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Showing 151 to 165 of 217 results Save | Export
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Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael – Grantee Submission, 2013
Authoring tools for Intelligent Tutoring System (ITS) have been shown to decrease the amount of time that it takes to develop an ITS. However, most of these tools currently do not extend to collaborative ITSs. In this paper, we illustrate an extension to the Cognitive Tutor Authoring Tools (CTAT) to allow for development of collaborative ITSs that…
Descriptors: Intelligent Tutoring Systems, Programming Languages, Fractions, Learning Processes
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Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay – International Journal of Artificial Intelligence in Education, 2016
Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students--explanations, feedback, and other pedagogical interactions. Considering the…
Descriptors: Artificial Intelligence, Educational Technology, Student Needs, Electronic Publishing
Heffernan, Neil T.; Ostrow, Korinn S.; Kelly, Kim; Selent, Douglas; Van Inwegen, Eric G.; Xiong, Xiaolu; Williams, Joseph Jay – Grantee Submission, 2016
Due to substantial scientific and practical progress, learning technologies can effectively adapt to the characteristics and needs of students. This article considers how learning technologies can adapt over time by crowdsourcing contributions from teachers and students -- explanations, feedback, and other pedagogical interactions. Considering the…
Descriptors: Artificial Intelligence, Educational Technology, Student Needs, Electronic Publishing
McNamara, Danielle S.; Jacovina, Matthew E.; Snow, Erica L.; Allen, Laura K. – Grantee Submission, 2015
Work in cognitive and educational psychology examines a variety of phenomena related to the learning and retrieval of information. Indeed, Alice Healy, our honoree, and her colleagues have conducted a large body of groundbreaking research on this topic. In this article we discuss how 3 learning principles (the generation effect, deliberate…
Descriptors: Learning Processes, Instructional Design, Intelligent Tutoring Systems, Writing Instruction
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Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – Grantee Submission, 2016
Intelligent Tutoring Systems (ITSs) are beneficial for individual students learning in several domains, including mathematics where they have been used to support both secondary and elementary students. Collaborative learning may be beneficial to include in ITSs, particularly for conceptual knowledge. There is little work on collaborative ITSs,…
Descriptors: Intelligent Tutoring Systems, Cooperative Learning, Elementary School Students, Elementary School Mathematics
Cao, Bingyi; Esponda-Argüero, Margarita; Rojas, Raúl – International Association for Development of the Information Society, 2016
In order to reduce the passivity of students and enhance their learning experience in large lectures, we developed a browser-based tool called Classroom Interacter to promote classroom interaction. It allows students to use their own mobile devices to participate in the learning process. The main features of Classroom Interacter include live…
Descriptors: Classroom Communication, Classroom Techniques, Learning Experience, Learning Processes
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Rinderknecht, Christian – Informatics in Education, 2014
We survey the literature about the teaching and learning of recursive programming. After a short history of the advent of recursion in programming languages and its adoption by programmers, we present curricular approaches to recursion, including a review of textbooks and some programming methodology, as well as the functional and imperative…
Descriptors: Teaching Methods, Learning Processes, Visualization, Animation
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Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Doroudi, Shayan; Holstein, Kenneth; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 2016
How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…
Descriptors: Sequential Learning, Data Collection, Information Retrieval, Evaluation Methods
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Roll, Ido; Baker, Ryan S. J. d.; Aleven, Vincent; Koedinger, Kenneth R. – Journal of the Learning Sciences, 2014
Seeking the right level of help at the right time can support learning. However, in the context of online problem-solving environments, it is still not entirely clear which help-seeking strategies are desired. We use fine-grained data from 38 high school students who worked with the Geometry Cognitive Tutor for 2 months to better understand the…
Descriptors: Help Seeking, Comparative Analysis, Behavior Patterns, Intelligent Tutoring Systems
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Min, Wookhee; Wiggins, Joseph B.; Pezzullo, Lydia G.; Vail, Alexandria K.; Boyer, Kristy Elizabeth; Mott, Bradford W.; Frankosky, Megan H.; Wiebe, Eric N.; Lester, James C. – International Educational Data Mining Society, 2016
Recent years have seen a growing interest in intelligent game-based learning environments featuring virtual agents. A key challenge posed by incorporating virtual agents in game-based learning environments is dynamically determining the dialogue moves they should make in order to best support students' problem solving. This paper presents a…
Descriptors: Prediction, Models, Intelligent Tutoring Systems, Computer Simulation
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Khajah, Mohammad; Lindsey, Robert V.; Mozer, Michael C. – International Educational Data Mining Society, 2016
In theoretical cognitive science, there is a tension between highly structured models whose parameters have a direct psychological interpretation and highly complex, general-purpose models whose parameters and representations are difficult to interpret. The former typically provide more insight into cognition but the latter often perform better.…
Descriptors: Bayesian Statistics, Data Analysis, Prediction, Intelligent Tutoring Systems
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Bernacki, Matthew L.; Nokes-Malach, Timothy J.; Aleven, Vincent – Metacognition and Learning, 2015
Self-regulated learning (SRL) theorists propose that learners' motivations and cognitive and metacognitive processes interact dynamically during learning, yet researchers typically measure motivational constructs as stable factors. In this study, self-efficacy was assessed frequently to observe its variability during learning and how learners'…
Descriptors: Self Efficacy, Metacognition, Cues, Algebra
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Di Bitonto, Pierpaolo; Roselli, Teresa; Rossano, Veronica; Sinatra, Maria – International Journal of Distance Education Technologies, 2013
One of the most closely investigated topics in e-learning research has always been the effectiveness of adaptive learning environments. The technological evolutions that have dramatically changed the educational world in the last six decades have allowed ever more advanced and smarter solutions to be proposed. The focus of this paper is to depict…
Descriptors: Educational Technology, Technology Uses in Education, Computer Assisted Instruction, Artificial Intelligence
Rau, Martina A. – ProQuest LLC, 2013
Most learning environments in the STEM disciplines use multiple graphical representations along with textual descriptions and symbolic representations. Multiple graphical representations are powerful learning tools because they can emphasize complementary aspects of complex learning contents. However, to benefit from multiple graphical…
Descriptors: Intelligent Tutoring Systems, Visual Aids, Intermediate Grades, Elementary School Students
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