad Carlos III de Madrid, Leganés, España | |
dc.ucuenca.afiliacion | Pérez, M., Universite Toulouse, Jean Juares, Toulouse, Francia | |
dc.ucuenca.afiliacion | Maldonado, J., Universidad de Cuenca, Departamento de Ciencias de la Computación, Cuenca, Ecuador | |
dc.ucuenca.correspondencia | Maldonado Mahauad, Jorge Javier, jorge.maldonado@ucuenca.edu.ec | |
dc.ucuenca.volumen | Volumen 1648 | |
dc.ucuenca.indicebibliografico | SCOPUS | |
dc.ucuenca.factorimpacto | 0.21 | |
dc.ucuenca.cuartil | Q4 | |
dc.ucuenca.numerocitaciones | 0 | |
dc.ucuenca.areaconocimientofrascatiamplio | 2. Ingeniería y Tecnología | |
dc.ucuenca.pais | ECUADOR | |
dc.ucuenca.conferencia | 10th Ecuadorian Congress of Information and Communication Technologies, TICEC 2022 | |
dc.ucuenca.areaconocimientofrascatiespecifico | 2.2 Ingenierias Eléctrica, Electrónica e Información | |
dc.ucuenca.areaconocimientofrascatidetallado | 2.2.4 Ingeniería de La Comunicación y de Sistemas | |
dc.ucuenca.areaconocimientounescoespecifico | 061 - Información y Comunicación (TIC) | |
dc.ucuenca.areaconocimientounescodetallado | 0613 - Software y Desarrollo y Análisis de Aplicativos | |
dc.ucuenca.fechainicioconferencia | 2022-10-12 | |
dc.ucuenca.fechafinconferencia | 2022-10-14 | |
dc.ucuenca.organizadorconferencia | CEDIA | |
dc.ucuenca.comiteorganizadorconferencia | CEDIA-Ecuador, Universidad Laica Eloy Alfaro de Manabí | |
dc.ucuenca.urifuente | https://www.springer.com/series/7899 | |
Appears in Collections: | Artículos |
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File | Size | Format | |
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documento.pdf Until 2050-12-30 | 423.96 kB | Adobe PDF | View/Open Request a copy |
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