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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/6154

    Título
    Improve teaching with modalities and collaborative groups in an LMS: an analysis of monitoring using visualisation techniques
    Autor
    Sáiz Manzanares, María ConsueloUBU authority Orcid
    Marticorena Sánchez, RaúlUBU authority Orcid
    Rodríguez Diez, Juan JoséUBU authority Orcid
    Rodríguez Arribas, SandraUBU authority Orcid
    Diez Pastor, José FranciscoUBU authority Orcid
    Ji, Yi Peng
    Publicado en
    Journal of Computing in Higher Education. 2021, V. 33, n. 3, p. 747–778
    Editorial
    Springer
    Fecha de publicación
    2021-12
    ISSN
    1042-1726
    DOI
    10.1007/s12528-021-09289-9
    Abstract
    Monitoring students in Learning Management Systems (LMS) throughout the teaching– learning process has been shown to be a very effective technique for detecting students at risk. Likewise, the teaching style in the LMS conditions, the type of student behaviours on the platform and the learning outcomes. The main objective of this study was to test the effectiveness of three teaching modalities (all using Online Project-based Learning -OPBL- and Flipped Classroom experiences and differing in the use of virtual laboratories and Intelligent Personal Assistant -IPA-) on Moodle behaviour and student performance taking into account the covariate "collaborative group". Both quantitative and qualitative research methods were used. With regard to the quantitative analysis, differences were found in student behaviour in Moodle and in learning outcomes, with respect to teaching modalities that included virtual laboratories. Similarly, the qualitative study also analysed the behaviour patterns found in each collaborative group in the three teaching modalities studied. The results indicate that the collaborative group homogenises the learning outcomes, but not the behaviour pattern of each member. Future research will address the analysis of collaborative behaviour in LMSs according to different variables (motivation and metacognitive strategies in students, number of members, interactions between students and teacher in the LMS, etc.).
    Palabras clave
    Online project-based learning
    Visualisation techniques
    Machine learning techniques
    Monitoring students
    Self-regulated learning
    Heat map
    Materia
    Enseñanza superior
    Education, Higher
    Informática
    Computer science
    Psicología
    Psychology
    URI
    http://hdl.handle.net/10259/6154
    Versión del editor
    https://doi.org/10.1007/s12528-021-09289-9
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