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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)
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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
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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
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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
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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
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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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Tafazoli, Dara; María, Elena Gómez; Huertas Abril, Cristina A. – International Journal of Information and Communication Technology Education, 2019
Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Teaching Methods, Interdisciplinary Approach
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Mustafa, Ghulam; Abbas, Muhammad Azeem; Hafeez, Yaser; Khan, Sharifullah; Hwang, Gwo-Jen – Interactive Learning Environments, 2019
During early childhood, children start developing their cognitive, social, emotional, and behavioural skills, laying the foundation for life-long learning. Cognitive skills are usually taught in traditional classrooms through the use of textbooks and worksheets. The learning content in these textbooks and worksheets is static pre-authored content…
Descriptors: Cognitive Development, Preschool Children, Child Development, Skill Development
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Ibili, Emin; Billinghurst, Mark – International Journal of Assessment Tools in Education, 2019
In this study, the relationship between the usability of a mobile Augmented Reality (AR) tutorial system and cognitive load was examined. In this context, the relationship between perceived usefulness, the perceived ease of use, and the perceived natural interaction factors and intrinsic, extraneous, germane cognitive load were investigated. In…
Descriptors: Cognitive Processes, Difficulty Level, Correlation, Usability
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Cook, Joshua; Lynch, Collin F.; Hicks, Andrew G.; Mostafavi, Behrooz – International Educational Data Mining Society, 2017
BKT and other classical student models are designed for binary environments where actions are either correct or incorrect. These models face limitations in open-ended and data-driven environments where actions may be correct but non-ideal or where there may even be degrees of error. In this paper we present BKT-SR and RKT-SR: extensions of the…
Descriptors: Models, Bayesian Statistics, Data Use, Intelligent Tutoring Systems
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Guerrero-Roldán, Ana-Elena; Rodríguez-González, M. Elena; Bañeres, David; Elasri-Ejjaberi, Amal; Cortadas, Pau – International Journal of Educational Technology in Higher Education, 2021
Several tools and resources have been developed in the past years to enhance the teaching and learning process. Most of them are focused on the process itself, but few focus on the assessment process to detect at-risk learners for later acting through feedback to support them to succeed and pass the course. This research paper presents a case…
Descriptors: Intelligent Tutoring Systems, Electronic Learning, Technology Uses in Education, Virtual Universities
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Prihar, Ethan; Heffernan, Neil – International Educational Data Mining Society, 2021
Similar content has tremendous utility in classroom and online learning environments. For example, similar content can be used to combat cheating, track students' learning over time, and model students' latent knowledge. These different use cases for similar content all rely on different notions of similarity, which make it difficult to determine…
Descriptors: Computer Software, Middle School Teachers, Mathematics Teachers, College Students
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Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
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