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Kurdi, Ghader; Leo, Jared; Parsia, Bijan; Sattler, Uli; Al-Emari, Salam – International Journal of Artificial Intelligence in Education, 2020
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing)…
Descriptors: Computer Assisted Testing, Adaptive Testing, Natural Language Processing, Questioning Techniques
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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
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Taub, Michelle; Sawyer, Robert; Lester, James; Azevedo, Roger – International Journal of Artificial Intelligence in Education, 2020
The goal of this study was to examine college students' (n = 61) contextualized emotions during in-game actions while playing "Crystal Island," a game-based learning environment where students are tasked with solving the mystery of what illness impacted all island inhabitants. We examined emotions during in-game actions: during book…
Descriptors: Psychological Patterns, Independent Study, Logical Thinking, Game Based Learning
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Gulz, Agneta; Londos, Ludvig; Haake, Magnus – International Journal of Artificial Intelligence in Education, 2020
This study investigated how preschool children processed and understood critical information in Magical Garden, a teachable agent-based play-&-learn game targeting early math. We analyzed 36 children's (ages 4-6 years) real-time behavior during game-use to explore whether children: (i) processed the information meant to support number sense…
Descriptors: Preschool Children, Educational Games, Mathematics Instruction, Preschool Education
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Yannier, Nesra; Hudson, Scott E.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2020
Along with substantial consensus around the power of active learning, comes some lack of precision in what its essential ingredients are. New educational technologies offer vehicles for systematically exploring benefits of alternative techniques for supporting active learning. We introduce a new genre of Intelligent Science Station technology that…
Descriptors: Active Learning, Artificial Intelligence, STEM Education, Educational Technology
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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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Alexandron, Giora; Yoo, Lisa Y.; Ruipérez-Valiente, José A.; Lee, Sunbok; Pritchard, David E. – International Journal of Artificial Intelligence in Education, 2019
The rich data that Massive Open Online Courses (MOOCs) platforms collect on the behavior of millions of users provide a unique opportunity to study human learning and to develop data-driven methods that can address the needs of individual learners. This type of research falls into the emerging field of "learning analytics." However,…
Descriptors: Online Courses, Data Collection, Learning Analytics, Reliability
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Stahovich, Thomas F.; Lin, Hanlung; Gyllen, Justin – International Journal of Artificial Intelligence in Education, 2019
We present a technique that examines handwritten equations from a student's solution to an engineering problem and from this estimates the correctness of the work. More specifically, we demonstrate that lexical properties of the equations correlate with the grade a human grader would assign. We characterize these properties with a set of features…
Descriptors: Handwriting, Engineering Education, Problem Solving, Equations (Mathematics)
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Fabic, Geela Venise Firmalo; Mitrovic, Antonija; Neshatian, Kourosh – International Journal of Artificial Intelligence in Education, 2019
The overarching goal of our project is to design effective learning activities for PyKinetic, a smartphone Python tutor. In this paper, we present a study using a variant of Parsons problems we designed for PyKinetic. Parsons problems contain randomized code which needs to be re-ordered to produce the desired effect. In our variant of Parsons…
Descriptors: Telecommunications, Handheld Devices, Cues, Intelligent Tutoring Systems
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González-Eras, Alexandra; Aguilar, Jose – International Journal of Artificial Intelligence in Education, 2019
Describing the competencies required by a profession is essential for aligning online profiles of job seekers and job advertisements. Comparing the competencies described within each context has typically not be done, which has generated a complete disconnect in language between them. This work presents an approach for the alignment of online…
Descriptors: Job Skills, Competence, Occupational Information, Profiles
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Doroudi, Shayan; Aleven, Vincent; Brunskill, Emma – International Journal of Artificial Intelligence in Education, 2019
Since the 1960s, researchers have been trying to optimize the sequencing of instructional activities using the tools of reinforcement learning (RL) and sequential decision making under uncertainty. Many researchers have realized that reinforcement learning provides a natural framework for optimal instructional sequencing given a particular model…
Descriptors: Reinforcement, Learning Processes, Sequential Learning, Decision Making
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