Publication Date
| In 2015 | 1 |
| Since 2014 | 4 |
| Since 2011 (last 5 years) | 8 |
| Since 2006 (last 10 years) | 19 |
| Since 1996 (last 20 years) | 19 |
Descriptor
Source
| International Journal of… | 19 |
Author
| Aleven, Vincent | 2 |
| Martin, Brent | 2 |
| Mitrovic, Antonija | 2 |
| VanLehn, Kurt | 2 |
| Adamson, David | 1 |
| Anwar, Mohd | 1 |
| Baker, Ryan S. | 1 |
| Beaulieu, Gabriel | 1 |
| Blessing, Stephen B. | 1 |
| Bratt, Elizabeth Owen | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 19 |
| Reports - Research | 15 |
| Reports - Descriptive | 2 |
| Reports - Evaluative | 2 |
Education Level
| Postsecondary Education | 19 |
| Higher Education | 17 |
| Adult Education | 2 |
| Elementary Secondary Education | 1 |
| High Schools | 1 |
| Secondary Education | 1 |
Audience
Showing 1 to 15 of 19 results
Paquette, Luc; Lebeau, Jean-François; Beaulieu, Gabriel; Mayers, André – International Journal of Artificial Intelligence in Education, 2015
Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…
Descriptors: Intelligent Tutoring Systems, Intervention, Instruction, Automation
Yoo, Jaebong; Kim, Jihie – International Journal of Artificial Intelligence in Education, 2014
Although many college courses adopt online tools such as Q&A online discussion boards, there is no easy way to measure or evaluate their effect on learning. As a part of supporting instructional assessment of online discussions, we investigate a predictive relation between characteristics of discussion contributions and student performance.…
Descriptors: Discussion Groups, Participation, Group Activities, Student Projects
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
Weragama, Dinesha; Reye, Jim – International Journal of Artificial Intelligence in Education, 2014
Programming is a subject that many beginning students find difficult. The PHP Intelligent Tutoring System (PHP ITS) has been designed with the aim of making it easier for novices to learn the PHP language in order to develop dynamic web pages. Programming requires practice. This makes it necessary to include practical exercises in any ITS that…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Programming Languages
Dela Rosa, Kevin; Eskenazi, Maxine – International Journal of Artificial Intelligence in Education, 2013
Self-assessment questionnaires have long been used in tutoring systems to help researchers measure and evaluate various aspects of a student's performance during learning activities. In this paper, we chronicle the efforts made in the REAP project, a language tutor developed to teach vocabulary to ESL students through reading activities, to…
Descriptors: Self Evaluation (Individuals), Questionnaires, Student Evaluation, Intelligent Tutoring Systems
Gowda, Sujith M.; Baker, Ryan S.; Corbett, Albert T.; Rossi, Lisa M. – International Journal of Artificial Intelligence in Education, 2013
Recent research has extended student modeling to infer not just whether a student knows a skill or set of skills, but also whether the student has achieved robust learning--learning that enables the student to transfer their knowledge and prepares them for future learning (PFL). However, a student may fail to have robust learning in two fashions:…
Descriptors: Learning Processes, Transfer of Training, Outcomes of Education, Intelligent Tutoring Systems
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
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
Hausmann, Robert G. M.; VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2010
Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to comprehension,…
Descriptors: Instructional Design, Intelligent Tutoring Systems, College Students, Predictor Variables
D'Mello, Sidney K.; Lehman, Blair; Person, Natalie – International Journal of Artificial Intelligence in Education, 2010
We explored the affective states that students experienced during effortful problem solving activities. We conducted a study where 41 students solved difficult analytical reasoning problems from the Law School Admission Test. Students viewed videos of their faces and screen captures and judged their emotions from a set of 14 states (basic…
Descriptors: Video Technology, Electronic Learning, Handheld Devices, Student Attitudes
Bratt, Elizabeth Owen – International Journal of Artificial Intelligence in Education, 2009
This paper describes the role of simulation-based training in the military. Interviews and observations of military instructors in the damage control and shiphandling domains provide examples of how the instructors extend the student's training beyond the well-defined simulated world with qualitative reasoning about context, hypothetical variants,…
Descriptors: Intelligent Tutoring Systems, Military Training, Simulation, Tutoring
Weerasinghe, Amali; Mitrovic, Antonija; Martin, Brent – International Journal of Artificial Intelligence in Education, 2009
One of the critical factors contributing to the effectiveness of human tutoring is the conversational aspect of the instruction. Our goal is to develop a general model for supporting dialogues with menu-based input that could be used in both well- and ill-defined instructional tasks. We have previously studied how human tutors provide additional…
Descriptors: Intelligent Tutoring Systems, Dialogs (Language), Databases, Design
Siler, Stephanie Ann; VanLehn, Kurt – International Journal of Artificial Intelligence in Education, 2009
Face-to-face (FTF) human-human tutoring has ranked among the most effective forms of instruction. However, because computer-mediated (CM) tutoring is becoming increasingly common, it is instructive to evaluate its effectiveness relative to face-to-face tutoring. Does the lack of spoken, face-to-face interaction affect learning gains and…
Descriptors: Feedback (Response), Undergraduate Students, Student Motivation, Tutoring
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
Previous Page | Next Page »
Pages: 1 | 2
Peer reviewed
Direct link
