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Showing 1 to 15 of 17 results Save | Export
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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
Ritchey, ChristiAnne – ProQuest LLC, 2018
The mathematics test is the most difficult test in the GED (General Education Development) Test battery, largely due to the presence of story problems. Raising performance levels of story problem-solving would have a significant effect on GED Test passage rates. The subject of this formative research study is Ms. Stephens' Categorization Practice…
Descriptors: Mathematics Tests, General Education, Formative Evaluation, Word Problems (Mathematics)
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Acharya, Anal; Sinha, Devadatta – Journal of Educational Computing Research, 2017
The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence.…
Descriptors: Intelligent Tutoring Systems, Web Based Instruction, Concept Mapping, Learning Problems
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Mao, Ye; Lin, Chen; Chi, Min – Journal of Educational Data Mining, 2018
Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…
Descriptors: Prediction, Pretests Posttests, Bayesian Statistics, Short Term Memory
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Fang, Ying; Nye, Benjamin; Pavlik, Philip; Xu, Yonghong Jade; Graesser, Arthur; Hu, Xiangen – International Educational Data Mining Society, 2017
Student persistence in online learning environments has typically been studied at the macro-level (e.g., completion of an online course, number of academic terms completed, etc.). The current examines student persistence in an adaptive learning environment, ALEKS (Assessment and LEarning in Knowledge Spaces). Specifically, the study explores the…
Descriptors: Learning Processes, Academic Persistence, Correlation, Academic Achievement
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Lallé, Sébastien; Conati, Cristina; Azevedo, Roger; Mudrick, Nicholas; Taub, Michelle – International Educational Data Mining Society, 2017
In this paper, we investigate the relationship between students' learning gains and their compliance with prompts fostering self-regulated learning (SRL) during interaction with MetaTutor, a hypermedia-based intelligent tutoring systems (ITS). When possible, we evaluate compliance from student explicit answers on whether they want to follow the…
Descriptors: Compliance (Psychology), Metacognition, Computer Software, Eye Movements
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McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M. – Journal of Visual Impairment & Blindness, 2016
Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…
Descriptors: Intelligent Tutoring Systems, Supplementary Education, Assistive Technology, Braille
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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
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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
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Wu, Ji-Wei; Tseng, Judy C. R.; Hwang, Gwo-Jen – Educational Technology & Society, 2015
Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to…
Descriptors: Foreign Countries, Inquiry, Active Learning, Intelligent Tutoring Systems
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Gomez, Jorge E.; Huete, Juan F.; Hernandez, Velssy L. – IEEE Transactions on Learning Technologies, 2016
The dynamics of the world today demands a change in traditional education paradigms to enable the creation of more efficient learning environments, where students will learn more effectively and will play a more active role in their education. They should interact with the knowledge at anytime-anywhere. In order to tackle this problem we should…
Descriptors: Active Learning, Telecommunications, Handheld Devices, Intelligent Tutoring Systems
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Baker, Ryan S.; Hershkovitz, Arnon; Rossi, Lisa M.; Goldstein, Adam B.; Gowda, Sujith M. – Journal of the Learning Sciences, 2013
We present a new method for analyzing a student's learning over time for a specific skill: analysis of the graph of the student's moment-by-moment learning over time. Moment-by-moment learning is calculated using a data-mined model that assesses the probability that a student learned a skill or concept at a specific time during learning (Baker,…
Descriptors: Learning Processes, Intelligent Tutoring Systems, Probability, Skill Development
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Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam – Educational Technology Research and Development, 2013
Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…
Descriptors: Artificial Intelligence, Computer Simulation, Computer Mediated Communication, Intelligent Tutoring Systems
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Wang, Ya-huei; Liao, Hung-Chang – British Journal of Educational Technology, 2011
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students' learning outcomes are to be maximised, it is…
Descriptors: Cognitive Style, Learning Motivation, Learning Processes, Individualized Instruction
Rau, M. A.; Aleven, V.; Rummel, N. – Society for Research on Educational Effectiveness, 2011
Graphical representations (GRs) of the learning content are often used for instruction (Ainsworth, 2006). When used in learning technology, GRs can be especially useful since they allow for interactions across representations that are physically impossible, for instance by dragging and dropping symbolic statements into a chart that automatically…
Descriptors: Intelligent Tutoring Systems, Retention (Psychology), Mathematics, Mathematics Instruction
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