Publication Date
| In 2026 | 0 |
| Since 2025 | 161 |
| Since 2022 (last 5 years) | 568 |
| Since 2017 (last 10 years) | 1115 |
| Since 2007 (last 20 years) | 1919 |
Descriptor
Source
Author
Publication Type
Education Level
Location
| Taiwan | 49 |
| China | 46 |
| United Kingdom | 29 |
| Pennsylvania | 27 |
| Germany | 25 |
| Turkey | 24 |
| Canada | 22 |
| Massachusetts | 22 |
| Spain | 22 |
| United States | 16 |
| California | 15 |
| More ▼ | |
Laws, Policies, & Programs
| Every Student Succeeds Act… | 3 |
| Elementary and Secondary… | 2 |
| American Rescue Plan Act 2021 | 1 |
| No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 4 |
| Meets WWC Standards with or without Reservations | 6 |
| Does not meet standards | 2 |
Huang, Chenn-Jung; Liu, Ming-Chou; Chu, San-Shine; Cheng, Chih-Lun – Computers and Education, 2007
This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to…
Descriptors: Web Based Instruction, Intelligent Tutoring Systems, Courseware, Internet
Peer reviewedSolomos, Konstantinos; Avouris, Nikolaos – Journal of Interactive Learning Research, 1999
Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)
Descriptors: Artificial Intelligence, Educational Environment, Intelligent Tutoring Systems, Interaction
Peer reviewedDang, Trang; Ghenniwa, Hamada; Kamel, Mohamed – Journal of Interactive Learning Research, 1999
Proposes an interface agent for intelligent tutoring systems that creates a collaborative learning environment between the learner and the tutoring software. Describes implementation of a prototype using the IBM Agent Builder Environment Toolkit to use with an intelligent tutoring system for algebra and considers benefits in a lifelong learning…
Descriptors: Algebra, Computer Interfaces, Educational Environment, Intelligent Tutoring Systems
Peer reviewedMerrill, M. David – Instructional Science, 1998
Describes ID Expert, an intelligent computer-based multimedia interactive instructional development and delivery system. Topics include instructional transactions with built-in instructional design; knowledge bases and knowledge representation; automated instructional design; and similarities to GTE (Generic Tutoring Environment). (Author/LRW)
Descriptors: Automation, Instructional Design, Intelligent Tutoring Systems, Knowledge Representation
Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
Koedinger, Kenneth R.; Aleven, Vincent – Educational Psychology Review, 2007
Intelligent tutoring systems are highly interactive learning environments that have been shown to improve upon typical classroom instruction. Cognitive Tutors are a type of intelligent tutor based on cognitive psychology theory of problem solving and learning. Cognitive Tutors provide a rich problem-solving environment with tutorial guidance in…
Descriptors: Intelligent Tutoring Systems, Metacognition, Tutors, Cognitive Psychology
Andersson, David; Reimers, Karl – Journal of Educational Technology, 2010
The field of education is experiencing a rapid shift as internet-enabled distance learning becomes more widespread. Often, traditional classroom teaching pedagogical techniques can be ill-suited to the online environment. While a traditional entry-level class might see a student attrition rate of 5-10%, the same teaching pedagogy in an online…
Descriptors: Computer Software, Computer Oriented Programs, Online Courses, Electronic Learning
Ben-Naim, Dror; Bain, Michael; Marcus, Nadine – International Working Group on Educational Data Mining, 2009
It has been recognized that in order to drive Intelligent Tutoring Systems (ITSs) into mainstream use by the teaching community, it is essential to support teachers through the entire ITS process: Design, Development, Deployment, Reflection and Adaptation. Although research has been done on supporting teachers through design to deployment of ITSs,…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Computer System Design, Computer Managed Instruction
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
Shuqun, Yang; Shuliang, Ding; Zhiqiang, Yao – International Journal of Distance Education Technologies, 2009
Cognitive diagnosis (CD) plays an important role in intelligent tutoring system. Computerized adaptive testing (CAT) is adaptive, fair, and efficient, which is suitable to large-scale examination. Traditional cognitive diagnostic test needs quite large number of items, the efficient and tailored CAT could be a remedy for it, so the CAT with…
Descriptors: Monte Carlo Methods, Distance Education, Adaptive Testing, Intelligent Tutoring Systems
Steinberg, Linda S.; Gitomer, Drew H. – 1992
A model of the interface design process is proposed that makes use of two interdependent levels of cognitive analysis: the study of the criterion task through an analysis of expert/novice differences and the evaluation of the working user interface design through the application of a practical interface analysis methodology (GOMS model). This dual…
Descriptors: Cognitive Processes, Computer Interfaces, Hydraulics, Intelligent Tutoring Systems
Shute, Valerie J. – 1994
For an intelligent tutoring system (ITS) to earn its "I", it must be able to (1) accurately diagnose students' knowledge structures, skills, and/or learning styles using principles, rather than pre-programmed responses, to decide what to do next; and (2) adapt instruction accordingly. While some maintain that remediation actually…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Knowledge Representation, Models
Peer reviewedSchwarz, Baruch; Zehavi, Nurit – Journal of Research on Computing in Education, 1996
Discussion of the nature of the algebraic and graphical representations of functions focuses on a study integrating cognitive research and the development of an intelligent tutoring system (ITS), the Function Characteristics Tutor, to evaluate the effects of pairing representations of mathematical functions on high school students. (Author/LRW)
Descriptors: Algebra, Functions (Mathematics), Graphs, Intelligent Tutoring Systems
Peer reviewedBaffes, Paul; Mooney, Raymond – Journal of Artificial Intelligence in Education, 1996
Discussion of student modeling and intelligent tutoring systems focuses on the development of the ASSERT algorithm (Acquiring Stereotypical Student Errors by Refining Theories). Topics include overlay modeling; bug libraries (databases of student misconceptions); dynamic modeling; refinement-based modeling; and experimental results from tests at…
Descriptors: Algorithms, Databases, Error Correction, Higher Education

Direct link
