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

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Bemerkenswerte Familienunternehmen, repair such errors can be a useful aid to the developers for their productivity. In this work, we propose a deep generative model, RepairNet, that automatically repairs programs that fail at compile time. RepairNet is based on sequence-to-sequence modeling and uses both code and error messages to r

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https://doi.org/10.1007/978-3-322-84233-6sistence, when students are working in online learning system. This work has, in cases, treated any student who completes more than ten items on a topic without mastering it as being in need of intervention. By contrast, the broader fields of education and human development have recognized the value

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Frank Hannes,Thorsten Kuhn,Miriam Brückmannrceptions about the learning activity drive their experience of frustration and their subsequent choices during learning. In this paper, we adopt a mixed-methods approach, using automated detectors of affect to signal classroom researchers to interview a specific student at a specific time. We hand-

Chemotherapy

Frank Hannes,Thorsten Kuhn,Miriam Brückmannnalized practice system for introductory Java programming. We present the design of two types of explanations to justify recommendation of next learning activity to practice. The value of these explainable recommendations was assessed in a semester-long classroom study. The paper analyses the observ

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Frank Hannes,Thorsten Kuhn,Miriam Brückmannr applications in student modeling, it is useful to find structure in the set of all submitted solutions. We propose a generic, modular algorithm for the construction of interpretable clustering of students’ solutions in problem-solving activities. We describe a specific realization of the algorithm

minion

https://doi.org/10.1007/978-3-8349-9558-2h a learning activity in terms of four different engagement modes—Interactive, Constructive, Active, and Passive—and it predicts that increased cognitive engagement will yield improved learning. However, a key open question is how best to translate the ICAP theory into the design of adaptive scaffol