Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 9 |
Descriptor
Source
International Journal of… | 9 |
Author
Aleven, Vincent | 2 |
Gilbert, Stephen B. | 2 |
Anwar, Mohd | 1 |
Blessing, Stephen B. | 1 |
Bonner, Desmond | 1 |
Bourdeau, Jacqueline | 1 |
Boyer, Kristy Elizabeth | 1 |
Dorneich, Michael C. | 1 |
Greer, Jim | 1 |
Ha, Eun Young | 1 |
Haddawy, Peter | 1 |
More ▼ |
Publication Type
Journal Articles | 9 |
Reports - Research | 9 |
Education Level
Higher Education | 6 |
Postsecondary Education | 6 |
Elementary Secondary Education | 2 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Gilbert, Stephen B.; Slavina, Anna; Dorneich, Michael C.; Sinatra, Anne M.; Bonner, Desmond; Johnston, Joan; Holub, Joseph; MacAllister, Anastacia; Winer, Eliot – International Journal of Artificial Intelligence in Education, 2018
With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of…
Descriptors: Tutors, Teamwork, Intelligent Tutoring Systems, Tutoring
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
Miller, L. D.; Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen – International Journal of Artificial Intelligence in Education, 2012
Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…
Descriptors: Computer Science Education, Metadata, Internet, Artificial Intelligence
Anwar, Mohd; Greer, Jim – International Journal of Artificial Intelligence in Education, 2012
An e-learning discussion forum, an essential component of today's e-learning systems, offers a platform for social learning activities. However, as learners participate in the discussion forum, privacy emerges as a major concern. Privacy concerns in social learning activities originate from one learner's inability to convey a desired presentation…
Descriptors: Foreign Countries, Electronic Learning, Socialization, Learning Activities
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
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
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
Hayashi, Yusuke; Bourdeau, Jacqueline; Mizoguchi, Riichiro – International Journal of Artificial Intelligence in Education, 2009
This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and…
Descriptors: Foreign Countries, Theory Practice Relationship, Engineering, Teaching Methods
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