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Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima – Journal of Information Technology Education: Research, 2017
Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these…
Descriptors: Foreign Countries, Graduate Students, Masters Programs, Learning Disabilities
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Stamper, John; Eagle, Michael; Barnes, Tiffany; Croy, Marvin – International Journal of Artificial Intelligence in Education, 2013
We have augmented the Deep Thought logic tutor with a Hint Factory that generates data-driven, contextspecific hints for an existing computer aided instructional tool. We investigate the impact of the Hint Factory's automatically generated hints on educational outcomes in a switching replications experiment that shows that hints help students…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Problem Solving, College Students
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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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Lee, Young-Jin – Educational Technology & Society, 2015
This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…
Descriptors: Physics, Science Instruction, Computer Software, Accuracy
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Liu, Ran; Koedinger, Kenneth R. – Journal of Educational Data Mining, 2017
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
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Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – Grantee Submission, 2017
Collaborative and individual learning are both frequently used in classrooms to support learning. However, little research has investigated the benefits of combining individual and collaborative learning, as compared to learning only individually or only collaboratively. With our study, we address this research gap. We compared a combined…
Descriptors: Cooperative Learning, Grade 4, Grade 5, Elementary School Students
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Pelánek, Radek; Jarušek, Petr – International Journal of Artificial Intelligence in Education, 2015
Student modeling in intelligent tutoring systems is mostly concerned with modeling correctness of students' answers. As interactive problem solving activities become increasingly common in educational systems, it is useful to focus also on timing information associated with problem solving. We argue that the focus on timing is natural for certain…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Interaction, Problem Solving
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González-Calero, José Antonio; Arnau, David; Puig, Luis; Arevalillo-Herráez, Miguel – British Journal of Educational Technology, 2015
The term intensive scaffolding refers to any set of conceptual scaffolding strategies that always allow the user to find the solution to a problem. Despite the many benefits of scaffolding, some negative effects have also been reported. These are mainly related to the possibility that a student solves the problems without actually engaging in…
Descriptors: Scaffolding (Teaching Technique), Teaching Methods, Intelligent Tutoring Systems, Algebra
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Leite, Maici Duarte; Marczal, Diego; Pimentel, Andrey Ricardo; Direne, Alexandre Ibrahim – Journal of Technology and Science Education, 2014
This paper presents the application of some concepts of Intelligent Tutoring Systems (ITS) to elaborate a conceptual framework that uses the remediation of errors with Multiple External Representations (MERs) in Learning Objects (LO). To this is demonstrated a development of LO for teaching the Pythagorean Theorem through this framework. This…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Models, Mathematics Instruction
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Chen, Lujie; Li, Xin; Xia, Zhuyun; Song, Zhanmei; Morency, Louis-Philippe; Dubrawski, Artur – International Educational Data Mining Society, 2016
Solving challenging math problems often invites a child to ride an "emotional roller-coaster" and experience a complex mixture of emotions including confusion, frustration, joy, and surprise. Early exposure to this type of "hard fun" may stimulate child's interest and curiosity of mathematics and nurture life long skills such…
Descriptors: Young Children, Mathematics Education, Problem Solving, Psychological Patterns
Eagle, Michael; Johnson, Matthew; Barnes, Tiffany – International Educational Data Mining Society, 2012
We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…
Descriptors: Data Analysis, Interaction, Network Analysis, Problem Solving
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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Booth, Julie L.; Koedinger, Kenneth R.; Newton, Kristie J.; Lange, Karin E. – Society for Research on Educational Effectiveness, 2013
A plethora of laboratory studies have shown that including the study of worked examples during problem-solving practice improves learning (Sweller, 1999; Sweller & Cooper, 1985). While most worked-example research focuses on the use of correct examples, recent work suggests that asking children to explain a combination of correct and incorrect…
Descriptors: Individualized Instruction, Middle School Students, Grade 8, Algebra
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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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