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Damacharla, Praveen; Dhakal, Parashar; Stumbo, Sebastian; Javaid, Ahmad Y.; Ganapathy, Subhashini; Malek, David A.; Hodge, Douglas C.; Devabhaktuni, Vijay – International Journal of Artificial Intelligence in Education, 2019
As part of a perennial project, our team is actively engaged in developing new synthetic assistant (SA) technologies to assist in training combat medics and medical first responders. It is critical that medical first responders are well trained to deal with emergencies more effectively. This would require real-time monitoring and feedback for each…
Descriptors: Emergency Medical Technicians, Intelligent Tutoring Systems, Instructional Effectiveness, Performance
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Ayedoun, Emmanuel; Hayashi, Yuki; Seta, Kazuhisa – International Journal of Artificial Intelligence in Education, 2019
This paper describes an embodied conversational agent enhanced with specific conversational strategies aiming to foster learners' readiness towards communication in a second language (L2). Willingness to communicate (WTC) in a second language is believed to have a direct and sustained influence on learners' actual usage frequency of the target…
Descriptors: Second Language Learning, Anxiety, Communication (Thought Transfer), Intelligent Tutoring Systems
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Walkington, Candace; Bernacki, Matthew L. – International Journal of Artificial Intelligence in Education, 2019
Students experience mathematics in their day-to-day lives as they pursue their individual interests in areas like sports or video games. The present study explores how connecting to students' individual interests can be used to personalize learning using an Intelligent Tutoring System (ITS) for algebra. We examine the idea that the effects of…
Descriptors: Algebra, Student Interests, Mathematics Instruction, Intelligent Tutoring Systems
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Tärning, Betty; Silvervarg, Annika; Gulz, Agneta; Haake, Magnus – International Journal of Artificial Intelligence in Education, 2019
This study examines the effects of teachable agents' expressed self-efficacy on students. A total of 166 students, 10- to 11-years-old, used a teachable agent-based math game focusing on the base-ten number system. By means of data logging and questionnaires, the study compared the effects of high vs. low agent self-efficacy on the students'…
Descriptors: Self Efficacy, Elementary School Students, Intelligent Tutoring Systems, Mathematics Instruction
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Taub, Michelle; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2019
The goal of this study was to use eye-tracking and log-file data to investigate the impact of prior knowledge on college students' (N = 194, with a subset of n = 30 for eye tracking and sequence mining analyses) fixations on (i.e., looking at) self-regulated learning-related areas of interest (i.e., specific locations on the interface) and on the…
Descriptors: Prior Learning, Eye Movements, Metacognition, Learning Processes
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Chase, Catherine C.; Connolly, Helena; Lamnina, Marianna; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2019
A successful instructional method is to engage learners with exploratory problem-solving before providing explanations of the canonical solutions and foundational concepts. A key question is whether and what type of guidance will lead learners to explore more productively and how this guidance will affect subsequent learning and transfer. We…
Descriptors: Computer Assisted Instruction, Teaching Methods, Learner Engagement, Problem Solving
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Ullmann, Thomas Daniel – International Journal of Artificial Intelligence in Education, 2019
Reflective writing is an important educational practice to train reflective thinking. Currently, researchers must manually analyze these writings, limiting practice and research because the analysis is time and resource consuming. This study evaluates whether machine learning can be used to automate this manual analysis. The study investigates…
Descriptors: Reflection, Writing (Composition), Writing Evaluation, Automation
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Doble, Christopher; Matayoshi, Jeffrey; Cosyn, Eric; Uzun, Hasan; Karami, Arash – International Journal of Artificial Intelligence in Education, 2019
A large-scale simulation study of the assessment effectiveness of a particular instantiation of knowledge space theory is described. In this study, data from more than 700,000 actual assessments in mathematics using the ALEKS (Assessment and LEarning in Knowledge Spaces) software were used to determine response probabilities for the same number of…
Descriptors: Test Reliability, Adaptive Testing, Mathematics Tests, Computer Assisted Testing
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Leo, J.; Kurdi, G.; Matentzoglu, N.; Parsia, B.; Sattler, U.; Forge, S.; Donato, G.; Dowling, W. – International Journal of Artificial Intelligence in Education, 2019
Designing good multiple choice questions (MCQs) for education and assessment is time consuming and error-prone. An abundance of structured and semi-structured data has led to the development of automatic MCQ generation methods. Recently, ontologies have emerged as powerful tools to enable the automatic generation of MCQs. However, current question…
Descriptors: Multiple Choice Tests, Test Items, Automation, Test Construction
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Wu, Wen; Chen, Li; Yang, Qingchang; Li, You – International Journal of Artificial Intelligence in Education, 2019
Communication tools have been popular in web-based learning systems because of their ability to promote the interaction and potentially alleviate the high dropout issue. In recent years, with the increased awareness among researchers about the individual difference of the students, more and more personalized learning supports have been developed.…
Descriptors: Personality, Inferences, Student Behavior, Computer Mediated Communication
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Goldberg, Benjamin; Amburn, Charles; Ragusa, Charlie; Chen, Dar-Wei – International Journal of Artificial Intelligence in Education, 2018
The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…
Descriptors: Psychomotor Skills, Intelligent Tutoring Systems, Program Validation, Models
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Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B. – International Journal of Artificial Intelligence in Education, 2018
The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…
Descriptors: Meta Analysis, Teaching Methods, Teamwork, Outcomes of Education
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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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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
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DeFalco, Jeanine A.; Rowe, Jonathan P.; Paquette, Luc; Georgoulas-Sherry, Vasiliki; Brawner, Keith; Mott, Bradford W.; Baker, Ryan S.; Lester, James C. – International Journal of Artificial Intelligence in Education, 2018
Tutoring systems that are sensitive to affect show considerable promise for enhancing student learning experiences. Creating successful affective responses requires considerable effort both to detect student affect and to design appropriate responses to affect. Recent work has suggested that affect detection is more effective when both physical…
Descriptors: Psychological Patterns, Stress Variables, Educational Games, Intelligent Tutoring Systems
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