Titlebook: Artificial Intelligence in Education; 16th International C H. Chad Lane,Kalina Yacef,Philip Pavlik Conference proceedings 2013 Springer-Ver

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https://doi.org/10.1007/978-3-319-61596-7st, fear, and sadness were comparatively rare. The emotions varied as a function of instructional scaffolds and were systematically linked to different student behaviors (idling, constructing code, running code). Boredom, flow/engaged, and confusion were also correlated with performance outcomes. Im

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https://doi.org/10.1057/9780230291768participants also scored substantially higher on a subsequent knowledge test (.= 1.27). These results suggest that choice and text difficulty differentially impact mind wandering, engagement, and learning and provide important considerations for the design of ITSs and serious games with a reading co

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Governance in Chinese Family Business,he result shows that modeling at coarser grain sizes can actually result in higher predictive accuracy, and data about classmates’ performance is results in a higher predictive accuracy on unseen test data.

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Identifying Localization in Peer Reviews of Argument Diagrams

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