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Geden, Michael; Emerson, Andrew; Carpenter, Dan; Rowe, Jonathan; Azevedo, Roger; Lester, James – International Journal of Artificial Intelligence in Education, 2021
Game-based learning environments are designed to provide effective and engaging learning experiences for students. Predictive student models use trace data extracted from students' in-game learning behaviors to unobtrusively generate early assessments of student knowledge and skills, equipping game-based learning environments with the capacity to…
Descriptors: Game Based Learning, Middle School Students, Microbiology, Secondary School Science
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Lodder, Josje; Heeren, Bastiaan; Jeuring, Johan; Neijenhuis, Wendy – International Journal of Artificial Intelligence in Education, 2021
This paper describes LOGAX, an interactive tutoring tool that gives hints and feedback to a student who stepwise constructs a Hilbert-style axiomatic proof in propositional logic. LOGAX generates proofs to calculate hints and feedback. We compare these generated proofs with expert proofs and student solutions, and conclude that the quality of the…
Descriptors: Intelligent Tutoring Systems, Cues, Feedback (Response), Mathematical Logic
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Deane, Paul; Wilson, Joshua; Zhang, Mo; Li, Chen; van Rijn, Peter; Guo, Hongwen; Roth, Amanda; Winchester, Eowyn; Richter, Theresa – International Journal of Artificial Intelligence in Education, 2021
Educators need actionable information about student progress during the school year. This paper explores an approach to this problem in the writing domain that combines three measurement approaches intended for use in interim-assessment fashion: scenario-based assessments (SBAs), to simulate authentic classroom tasks, automated writing evaluation…
Descriptors: Vignettes, Writing Evaluation, Writing Improvement, Progress Monitoring
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Lawson, Alyssa P.; Mayer, Richard E.; Adamo-Villani, Nicoletta; Benes, Bedrich; Lei, Xingyu; Cheng, Justin – International Journal of Artificial Intelligence in Education, 2021
There has been much research on the effectiveness of animated pedagogical agents in an educational context, however there is little research about how the emotions they display contribute to a learner's understanding of the lesson. The positivity principle suggests that learners should learn better from instructors with positive emotions compared…
Descriptors: Psychological Patterns, Animation, Recognition (Psychology), Artificial Intelligence
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Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2021
Educational technologies are often developed such that students work on specific social levels (e.g., individual, small group, whole class) at specific times. However, in the reality of the classroom, learning activities are not so cleanly divided, with transitions occurring between social levels for students at different times. To support these…
Descriptors: Individual Instruction, Small Group Instruction, Educational Technology, Elementary School Teachers
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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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Uto, Masaki; Miyazawa, Yoshimitsu; Kato, Yoshihiro; Nakajima, Koji; Kuwata, Hajime – International Journal of Artificial Intelligence in Education, 2020
Teaching writing strategies based on writing processes has attracted wide attention as a method for developing writing skills. The writing process can be generally defined as a sequence of subtasks, such as planning, formulation, and revision. Therefore, instructor feedback is often given based on sequence patterns of those subtasks. For such…
Descriptors: Markov Processes, Writing Processes, Writing Skills, Keyboarding (Data Entry)
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Behera, Ardhendu; Matthew, Peter; Keidel, Alexander; Vangorp, Peter; Fang, Hui; Canning, Susan – International Journal of Artificial Intelligence in Education, 2020
Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…
Descriptors: Nonverbal Communication, Intelligent Tutoring Systems, Eye Movements, Learning Processes
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Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement
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Cukurova, Mutlu; Luckin, Rosemary; Kent, Carmel – International Journal of Artificial Intelligence in Education, 2020
Artificial Intelligence (AI) is attracting a great deal of attention and it is important to investigate the public perceptions of AI and their impact on the perceived credibility of research evidence. In the literature, there is evidence that people overweight research evidence when framed in neuroscience findings. In this paper, we present the…
Descriptors: Artificial Intelligence, Educational Research, Attitudes, Credibility
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de Chiusole, Debora; Stefanutti, Luca; Anselmi, Pasquale; Robusto, Egidio – International Journal of Artificial Intelligence in Education, 2020
An intelligent tutoring system for learning basic statistics, called Stat-Knowlab, is presented and analyzed. The algorithms implemented in the system are based on the competence-based knowledge space theory, a mathematical theory developed for the formative assessment of knowledge and learning. The system's architecture consists of the two…
Descriptors: Statistics, Intelligent Tutoring Systems, Mathematics Instruction, Formative Evaluation
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