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Lara Nieto-Márquez, Natalia; Baldominos, Alejandro; Pérez-Nieto, Miguel Ángel – Education Sciences, 2020
Metacognition is a construct that is noteworthy for its relationship with the prediction and enhancement of student performance. It is of interest in education, as well as in the field of cognitive psychology, because it contributes to competencies, such as learning to learn and the understanding of information. This study conducted research at a…
Descriptors: Metacognition, Elementary School Students, Measures (Individuals), Prediction
Matsuda, Noboru; Weng, Wenting; Wall, Natalie – International Journal of Artificial Intelligence in Education, 2020
The effect of metacognitive scaffolding for learning by teaching was investigated and compared against learning by being tutored. Three versions of an online learning environment for learning algebra equations were created: (1) APLUS that allows students to interactively teach a synthetic peer with a goal to have the synthetic peer pass the quiz…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Tutoring, Intelligent Tutoring Systems
Greer, Jim; Mark, Mary – International Journal of Artificial Intelligence in Education, 2016
The 1993 paper in "IJAIED" on evaluation methods for Intelligent Tutoring Systems (ITS) still holds up well today. Basic evaluation techniques described in that paper remain in use. Approaches such as kappa scores, simulated learners and learning curves are refinements on past evaluation techniques. New approaches have also arisen, in…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology, Evaluation Methods
Twenty Years On: Reflections on "Supporting the Use of External Representations in Problem Solving"…
Cox, Richard; Brna, Paul – International Journal of Artificial Intelligence in Education, 2016
We reflect upon a paper we wrote that was published in 1995 (20 years ago). We outline the motivation for the work and situate it in the state of the art at that time. We suggest that a key contribution was to highlight the need to provide support for learners who reason with external representations. The support must be flexible enough to…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Problem Solving, Cognitive Processes
Ritter, Steven – International Journal of Artificial Intelligence in Education, 2016
"An Architecture for Plug-in Tutor Agents" (Ritter and Koedinger 1996) proposed a software architecture designed around the idea that tutors could be built as plug-ins for existing software applications. Looking back on the paper now, we can see that certain assumptions about the future of software architecture did not come to be, making…
Descriptors: Intelligent Tutoring Systems, Computer Software, Technology Uses in Education, Teaching Methods
Chen, Yetian; González-Brenes, José P.; Tian, Jin – International Educational Data Mining Society, 2016
Skill prerequisite information is useful for tutoring systems that assess student knowledge or that provide remediation. These systems often encode prerequisites as graphs designed by subject matter experts in a costly and time-consuming process. In this paper, we introduce "Combined student Modeling and prerequisite Discovery"…
Descriptors: Bayesian Statistics, Prerequisites, Graphs, Intelligent Tutoring Systems
Maria-Dorinela Dascalu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2022
The use of technology as a facilitator in learning environments has become increasingly prevalent with the global pandemic caused by COVID-19. As such, computer-supported collaborative learning (CSCL) gains a wider adoption in contrast to traditional learning methods. At the same time, the need for automated tools capable of assessing and…
Descriptors: Computational Linguistics, Longitudinal Studies, Technology Uses in Education, Teaching Methods
Fletcher, J. D.; Sottilare, Robert A. – International Journal of Artificial Intelligence in Education, 2018
Teams and teamwork are ubiquitous in military and civilian organizations. Their importance to organizational success cannot be overstated. This article describes the relationship and effect of three concepts: Intelligent Tutoring Systems (ITSs), shared mental models, and teamwork. The nexus between these concepts is examined to determine its…
Descriptors: Teamwork, Teaching Methods, Intelligent Tutoring Systems, Schemata (Cognition)
Holmes, Mike; Latham, Annabel; Crockett, Keeley; O'Shea, James D. – IEEE Transactions on Learning Technologies, 2018
Comprehension is an important cognitive state for learning. Human tutors recognize comprehension and non-comprehension states by interpreting learner non-verbal behavior (NVB). Experienced tutors adapt pedagogy, materials, and instruction to provide additional learning scaffold in the context of perceived learner comprehension. Near real-time…
Descriptors: Comprehension, Classification, Artificial Intelligence, Networks
Alsoliman, Badr Salman H. – International Education Studies, 2018
Objective: The study aims to determine the barriers and potentials of educational robotics in Saudi schools based on the perceptions of Saudi school teachers. Methods: Both qualitative and quantitative research approaches were opted to assess the aim of the study. An open-ended survey has been conducted among the teachers, who use robotics in…
Descriptors: Foreign Countries, Robotics, Teaching Methods, Barriers
Ritchey, ChristiAnne – ProQuest LLC, 2018
The mathematics test is the most difficult test in the GED (General Education Development) Test battery, largely due to the presence of story problems. Raising performance levels of story problem-solving would have a significant effect on GED Test passage rates. The subject of this formative research study is Ms. Stephens' Categorization Practice…
Descriptors: Mathematics Tests, General Education, Formative Evaluation, Word Problems (Mathematics)
Karaci, Abdulkadir; Piri, Zeynep; Akyüz, Halil Ibrahim; Bilgiici, Göksal – Online Submission, 2018
The aim of this study is to understand how students accept an Intelligent Tutoring System (ITS) in terms of the Technology Acceptance Model. For this study, a web-based intelligent tutoring system was used by 38 university students for four weeks. Fifteen randomly selected students participated in two semi-structured focus group interviews which…
Descriptors: Student Attitudes, Intelligent Tutoring Systems, Technology Uses in Education, Educational Technology
Leblay, Joffrey; Rabah, Mourad; Champagnat, Ronan; Nowakowski, Samuel – International Association for Development of the Information Society, 2018
How can we learn to use properly business software, digital environments, games or intelligent tutoring systems (ITS)? Mainly, we assume that the new user will learn by doing. But what about the efficiency of such a method? Our approach proposes an answer by introducing on-line coaching. In learning process, learners may need guidance to help them…
Descriptors: Intelligent Tutoring Systems, Coaching (Performance), Efficiency, Learning Processes
Weltman, Heather Richelle; Timchenko, Victoria; Sofios, Haritos Emanuel; Ayres, Paul; Marcus, Nadine – European Journal of Engineering Education, 2019
Adaptive tutorials enable engaged, personalised and interactive online learning that includes instant adaptive feedback. By integrating an adaptive tutorial into a large and diverse engineering mathematics course, we explored its potential to support and guide students' learning from afar. The aim of this study was to assess whether students…
Descriptors: Intelligent Tutoring Systems, Mathematics Instruction, Instructional Effectiveness, Engineering Education
Tan, Seng-Chee – Australasian Journal of Educational Technology, 2019
Using computers as cognitive tools or mindtools has created impact in education since their introduction in the 1990s. One main characteristic is the notion of learning with computers as intellectual partners: engaging learners in higher level thinking while taking away the lower level cognitive load such as computing and digital storage. In…
Descriptors: Computer Assisted Instruction, Learning Theories, Computer Uses in Education, Educational Technology

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