Titlebook: Artificial Intelligence in Education; 22nd International C Ido Roll,Danielle McNamara,Vania Dimitrova Conference proceedings 2021 Springer

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Engendering Trust in Automated Feedback: A Two Step Comparison of?Feedbacks in Gesture Based Learninmated feedback as it may not be as good as the manual feedback. We use an ASL learning application that provides fine grained explainable feedback and follow a two step process to present a comparison between the automated feedback and the manual feedback provided by experts.

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Frank Hannes,Thorsten Kuhn,Miriam Brückmannresponse datasets. We also qualitatively evaluate their ability in identifying common student errors in the form of clusters of incorrect options across different questions that correspond to the same error.

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Evaluating Critical Reinforcement Learning Framework in the Fieldcal-RL framework is empirically evaluated from two perspectives: whether optimal actions . be carried out in critical states (.) and whether only carrying out optimal actions in critical states is as effective as a fully-executed RL policy (.). Our results confirmed both hypotheses.

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