Publications

Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34

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Author: search.filters.author.García-Peñalvo, F. J.Subject: search.filters.subject.learning analytics

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    Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education
    (MDPI, 2021-02-13) García-Peñalvo, F. J.
    The purpose of this paper is to define a reference framework for introducing eLearning practices in mainly face-to-face higher education institutions. We suggest a suitable adoption and management of associated infrastructures and processes, in order to guarantee the ethical use of data in the related academic and learning analytics. A theoretical framework is proposed after years of practice and experience in the institutional government of IT processes related to learning technology. The digital transformation of teaching should imply the right technological decisions made by people and for people, in order to achieve a more inclusive, participative, and human university supported by technology. digital transformation is a social requirement of governments, companies, and institutions, and it should take into account the associated risks of the unethical use of technology, which leads to the dark side of transformation processes. eLearning approaches, especially with the influence of the COVID-19 outbreaks, are increasing the need for digital mechanisms in universities. Further, there is a need for strategical support and reference models if we are to avoid these undesired effects.
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    Using Learning Analytics to Detect Authentic Leadership Characteristics in Engineering Students
    (2018-05-01) Sein-Echaluce, M. L.; Fidalgo-Blanco, Á.; Esteban-Escaño, J.; García-Peñalvo, F. J.; Conde, M. Á.
    Previous research has shown that teamwork between students underpins the communication interactions among team members, and these interactions are underscored in the work environment, job quality, work outcome and, of course, grades. Analysing the interactions among the members of a team using a learning analytics system allows for a forma-tive evaluation that indicates the progress of each team member and taking remedial actions if appropriate progress has not been made. This paper uses a learning analytics system to study interactions between students and detect the values and attitudes demanded of a leader by society. The results of this analysis are keys for avoiding corruption and wrong practices and can even provide a solution to global intercultural troubles. In this study, a validated questionnaire of authentic leadership was given to 78 team members in a university context; the influence of some values and attitudes on leadership is proved with grades; and a learning analytics system was used to analyse information that could predict a leader’s behaviour during the development of teamwork.
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    Learning Analytics to Assess Students’ Behavior With Scratch Through Clickstream
    (CEUR-WS.org, 2018-08-31) Amo, D.; Alier, M.; García-Peñalvo, F. J.; Fonseca, D.; Casañ, M. J.
    The construction of knowledge through computational practice requires to teachers a substantial amount of time and effort to evaluate programming skills, to understand and to glimpse the evolution of the students and finally to state a quantitative judgment in learning assessment. This suposes a huge problem of time and no adecuate intime feedback to students while practicing programming activities. The field of learning analytics has been a common practice in research since last years due their great possibilities in terms of learning improvement. Such possibilities can be a strong positive contribution in the field of computational practice such as programming. In this work we attempt to use learning analytics to ensure intime and quality feedback through the analysis of students behavior in programming practice. Hence, in order to help teachers in their assessments we propose a solution to categorize and understand students’ behavior in programming activities using business technics such as web clickstream. Clickstream is a technique that consists in the collection and analysis of data generated by users. We applied it in learning programming environments to study students behavior to enhance students learning and programming skills. The results of the work support this business technique as useful and adequate in programming practice. The main finding shows a first taxonomy of programming behaviors that can easily be used in a classroom. This will help teachers to understand how students behave in their practice and consequently enhance assessment and students’ following-up to avoid examination failures.