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Katz, Sandra; Albacete, Patricia; Jordan, Pamela – Grantee Submission, 2014
Although research on human tutoring highlights the importance of a high degree of "interactivity" between the tutor and student, some instructional strategies that could be carried out interactively are implemented didactically in tutoring systems. This is especially true of summarization, a ubiquitous instructional strategy. We…
Descriptors: Tutoring, Documentation, Intelligent Tutoring Systems, Standards
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Johnson, W. Lewis; Lester, James C. – International Journal of Artificial Intelligence in Education, 2016
Johnson et al. ("International Journal of Artificial Intelligence in Education," 11, 47-78, 2000) introduced and surveyed a new paradigm for interactive learning environments: animated pedagogical agents. The article argued for combining animated interface agent technologies with intelligent learning environments, yielding intelligent…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Outcomes of Education, Computer Assisted Instruction
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an de Sande, Brett – International Educational Data Mining Society, 2016
Learning curves have proven to be a useful tool for understanding how a student learns a given skill as they progress through a curriculum. A learning curve for a given Knowledge Component (KC) is a plot of some measure of competence as a function of the number of opportunities the student has had to apply that KC. Consider the case where each…
Descriptors: Learning Processes, Knowledge Level, Problem Solving, Homework
Noguchi, Yasuhiro; Kogure, Satoru; Konishi, Tatsuhiro; Itoh, Yukihiro – Research and Practice in Technology Enhanced Learning, 2015
Exercises with well-designed similar problem sets are effective in classrooms. In this case, teachers design similar problem sets related to the educational effects they have targeted. However, to design these "related problem sets (RPSs)" is not so easy for teachers, especially for students who are studying the problems. To support…
Descriptors: Problem Sets, Problem Solving, Instructional Design, Intelligent Tutoring Systems
Mostafavi, Behrooz; Liu, Zhongxiu; Barnes, Tiffany – International Educational Data Mining Society, 2015
Deep Thought is a logic tutor where students practice constructing deductive logic proofs. Within Deep Thought is a data-driven mastery learning system (DDML), which calculates student proficiency based on rule scores weighted by expert-decided weights in order to assign problem sets of appropriate difficulty. In this study, we designed and tested…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Mathematical Logic, Mastery Learning
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Walkington, Candace; Bernacki, Matthew L. – Journal of Experimental Education, 2018
Instruction can be made relevant to students when it draws upon and utilizes their interests, experiences, and "funds of knowledge" in productive ways to support classroom learning. This approach has been referred to as "context personalization." In this paper, we discuss the cognitive basis of personalization interventions,…
Descriptors: Individualized Instruction, Instructional Design, Relevance (Education), Cognitive Processes
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Ganzfried, Sam; Yusuf, Farzana – Education Sciences, 2018
A problem faced by many instructors is that of designing exams that accurately assess the abilities of the students. Typically, these exams are prepared several days in advance, and generic question scores are used based on rough approximation of the question difficulty and length. For example, for a recent class taught by the author, there were…
Descriptors: Weighted Scores, Test Construction, Student Evaluation, Multiple Choice Tests
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Wolfe, Christopher R.; Widmer, Colin L.; Torrese, Christine V.; Dandignac, Mitchell – Journal of Learning Analytics, 2018
We developed a method for using Coh-Metrix to automatically analyze tutorial dialogues. Coh-Metrix, a web-based tool for automatically evaluating text, is freely available to researchers. We applied the method to 190 tutorial dialogues between women and "BRCA Gist" from two experiments. "BRCA Gist" is an intelligent tutoring…
Descriptors: Data Analysis, Risk, Cancer, Females
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Bontogon, Megan; Arppe, Antti; Antonsen, Lene; Thunder, Dorothy; Lachler, Jordan – Canadian Modern Language Review, 2018
Intelligent computer assisted language learning (ICALL) applications for Indigenous languages are a relatively new avenue for computer assisted language learning (CALL). CALL allows language learners to practise a wide range of grammatical exercises and receive feedback on their answers outside of class time. ICALL is essential for dynamically…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Technology Uses in Education, Computer Assisted Instruction
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Aguilar, Jose; Cordero, Jorge; Buendía, Omar – Journal of Educational Computing Research, 2018
In this article, we propose the concept of "Autonomic Cycle Of Learning Analysis Tasks" (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic…
Descriptors: Data Analysis, Learning Processes, Decision Making, Instructional Improvement
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Bernacki, Matthew L.; Walkington, Candace – Journal of Educational Psychology, 2018
Context personalization--the incorporation of students' out-of-school interests into learning tasks--has recently been shown to positively affect students' situational interest and their performance and learning in mathematics. However, few studies have shown effects on both interest and achievement, drawing into question whether context…
Descriptors: High School Students, Student Interests, Individualized Instruction, Mathematics Instruction
Stefan Ruseti; Mihai Dascalu; Amy M. Johnson; Renu Balyan; Kristopher J. Kopp; Danielle S. McNamara – Grantee Submission, 2018
This study assesses the extent to which machine learning techniques can be used to predict question quality. An algorithm based on textual complexity indices was previously developed to assess question quality to provide feedback on questions generated by students within iSTART (an intelligent tutoring system that teaches reading strategies). In…
Descriptors: Questioning Techniques, Artificial Intelligence, Networks, Classification
Sahba Akhavan Niaki – ProQuest LLC, 2018
The increasing amount of available subjective text data in internet such as product reviews, movie critiques and social media comments provides golden opportunities for information retrieval researchers to extract useful information out of such datasets. Topic modeling and sentiment analysis are two widely researched fields that separately try to…
Descriptors: Models, Classification, Content Analysis, Documentation
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Dong, Jian-Jie; Hwang, Wu-Yuin; Shadiev, Rustam; Chen, Ginn-Yein – IEEE Transactions on Learning Technologies, 2019
In this study, we developed an on-call-tutor system to facilitate peer-help activities. The system was implemented in a face-to-face heterogeneous classroom with 119 students from different departments who were not familiar with each other. Students learned Geographic Information System (GIS) in a computer classroom in two groups: students, who…
Descriptors: Peer Teaching, Synchronous Communication, Social Networks, Friendship
Glaze, Andrew R. – ProQuest LLC, 2019
The purpose of this mixed-methods study was to investigate the relationship between teachers' conceptions of mathematics and their use of intelligent tutoring systems for mathematics instruction. Intelligent tutoring systems are adaptive computer programs which administer mathematics instruction to students based on their cognitive state. A…
Descriptors: Mathematics Instruction, Teaching Methods, Intelligent Tutoring Systems, Web Sites
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