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Stone, Melissa L.; Kent, Kevin M.; Roscoe, Rod D.; Corley, Kathleen M.; Allen, Laura K.; McNamara, Danielle S. – Grantee Submission, 2017
This chapter explores three broad principles of user-centered design methodologies: participatory design, iteration, and usability considerations. The authors highlight the importance of considering teachers as a prominent type of ITS end user, by describing the barriers teachers face as users and their role in educational technology design. To…
Descriptors: Intelligent Tutoring Systems, Design, Usability, Barriers
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Graesser, Arthur C.; Forsyth, Carol M.; Lehman, Blair A. – Grantee Submission, 2017
Background: Pedagogical agents are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with the students in natural language. Dialogues occur between a tutor agent and the student in the case of AutoTutor and other intelligent tutoring systems with natural language…
Descriptors: Intelligent Tutoring Systems, Computer Managed Instruction, Natural Language Processing, Instructional Design
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Hutt, Stephen; Hardey, Jessica; Bixler, Robert; Stewart, Angela; Risko, Evan; D'Mello, Sidney K. – International Educational Data Mining Society, 2017
We investigate the use of consumer-grade eye tracking to automatically detect Mind Wandering (MW) during learning from a recorded lecture, a key component of many Massive Open Online Courses (MOOCs). We considered two feature sets: stimulus-independent global gaze features (e.g., number of fixations, fixation duration), and stimulus-dependent…
Descriptors: Eye Movements, Attention, Lecture Method, Student Behavior
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Shen, Shitian; Chi, Min – International Educational Data Mining Society, 2017
One of the most challenging tasks in the field of Educational Data Mining (EDM) is to cluster students directly based on system-student sequential moment-to-moment interactive trajectories. The objective of this study is to build a general temporal clustering framework that captures the distinct characteristics of students' sequential behaviors…
Descriptors: Sequential Approach, Cluster Grouping, Interaction, Student Behavior
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Albacete, Patricia; Silliman, Scott; Jordan, Pamela – Grantee Submission, 2017
Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Multiple Choice Tests, Computer Assisted Testing
Zikai Wen – ProQuest LLC, 2021
Drill and practice is a well-received approach to repeatedly train learners' skills through a series of exercises and to reward them with corrective feedback. However, drill-based training may not improve learners' performance if its exercises are badly designed (e.g., not fun, not relevant to the learning goal, and becoming too difficult or too…
Descriptors: Educational Games, Game Based Learning, Computer Games, Artificial Intelligence
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Amanda J. Neitzel; Qiyang Zhang; Robert E. Slavin – Society for Research on Educational Effectiveness, 2021
Background: Over the years, the quantity and quality of educational research has been rapidly improving. This can be attributed to the growing call to use evidence of effectiveness in decision-making by policymakers and practitioners. In fact, evidence sufficient to establish programs as "small", "moderate", or…
Descriptors: Meta Analysis, Evidence Based Practice, Elementary Secondary Education, Educational Legislation
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Nygren, Eeva; Blignaut, A. Seugnet; Leendertz, Verona; Sutinen, Erkki – Informatics in Education, 2019
Technology-enhanced learning generally focuses on the cognitive rather than the affective domain of learning. This multi-method evaluation of the INBECOM project (Integrating Behaviourism and Constructivism in Mathematics) was conducted from the point of view of affective learning levels of Krathwohl "et al." (1964). The research…
Descriptors: Game Based Learning, Electronic Learning, Mathematics Instruction, Intelligent Tutoring Systems
Li, Haiying; Graesser, Art C. – Grantee Submission, 2020
This study investigated the impact of conversational agent formality on the quality of summaries and formality of written summaries during the training session and on posttest in a trialog-based intelligent tutoring system (ITS). During training, participants learned summarization strategies with the guidance of conversational agents who spoke one…
Descriptors: Intelligent Tutoring Systems, Writing Instruction, Writing Skills, Language Styles
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Alvarez, Nahum; Sanchez-Ruiz, Antonio; Cavazza, Marc; Shigematsu, Mika; Prendinger, Helmut – International Journal of Artificial Intelligence in Education, 2015
The use of three-dimensional virtual environments in training applications supports the simulation of complex scenarios and realistic object behaviour. While these environments have the potential to provide an advanced training experience to students, it is difficult to design and manage a training session in real time due to the number of…
Descriptors: Intelligent Tutoring Systems, Safety Education, Virtual Classrooms, Biology
Nižnan, Juraj; Pelánek, Radek; Rihák, Jirí – International Educational Data Mining Society, 2015
Intelligent behavior of adaptive educational systems is based on student models. Most research in student modeling focuses on student learning (acquisition of skills). We focus on prior knowledge, which gets much less attention in modeling and yet can be highly varied and have important consequences for the use of educational systems. We describe…
Descriptors: Prior Learning, Models, Intelligent Tutoring Systems, Bayesian Statistics
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Ramírez, Jaime; Rico, Mariano; Riofrío-Luzcando, Diego; Berrocal-Lobo, Marta; de Antonio, Angélica – Journal of Educational Computing Research, 2018
This article presents an investigation on the educational value of virtual worlds intended for the acquisition of procedural knowledge. This investigation takes as a case of study a virtual laboratory on biotechnology. A remarkable feature in this virtual laboratory is an automatic tutor that supervises student's actions and provides tutoring…
Descriptors: Foreign Countries, Case Studies, Biotechnology, Computer Uses in Education
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Roll, Ido; Russell, Daniel M.; Gaševic, Dragan – International Journal of Artificial Intelligence in Education, 2018
Learning at Scale is a fast growing field that affects formal, informal, and workplace education. Highly interdisciplinary, it builds on solid foundations in the learning sciences, computer science, education, and the social sciences. We define learning at scale as the study of the technologies, pedagogies, analyses, and theories of learning and…
Descriptors: Interdisciplinary Approach, Computer Science Education, Social Sciences, Learning
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Serrano, M.-Á.; Vidal-Abarca, E.; Ferrer, A. – Journal of Computer Assisted Learning, 2018
The use of documents to perform tasks is a continuous task demand in the current knowledge-based society that involves making a series of decisions to self-regulate the use of text information. Low-skilled comprehenders have serious problems monitoring and self-regulating their decisions in these task-oriented reading situations, which has a…
Descriptors: Metacognition, Teaching Methods, Learning Strategies, Intelligent Tutoring Systems
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Sullins, Jeremiah; Acuff, Samuel; Neely, Daniel; Hu, Xiangen – Journal of Educational Multimedia and Hypermedia, 2018
Is it possible to teach a learner to become a better question asker in as little as 25 minutes? Given that many teachers and school districts do not have the resources to provide individualized question training to students, the current study sought to explore the benefits of using animated pedagogical agents to teach question-asking skills in a…
Descriptors: Prior Learning, Questioning Techniques, Training, Intelligent Tutoring Systems
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