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Min, Wookhee; Frankosky, Megan H.; Mott, Bradford W.; Rowe, Jonathan P.; Smith, Andy; Wiebe, Eric; Boyer, Kristy Elizabeth; Lester, James C. – IEEE Transactions on Learning Technologies, 2020
A distinctive feature of game-based learning environments is their capacity for enabling stealth assessment. Stealth assessment analyzes a stream of fine-grained student interaction data from a game-based learning environment to dynamically draw inferences about students' competencies through evidence-centered design. In evidence-centered design,…
Descriptors: Game Based Learning, Student Evaluation, Artificial Intelligence, Models
Uto, Masaki; Ueno, Maomi – IEEE Transactions on Learning Technologies, 2016
As an assessment method based on a constructivist approach, peer assessment has become popular in recent years. However, in peer assessment, a problem remains that reliability depends on the rater characteristics. For this reason, some item response models that incorporate rater parameters have been proposed. Those models are expected to improve…
Descriptors: Item Response Theory, Peer Evaluation, Bayesian Statistics, Simulation