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Emiko Tsutsumi; Yiming Guo; Ryo Kinoshita; Maomi Ueno – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT), the task of tracking the knowledge state of a student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines item response theory (IRT) with a deep learning method, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Academic Ability, Intelligent Tutoring Systems, Artificial Intelligence
Sebastian Gombert; Aron Fink; Tornike Giorgashvili; Ioana Jivet; Daniele Di Mitri; Jane Yau; Andreas Frey; Hendrik Drachsler – International Journal of Artificial Intelligence in Education, 2024
Various studies empirically proved the value of highly informative feedback for enhancing learner success. However, digital educational technology has yet to catch up as automated feedback is often provided shallowly. This paper presents a case study on implementing a pipeline that provides German-speaking university students enrolled in an…
Descriptors: Automation, Student Evaluation, Essays, Feedback (Response)
Wu, Stephen Tze-Inn – ProQuest LLC, 2010
This thesis aims to define and extend a line of computational models for text comprehension that are humanly plausible. Since natural language is human by nature, computational models of human language will always be just that--models. To the degree that they miss out on information that humans would tap into, they may be improved by considering…
Descriptors: Comprehension, Semantics, Syntax, Short Term Memory