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Conference Papers Year : 2022

AsTRA – An Assessment Tool for Recognition and Adaptation of Prior Professional Experience and Vocational Training

Simone Opel
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  • PersonId : 1270053
Cajus Marian Netzer
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Jörg Desel
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  • PersonId : 1270055

Abstract

Educational systems in most countries are differentiated by level and entail transitions between different school types. The different school types do not always support a transition without gaps or repetitions. For students, this can be very frustrating, demotivating and time-consuming. For example, many graduated IT specialists bring work experience, a number of relevant competencies and previous knowledge from their vocational education and training into a degree programme in computer science – yet they still have to take the associated courses and pass examinations. To improve this situation and value the competencies brought along, we implemented a project to develop a comprehensive system to honour the prior knowledge of these students in various ways. One of our goals is to promote permeability between vocational and higher education, not only in computer science. The core element of this System is AsTRA, a comprehensive assessment tool which we developed to evaluate the common learning content and its difficult level. This system is designed to credit previous knowledge and to adapt the students’ learning paths, based on reliable decisions. In this paper, we present our tool AsTRA that supports these decisions as well as a brief overview of our resulting recognition system.
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hal-04161437 , version 1 (01-08-2023)

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Simone Opel, Cajus Marian Netzer, Jörg Desel. AsTRA – An Assessment Tool for Recognition and Adaptation of Prior Professional Experience and Vocational Training. Open Conference on Computers in Education (OCCE), Aug 2021, Tampere, Finland. pp.222-233, ⟨10.1007/978-3-030-97986-7_19⟩. ⟨hal-04161437⟩
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