STUDIO: A Solution on Adaptive Testing

Christian Weber ()
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Christian Weber: Corvinno Technology Transfer Center

A chapter in Corporate Knowledge Discovery and Organizational Learning, 2016, pp 131-153 from Springer

Abstract: Abstract Modern workers have to cope with changes and new flexible requirements in their working environment. Projects may require new skills, co-workers could leave the company, leading to a shift in responsibilities, or new labour market opportunities motivate the acquiring of different skill sets. Coping with changes and satisfying the need for personal improvement means to know and capture the border of personal education and continuously practicing self-assessment to monitor personal progress. Understanding personal education and development potential requires testing the current state of education in a resourceful way, while adapting to personal performance and learning potentials. As such, adaptivity is not only an important factor in terms of personal education but also in the sense of testing. The field of adaptive testing makes it possible to adapt to the skills and knowledge of a person, to then being able to reason about educational potentials. To gain insights on job proficiency and educational potential requires understanding education in a context—a vision evident in the psychology of learning, but lacking in concepts for modern computer assisted educational testing. This chapter will motivate a vision of a context aware and context rich educational self assessment. Testing the knowledge of individuals within the framework of organisational learning needs an adaptive test, which is flexible in terms of the knowledge to assess and adaptive in terms of the knowledge of an individual worker. The STUDIO solution contributes here with an adaptive testing and assessment solution, tackling the need for adaptiveness with a concept of knowledge exploration.

Keywords: Organisational Learning; Knowledge Structure; Domain Ontology; Informal Learning; Computerize Adaptive Test (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-28917-5_6

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