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Yildirim-Erbasli, Seyma N.; Bulut, Okan; Demmans Epp, Carrie; Cui, Ying – Journal of Educational Technology Systems, 2023
Conversational agents have been widely used in education to support student learning. There have been recent attempts to design and use conversational agents to conduct assessments (i.e., conversation-based assessments: CBA). In this study, we developed CBA with constructed and selected-response tests using Rasa--an artificial intelligence-based…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Computer Mediated Communication, Formative Evaluation
Conijn, Rianne; Martinez-Maldonado, Roberto; Knight, Simon; Buckingham Shum, Simon; Van Waes, Luuk; van Zaanen, Menno – Computer Assisted Language Learning, 2022
Current writing support tools tend to focus on assessing final or intermediate products, rather than the writing process. However, sensing technologies, such as keystroke logging, can enable provision of automated feedback during, and on aspects of, the writing process. Despite this potential, little is known about the critical indicators that can…
Descriptors: Automation, Feedback (Response), Writing Evaluation, Learning Analytics
Sense, Florian; van der Velde, Maarten; van Rijn, Hedderik – Journal of Learning Analytics, 2021
Modern educational technology has the potential to support students to use their study time more effectively. Learning analytics can indicate relevant individual differences between learners, which adaptive learning systems can use to tailor the learning experience to individual learners. For fact learning, cognitive models of human memory are…
Descriptors: Predictor Variables, Undergraduate Students, Learning Analytics, Cognitive Psychology
Conejo, Ricardo; Barros, Beatriz; Bertoa, Manuel F. – IEEE Transactions on Learning Technologies, 2019
This paper presents an innovative method to tackle the automatic evaluation of programming assignments with an approach based on well-founded assessment theories (Classical Test Theory (CTT) and Item Response Theory (IRT)) instead of heuristic assessment as in other systems. CTT and/or IRT are used to grade the results of different items of…
Descriptors: Computer Assisted Testing, Grading, Programming, Item Response Theory
Kaburlasos, Vassilis G.; Marinagi, Catherine C.; Tsoukalas, Vassilis Th. – Computers & Education, 2008
This work presents innovative cybernetics (feedback) techniques based on Bayesian statistics for drawing questions from an Item Bank towards personalized multi-student improvement. A novel software tool, namely "Module for Adaptive Assessment of Students" (or, "MAAS" for short), implements the proposed (feedback) techniques. In conclusion, a pilot…
Descriptors: Feedback (Response), Student Improvement, Computer Science, Bayesian Statistics
Hwang, Gwo-Jen; Cheng, Hsiang; Chu, Carol H. C.; Tseng, Judy C. R.; Hwang, Gwo-Haur – International Journal of Distance Education Technologies, 2007
In the past decades, English learning has received lots of attention all over the world, especially for those who are not native English speakers. Various English learning and testing systems have been developed on the Internet. Nevertheless, most existing English testing systems represent the learning status of a student by assigning that student…
Descriptors: English Instruction, Web Based Instruction, Intelligent Tutoring Systems, Verbs