Roger Nkambou

Beverly Woolf

Susanne Lajoie

Esma Aimeur

The9thInternationalConferenceonIntelligentTutoringSystems(ITS2008)was heldJune 23–27,2008inMontreal. Thisyearwecelebratedthe 20thanniversary ofthe conferencefounded in 1988in Montreal. We havehadbiennial conferences for most of the past 10 years around the world, including in Brazil, Taiwan, France, Canada, and the USA. These ITS conferences provide a forum for the interchange of ideas in all areas of computer science and human learning, a unique environment to exchange ideas and support new developments relevant for the future. The 2008 conference was a symbolic milestone that enabled us to look back at what has been achieved and what is currently being done, in order to face the challenges of tomorrow. Much has changed in the last 20 years in terms of hardware, software, p- grammers,and education stakeholders. Technology is now networked, pervasive, and availableanyplace and anytime. The potential exists to provide customized, ubiquitous guidance andinstruction. However,much has remainedthe same and the need is just as great to model the learner, teaching strategies and domain knowledge. This year we saw an increase in research into student a?ect (mo- vation, boredom, and frustration), speci?cally attempts to detect student a?ect, while feedback studies consideredwhich responses to provide given both student cognition and a?ect. Studies also looked at the impact on learning of positive feedbackandpolitenessinfeedback. Newresearchwasseenindataminingbased on larger studies that use data from real students to diagnose e?ective learning and teaching. So much interest has been generated in this area that the ?rst International Conference on Educational Data Mining was co-located with ITS 2008.

9th International Conference on Intelligent Tutoring Systems, ITS 2008, Montreal, Canada, June 23-27, 2008, Proceedings

Intelligent Tutoring Systems

Vincent S. Tseng

Philippe Fournier-Viger

Jerry Chun-Wei Lin

Bay Vo

This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.

Theory, Algorithms and Applications

High-Utility Pattern Mining

Julita Vassileva

Roger Azevedo

This book constitutes the proceedings of the 14th International Conference on Intelligent Tutoring Systems, IST 2018, held in Montreal, Canada, in June 2018. The 26 full papers and 22 short papers presented in this volume were carefully reviewed and selected from 120 submissions. In the back matter of the volume 20 poster papers and 6 doctoral consortium papers are included. They deal with the use of advanced computer technologies and interdisciplinary research for enabling, supporting and enhancing human learning.

14th International Conference, ITS 2018, Montreal, QC, Canada, June 11–15, 2018, Proceedings

This book constitutes the refereed proceedings of the 9th International Conference on Intelligent Tutoring Systems, ITS 2008, held in Montreal, Canada, in June 2008. The 63 revised full papers and 61 poster papers presented together with abstracts of 5 keynote talks were carefully reviewed and selected from 207 submissions. The papers are organized in topical sections on emotion and affect, tutor evaluation, student modeling, machine learning, authoring tools , tutor feedback and intervention, data mining, e-learning and Web-based ITS, natural language techniques and dialogue, narrative tutors and games, semantic Web and ontology, cognitive models, and collaboration.

Roger Nkambou

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