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In this paper, we argue that a particular set of issues mars traditional assessment practices. They may be difficult for educators to design and implement; only provide discrete snapshots of performance rather than nuanced views of learning; be unadapted to the particular knowledge, skills, and backgrounds of participants; be tailored to the culture of schooling rather than the cultures schooling is designed to prepare students to enter; and assess skills that humans routinely use computers to perform. We review extant artificial intelligence approaches that–at least partially–address these issues and critically discuss whether these approaches present additional challenges for assessment practice.
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Zachari Swiecki
Hassan Khosravi
Guanliang Chen
SHILAP Revista de lepidopterología
Computers and Education Artificial Intelligence
The University of Melbourne
The University of Queensland
Monash University
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Swiecki et al. (Sat,) studied this question.
www.synapsesocial.com/papers/69dd2da199c691022d99b4a2 — DOI: https://doi.org/10.1016/j.caeai.2022.100075