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Domínguez Figaredo, Daniel

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0000-0002-7772-1856
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Domínguez Figaredo
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Daniel
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2019 - 201912020 - 20232
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search.filters.applied.f.accessLevel: Atribución-NoComercial-SinDerivadas 4.0 Internacional × search.filters.applied.f.itemFacultad: Facultad de Educación ×

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Mostrando 1 - 3 de 3
  • Miniatura
    Publicación
    The Impact of Rapid Adoption of Online Assessment on Students’ Performance and Perceptions: Evidence from a Distance Learning University
    (Academic Publishing International Limited, 2022) Domínguez Figaredo, Daniel; Gil Jaurena, Inés; Morentin Encina, Javier
    One of the most sensitive changes faced by universities due to the COVID-19 crisis was the remote assessment of student learning. This research analysed the case of a massive distance learning university that rapidly changed the final assessment (N=126,653 undergraduate students in 2020) from face-to-face exams to entirely online exams. The research focused on the influence of online assessment on academic performance and students’ perception of the new method. Two data sources were used: the contrast of academic performance indicators (assessment, success and achievement rates, and average marks obtained) between the online examination call and the previous ones with face-to-face examinations; and a questionnaire to a sample of students (n=714) on their perception of the online assessment experience. The results show that all the academic performance indicators in the 28 Bachelor Degrees offered at the university increased when the final assessment method turned to online due to the pandemic crisis; and that a majority of students are more favourable to online assessment methods. The discussion places these findings in a context of rapid change, and concludes by identifying the possible implications of online assessment for student retention, organisational challenges, as well as possible further studies.
  • Miniatura
    Publicación
    Heuristic framework design in the field of digital literacy: A case study based on the Mozilla Web Literacy Map.
    (ResearchGate, 2019) Domínguez Figaredo, Daniel; Trillo Miravalles, Mª Paz
    The use of skill frameworks has become commonplace in the field of digital literacy. These frameworks are based preferentially on conceptual approaches, which leads to biases when applied in practice. Here, we present a study with an alternate focus: the skills proposed in the frameworks are connected with user behavior and heuristics are employed to group these skills. The objectives of the study were to: (1) achieve a greater coherence between the skills incorporated in these frameworks and user behavior, and (2) identify and reliably organize the clusters of skills that form frameworks. The study consisted of collecting data from a group of students about their practices within the skills of the Mozilla Web Literacy Map. The data was then grouped via factor analysis. The results were then contrasted with the initial organization of the Mozilla framework. The gap between the theoretical definition of a skill and individual behaviors was found to be more pronounced in the case of those skills whose definitions included a wider range of concepts and practices. This study opens a discussion into the scope and suitability of the method used here to generate heuristic dimensions by managing information from social behaviors.
  • Miniatura
    Publicación
    Responsible AI literacy: A stakeholder-first approach
    (SAGE, 2023-12-19) Stoyanovich, Julia; Domínguez Figaredo, Daniel
    The need for citizens to better understand the ethical and social challenges of algorithmic systems has led to a rapid proliferation of AI literacy initiatives. After reviewing the literature on AI literacy projects, we found that most educational practices in this area are based on teaching programming fundamentals, primarily to K-12 students. This leaves out citizens and those who are primarily interested in understanding the implications of automated decision- making systems, rather than in learning to code. To address these gaps, this article explores the methodological contributions of responsible AI education practices that focus first on stakeholders when designing learning experiences for different audiences and contexts. The article examines the weaknesses identified in current AI literacy projects, explains the stakeholder-first approach, and analyzes several responsible AI education case studies, to illustrate how such an approach can help overcome the aforementioned limitations. The results suggest that the stakeholder-first approach allows to address audiences beyond the usual ones in the field of AI literacy, and to incorporate new content and methodologies depending on the needs of the respective audiences, thus opening new avenues for teaching and research in the field.