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Assessing Digital Skills and Competencies for Different Groups and Devising a Conceptual Model to Support Teaching and Training

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Cross Reality and Data Science in Engineering (REV 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1231))

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Abstract

The assessment of digital skills and competencies required to make use of digital resources poses several challenges. In order to evaluate the current situation and trends, this research study initially presents a review of history, existing trends and digital competence frameworks, learning and teaching methodologies for digital literacy and provides insights and recommendations. The review of existing framework and methods used to assess digital skills of different groups has revealed that self-assessment is an assessment category that most often results in an overestimation of own digital skills by respondents. To address such deficiencies, a digital competency model (DigComp) was created in 2013, as part of the EU Education and Training Agenda 2020. This model describes which skills and competencies are needed to use digital technologies in a confident, critical, collaborative and creative way and to accomplish the goals related to work, learning, and leisure in a digital society. Starting from the existing framework, this research study devises a conceptual model to support teaching and training. Each user group requires a different approach in order to accurately evaluate their digital competences; therefore, the use of a flexible and integrated approach is necessary. The model proposed in this study describes which skills should be learned, how they should be taught, and how they can be assessed.

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Correspondence to Xhelal Jashari .

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Jashari, X., Fetaji, B., Nussbaumer, A., Gütl, C. (2021). Assessing Digital Skills and Competencies for Different Groups and Devising a Conceptual Model to Support Teaching and Training. In: Auer, M., May, D. (eds) Cross Reality and Data Science in Engineering. REV 2020. Advances in Intelligent Systems and Computing, vol 1231. Springer, Cham. https://doi.org/10.1007/978-3-030-52575-0_82

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