Titlebook: Artificial Intelligence in Education; 20th International C Seiji Isotani,Eva Millán,Rose Luckin Conference proceedings 2019 Springer Nature

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Developing a Deep Learning-Based Affect Recognition System for Young Childrennt of various systems to capture learners’ emotional states. Young children are one of the biggest learner groups in digital learning environments, but these studies have rarely targeted them. Our current study leverages computer vision and deep learning to analyze young childrens’ learning-related

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Bayesian Diagnosis Tracing: Application of Procedural Misconceptions in Knowledge Tracingprocedure misconceptions. Using a novel dataset with actual student responses, this paper shows the BDT model has better interpretability of the latent factor and minor improvement in out-sample predictability in some specification than the BKT model.

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Analysis of Gamification Elements. A Case Study in a Computer Science Courses. This technique can be used in different sectors like health, marketing, politics or education. In this paper we have focused on education. There are many papers related to the impact that this methodology has on the student’s learning, but only a few of them delve into the gamified elements. They

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Towards Adaptive Worked-Out Examples in an Intelligent Tutoring Systemthree versions of our Intelligent Tutoring System for Computer Science, one that does not include WOEs, and two that differ as concerns WOE length and content. We found that shorter WOEs are more effective for advanced students, whereas novice students learned the same, no matter the presence or len

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https://doi.org/10.1057/9780230116016 from 58 students while problem solving in a game-based learning environment. Results suggest students with different goal orientations use metacognitive processes differently but found no differences in learning. Findings have implications for measuring motivation using multiple data channels to design adaptive game-based learning environments.

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Kelly LeCouvie,Jennifer Pendergastprocedure misconceptions. Using a novel dataset with actual student responses, this paper shows the BDT model has better interpretability of the latent factor and minor improvement in out-sample predictability in some specification than the BKT model.

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