Download Artificial Intelligence in Education: 17th International by Cristina Conati, Neil Heffernan, Antonija Mitrovic, M. PDF

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By Cristina Conati, Neil Heffernan, Antonija Mitrovic, M. Felisa Verdejo

This publication constitutes the refereed court cases of the seventeenth foreign convention on man made Intelligence in schooling, AIED 2015, held in Madrid, Spain, in June 2015.

The 50 revised complete papers offered including three keynotes, seventy nine poster displays, thirteen doctoral consortium papers, sixteen workshop abstracts, and eight interactive occasion papers have been rigorously reviewed and chosen from various submissions. The convention offers possibilities for the cross-fertilization of ways, innovations and ideas from the various fields that contain AIED, together with computing device technological know-how, cognitive and studying sciences, schooling, online game layout, psychology, sociology, linguistics, in addition to many domain-specific areas.

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Read or Download Artificial Intelligence in Education: 17th International Conference, AIED 2015, Madrid, Spain, June 22-26, 2015. Proceedings PDF

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Extra info for Artificial Intelligence in Education: 17th International Conference, AIED 2015, Madrid, Spain, June 22-26, 2015. Proceedings

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Mihai Dascalu, Larise L. Stavarache, Philippe Dessus, Stefan Trausan-Matu, Danielle S. McNamara, and Maryse Bianco Talk, Tutor, Explore, Learn: Intelligent Tutoring and Exploration for Robust Learning . . . . . . . . . . . . . . . . . . . . Beate Grawemeyer, Sergio Gutierrez-Santos, Wayne Holmes, Manolis Mavrikis, Nikol Rummel, Claudia Mazziotti, and Ruth Janning 911 913 915 917 Reasoning Mind Genie 3: Interactive Demonstration. . . . . .

This aids meaningful learning, as relevant prior knowledge is able to be integrated with new information [3]. Additionally, this paper investigates whether adapting the returned concept map to the specific question context provides further learning benefits. This research develops a framework enabling the automated extraction of question-specific concept maps to answer learner questions using NLP and graph theory techniques. These concept maps assist the learner to understand the interrelationships between concepts for parallel processing in contrast to the sequential nature of text-based answers.

Before testing our hypothesis that students who used the experimental version of Rimac would outperform students who used the control version, we compared pretest scores and time on task between conditions. There were no statistically significant between-group differences in pretest scores considering all problems combined, multiple-choice problems or open-response problems. 05) which prompted us to perform an ANCOVA to test the effect of condition on gain score, using time on task as a covariate to control for its possible effects.

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