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Cheng, Li; Umapathy, Karthikeyan; Rehman, Muhammad; Ritzhaupt, Albert; Antonyan, Kristine; Shidfar, Poorya; Nichols, James; Lee, Minyoung; Abramowitz, Brian – Journal of Interactive Learning Research, 2023
The purpose of this research study is to design, develop, and validate an instrument for measuring undergraduate students' conceptions of artificial intelligence in education. Following systematic procedures, our team created a conceptual framework through an extant literature review and used it to create an initial item pool of 48-items across…
Descriptors: Undergraduate Students, Knowledge Level, Artificial Intelligence, Technology Uses in Education
Mojarad, Shirin; Baker, Ryan S.; Essa, Alfred; Stalzer, Steve – Journal of Interactive Learning Research, 2021
Despite the importance of replication, it remains rare in the interactive learning research community. In this paper, we attempt to replicate recent quasi-experimental results suggesting that the ALEKS intelligent tutoring system is effective at improving student course outcomes in higher education (Mojarad et al., 2018). In this paper, we conduct…
Descriptors: Intelligent Tutoring Systems, Replication (Evaluation), Probability, Quasiexperimental Design
Jackson, Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle – Journal of Interactive Learning Research, 2015
Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART (Interactive Strategy Training for Active Reading and Thinking), a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Reading Strategies, Tutoring
Maloy, Robert W.; Razzaq, Leena; Edwards, Sharon A. – Journal of Interactive Learning Research, 2014
This study explored the use of an online mathematics tutoring system in eight fourth grade classrooms in two Massachusetts communities--a small rural city with a low 2010 Adequate Yearly Progress (AYP) math performance rating and a small suburban district with a high 2010 AYP math performance rating. 165 fourth graders completed 11 modules…
Descriptors: Intelligent Tutoring Systems, Multimedia Instruction, Mathematics Instruction, Elementary School Mathematics
Broderick, Zachary; O'Connor, Christine; Mulcahy, Courtney; Heffernan, Neil; Heffernan, Christina – Journal of Interactive Learning Research, 2011
This study demonstrates the ability of an Intelligent Tutoring System (ITS) to increase parental engagement in student learning. A parent notification feature was developed for the web-based ASSISTment ITS that allows parents to log into their own accounts and access detailed data about their students' performance. Parents from a local middle…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Program Effectiveness, Internet
Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan – Journal of Interactive Learning Research, 2011
The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…
Descriptors: Electronic Learning, Educational Strategies, Learning Theories, Instructional Design
Sykes, Edward – Journal of Interactive Learning Research, 2007
The Java Intelligent Tutoring System (JITS) was designed and developed to support the growing trend of Java programming around the world. JITS is an advanced web-based personalized tutoring system that is unique in several ways. Most programming Intelligent Tutoring Systems require the teacher to author problems with corresponding solutions. JITS,…
Descriptors: Programming, Tutoring, Intelligent Tutoring Systems, Interviews
Sessink, Olivier D. T.; Beeftink, Hendrik H.; Tramper, Johannes; Hartog, Rob J. M. – Journal of Interactive Learning Research, 2007
Effectively targeting a heterogeneous student population is a common challenge in academic courses. Most traditional learning material targets the "average student," and is suboptimal for students who lack certain prior knowledge, or students who have already attained some of the course objectives. Student-activating learning material supports…
Descriptors: Prior Learning, Course Objectives, Intelligent Tutoring Systems, Tutorial Programs

Wesley, Leonard P.; Shim, Simon S. Y.; Booth, Robert P.; Atreya, Shreemathi D. – Journal of Interactive Learning Research, 1999
Discusses intelligent agent development environments and distance learning environments, and describes ROADS (Real-time Object-oriented Agent Development System) that has been developed and used to manage the acquisition and presentation of multimedia information in distance learning. Explains a theory of objects and gives a distance learning…
Descriptors: Distance Education, Educational Environment, Intelligent Tutoring Systems, Multimedia Instruction

Stoyanov, Svetoslav; Kommers, Piet – Journal of Interactive Learning Research, 1999
Presents an experimental verification of a hypothetical construct explaining the basic mechanism behind the behavior of an intelligent agent implemented in the Solution, Mapping, Intelligent, Learning Environment (SMILE) performance supported system. Explains the SMILE concept mapping method and its role as a problem-solving tool. (Author/LRW)
Descriptors: Concept Mapping, Information Systems, Intelligent Tutoring Systems, Problem Solving

Solomos, Konstantinos; Avouris, Nikolaos – Journal of Interactive Learning Research, 1999
Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)
Descriptors: Artificial Intelligence, Educational Environment, Intelligent Tutoring Systems, Interaction

Dang, Trang; Ghenniwa, Hamada; Kamel, Mohamed – Journal of Interactive Learning Research, 1999
Proposes an interface agent for intelligent tutoring systems that creates a collaborative learning environment between the learner and the tutoring software. Describes implementation of a prototype using the IBM Agent Builder Environment Toolkit to use with an intelligent tutoring system for algebra and considers benefits in a lifelong learning…
Descriptors: Algebra, Computer Interfaces, Educational Environment, Intelligent Tutoring Systems
Ishizaka, Alessio; Lusti, Markus – Journal of Interactive Learning Research, 2006
Explanations are essential in the teaching process. Tracers are one possibility to provide students with explanations in an intelligent tutoring system. Their development can be divided into four steps: (a) the definition of the trace model; (b) the extraction of the information from this model; (c) the analysis and abstraction of the extracted…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Computer Uses in Education, Educational Technology

Nkambou, R.; Frasson, C.; Gauthier, G.; Rouane, K. – Journal of Interactive Learning Research, 2001
Presents an authoring model and a system for curriculum development in intelligent tutoring systems. Explains CREAM (Curriculum Representation and Acquisition Model) which allows for the creation and organization of the curriculum according to three models concerning the domain, the pedagogy, and the didactic aspects. (Author/LRW)
Descriptors: Authoring Aids (Programming), Curriculum Development, Instructional Design, Intelligent Tutoring Systems
Karampiperis, Pythagoras; Sampson, Demetrios – Journal of Interactive Learning Research, 2004
Adaptive learning object selection and sequencing is recognized as among the most interesting research questions in intelligent web-based education. In most intelligent learning systems that incorporate course sequencing techniques, learning object selection is based on a set of teaching rules according to the cognitive style or learning…
Descriptors: Cognitive Style, Instructional Design, Educational Technology, Intelligent Tutoring Systems
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