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Autor/inCaspari-Sadeghi, Sima
TitelArtificial Intelligence in Technology-Enhanced Assessment: A Survey of Machine Learning
QuelleIn: Journal of Educational Technology Systems, 51 (2023) 3, S.372-386 (15 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Caspari-Sadeghi, Sima)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0047-2395
DOI10.1177/00472395221138791
SchlagwörterArtificial Intelligence; Educational Technology; Computer Assisted Testing; Barriers; Educational Assessment; Technology Uses in Education; Data Analysis; Data Collection; Intelligent Tutoring Systems
AbstractIntelligent assessment, the core of any AI-based educational technology, is defined as embedded, stealth and ubiquitous assessment which uses intelligent techniques to diagnose the current cognitive level, monitor dynamic progress, predict success and update students' profiling continuously. It also uses various technologies, such as learning analytics, educational data mining, intelligent sensors, wearables and machine learning. This can be the key to Precision Education (PE): adaptive, tailored, individualized instruction and learning. This paper explores (a) the applications of Machine Learning (ML) in intelligent assessment, and (b) the use of deep learning models in 'knowledge tracing and student modeling'. The paper concludes by discussing barriers involved in using state-of-the-art ML methods and some suggestions to unleash the power of data and ML to improve educational decision-making. (As Provided).
AnmerkungenSAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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