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Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2014
Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…
Descriptors: Algebra, Peer Teaching, Tutoring, Cooperative Learning
Adamson, David; Dyke, Gregory; Jang, Hyeju; Rosé, Carolyn Penstein – International Journal of Artificial Intelligence in Education, 2014
This paper investigates the use of conversational agents to scaffold on-line collaborative learning discussions through an approach called Academically Productive Talk (APT). In contrast to past work on dynamic support for collaborative learning, where agents were used to elevate conceptual depth by leading students through directed lines of…
Descriptors: Cooperative Learning, Scaffolding (Teaching Technique), Intelligent Tutoring Systems, Electronic Learning
Pardos, Zachary A.; Dailey, Matthew D.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
The well established, gold standard approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pre-test and post-test design. RCTs have been used in the intelligent tutoring community for decades to determine which questions and tutorial feedback work best. Practically speaking, however,…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Pretests Posttests, Educational Research
Boyer, Kristy Elizabeth; Phillips, Robert; Ingram, Amy; Ha, Eun Young; Wallis, Michael; Vouk, Mladen; Lester, James – International Journal of Artificial Intelligence in Education, 2011
Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This article addresses that challenge through a machine learning…
Descriptors: Markov Processes, Intelligent Tutoring Systems, Tutoring, Program Effectiveness
Zhang, Li; Gillies, Marco; Dhaliwal, Kulwant; Gower, Amanda; Robertson, Dale; Crabtree, Barry – International Journal of Artificial Intelligence in Education, 2009
This paper describes a multi-user role-playing environment, referred to as "e-drama", which enables groups of people to converse online, in scenario driven virtual environments. The starting point of this research, is an existing application known as "edrama", a 2D graphical environment in which users are represented by static cartoon figures.…
Descriptors: Disabilities, Cartoons, Interpersonal Relationship, Interaction
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Mitrovic, Antonija; Martin, Brent; Suraweera, Pramuditha; Zakharov, Konstantin; Milik, Nancy; Holland, Jay; McGuigan, Nicholas – International Journal of Artificial Intelligence in Education, 2009
Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized.…
Descriptors: Foreign Countries, Investment, Intelligent Tutoring Systems, Artificial Intelligence
Blessing, Stephen B.; Gilbert, Stephen B.; Ourada, Stephen; Ritter, Steven – International Journal of Artificial Intelligence in Education, 2009
Intelligent Tutoring Systems (ITSs) that employ a model-tracing methodology have consistently shown their effectiveness. However, what evidently makes these tutors effective, the cognitive model embedded within them, has traditionally been difficult to create, requiring great expertise and time, both of which come at a cost. Furthermore, an…
Descriptors: Intelligent Tutoring Systems, Cognitive Processes, Models, Expertise
Ogan, Amy; Aleven, Vincent; Jones, Christopher – International Journal of Artificial Intelligence in Education, 2009
Most successes in intelligent tutoring systems have come in well-defined domains like algebra or physics. We investigate how to support students in acquiring ill-defined skills of intercultural competence using an online environment that employs clips of feature films from a target culture. To test the effectiveness of a set of attention-focusing…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Perspective Taking, Cultural Awareness
Kim, Julia M.; Hill, Randall W., Jr.; Durlach, Paula J.; Lane, H. Chad; Forbell, Eric; Core, Mark; Marsella, Stacy; Pynadath, David; Hart, John – International Journal of Artificial Intelligence in Education, 2009
Negotiation skills are essential in everyday life, whether in a professional or personal context. Negotiation enables two parties to address misunderstandings and avoid conflicts through an exchange that depends as much on the interpersonal skills of the negotiators as the tactics employed. Acquiring these skills requires not only sound conceptual…
Descriptors: Foreign Countries, Concept Formation, Cultural Context, Intelligent Tutoring Systems
Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2009
In well-defined domains such as Physics, Mathematics, and Chemistry, solutions to a posed problem can objectively be classified as correct or incorrect. In ill-defined domains such as medicine, the classification of solutions to a patient problem as correct or incorrect is much more complex. Typical tutoring systems accept only a small set of…
Descriptors: Foreign Countries, Problem Based Learning, Problem Solving, Correlation

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