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Pandey, Shalini; Karypis, George – International Educational Data Mining Society, 2019
Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities. Each student's knowledge is modeled by estimating the performance of the student on the learning activities. It is an important research area for providing a personalized learning platform to…
Descriptors: Learning Processes, Databases, Intelligent Tutoring Systems, Knowledge Level
Shi, Genghu; Wang, Lijia; Zhang, Liang; Shubeck, Keith; Peng, Shun; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2021
Adult learners with low literacy skills compose a highly heterogeneous population in terms of demographic variables, educational backgrounds, knowledge and skills in reading, self-efficacy, motivation etc. They also face various difficulties in consistently attending offline literacy programs, such as unstable worktime, transportation…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Adult Students, Reading Comprehension
Banjade, Rajendra; Rus, Vasile – International Educational Data Mining Society, 2019
Automatic answer assessment systems typically apply semantic similarity methods where student responses are compared with some reference answers in order to access their correctness. But student responses in dialogue based tutoring systems are often grammatically and semantically incomplete and additional information (e.g., dialogue history) is…
Descriptors: Dialogs (Language), Probability, Intelligent Tutoring Systems, Semantics
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
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
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
Bratt, Elizabeth Owen – International Journal of Artificial Intelligence in Education, 2009
This paper describes the role of simulation-based training in the military. Interviews and observations of military instructors in the damage control and shiphandling domains provide examples of how the instructors extend the student's training beyond the well-defined simulated world with qualitative reasoning about context, hypothetical variants,…
Descriptors: Intelligent Tutoring Systems, Military Training, Simulation, Tutoring
Fulgham, Susan M.; Shaughnessy, Michael F. – Educational Technology, 2013
Stavros Demetriadis is currently an Assistant Professor with the Department of Informatics, Aristotle University of Thessaloniki (AUTh) in Greece. He also earned his Bachelor's degree in Physics and a Master Diploma in Electronic Physics from AUTh. He became interested in information and communications technologies when he was a high school…
Descriptors: Foreign Countries, Profiles, Educational Technology, Technology Integration
Wauters, K.; Desmet, P.; Van den Noortgate, W. – Journal of Computer Assisted Learning, 2010
The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching…
Descriptors: Knowledge Level, Adaptive Testing, Test Items, Item Response Theory
Wohlhuter, Kay A.; Breyfogle, M. Lynn; McDuffie, Amy Roth – Teaching Children Mathematics, 2010
Developing deep knowledge and understanding of mathematics is a lifelong process, and building the foundation for teachers' development must begin in preservice preparation and continue throughout one's professional life. While teaching mathematics content courses and methods courses, the authors have found that preservice elementary school…
Descriptors: Preservice Teachers, Methods Courses, Mathematics Education, Elementary School Teachers
Mowlds, Frances; Roche, Bernard-Joseph; Mangina, Eleni – Campus-Wide Information Systems, 2005
Purpose: One of the greatest challenges facing any intelligent tutoring system is being able to adapt its behaviour based on the student's current knowledge level, ability, needs and wishes within a course. This paper aims to present a framework of BDI agents within an agent-based intelligent tutoring system (ABITS). Design/methodology/approach: A…
Descriptors: Knowledge Level, Intelligent Tutoring Systems, Tutoring, Cognitive Structures
Tzouveli, Paraskevi; Mylonas, Phivos; Kollias, Stefanos – Computers & Education, 2008
Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…
Descriptors: Educational Needs, Distance Education, Knowledge Level, Questionnaires
Mogharreban, Namdar – Journal of Information Technology Education, 2004
A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…
Descriptors: Knowledge Level, Student Characteristics, Intelligent Tutoring Systems, Systems Development
Perspectives in Peer Programs, 2007
In January 2006, PAL[R] Peer Assistance and Leadership, a Promising Prevention Program of Workers Assistance Program, Inc. (WAP), received a $30,000 grant from the Center for Substance Abuse Prevention (CSAP) in order to be scientifically-evaluated on the outcomes and effectiveness of its programs and services. According to the grant, the…
Descriptors: Campuses, Substance Abuse, Student Attitudes, Prevention
The Structure and Culture of Developing a Mathematics Tutoring Collaborative in an Urban High School
Walker, Erica N. – High School Journal, 2007
This conceptual article describes a model of a school-based, student-led initiative that uses peer tutoring to address underachievement in mathematics. The model is three pronged: a) it suggests a site-based approach to building on existing student excellence in mathematics to drive improved student mathematics achievement; b) it seeks to address…
Descriptors: Teacher Qualifications, Urban Schools, Peer Relationship, High School Students
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