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Title
Artificial intelligence on the advance to enhance educational assessment: Scientific clickbait or genuine gamechanger?
Authors
SourceJournal of computer assisted learning 39 (2023) 3, S. 695-702 ZDB
Document  (1.158 KB)
License of the document Lizenz-Logo 
Keywords (German)
sub-discipline
Document typeArticle (journal)
ISSN1365-2729 ; 13652729
LanguageEnglish
Year of creation
review statusPeer-Reviewed
Abstract (English):Contributions in the Special Issue: The special issue assembles papers centring around log data analysis, natural language processing, and machine learning used to advance educational assessment. They demonstrate how semi- and unstructured data such as log and text data can, despite their challenging nature, be handled appropriately to benefit educational assessment. In this editorial, we contextualize the special issue's contributions within the diverse field of modern technology-based assessments. Reflection on Terminology: Moreover, we raise concerns about nowadays' use of the term artificial intelligence (AI) in scientific communication. While the contribution of AI to scientific progress is indisputable, the mere use of methods that have evolved within AI research does not necessarily render tools or studies AI-related. We argue that academics have the social responsibility to adopt accurate terminology, given it is integral to scientific rigour and proper scientific communication. Implications: In view of the inflationary use of the term AI in science, we propose a scheme to locate one's research in the field by focusing on (1) the type of data, (2) the processing involved, and (3) the output of a study and the actions derived from it, which are situated within the (4) scope of a study. (DIPF/Orig.)
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Date of publication04.11.2024
CitationZehner, Fabian; Hahnel, Carolin: Artificial intelligence on the advance to enhance educational assessment: Scientific clickbait or genuine gamechanger? - In: Journal of computer assisted learning 39 (2023) 3, S. 695-702 - URN: urn:nbn:de:0111-pedocs-318216 - DOI: 10.25656/01:31821; 10.1111/jcal.12810
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