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Samim Mirhosseini – ProQuest LLC, 2023
Computer science instructors typically have many responsibilities, such as creating material, delivering lectures, clarifying student questions, and grading student deliverables, while the demand for computer science education has been increasing. Handling all of these responsibilities is challenging in itself. However, it is made worse when…
Descriptors: Computer Science Education, Teacher Responsibility, Faculty Workload, Instructional Materials
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Kim, Yanghee; Baylor, Amy L. – International Journal of Artificial Intelligence in Education, 2016
In this paper we review the contribution of our original work titled "Simulating Instructional Roles Through Pedagogical Agents" published in the "International Journal of Artificial Intelligence and Education" (Baylor and Kim in "Computers and Human Behavior," 25(2), 450-457, 2005). Our original work operationalized…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Computer Interfaces, Instructional Design
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Aravind, Vasudeva Rao; McConnell, Marcella Kay – World Journal on Educational Technology: Current Issues, 2018
Educating our future citizens in science and engineering is vitally important to ensure future advancement. Presently, in the light of environmental sustainability, it is critical that students learn concepts relating to energy, its consumption and future demands. In this article, we harness the state of the educational technology, namely…
Descriptors: Intelligent Tutoring Systems, Science Instruction, Energy, Instructional Design
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Mich, Ornella; Pianta, Emanuele; Mana, Nadia – Computers & Education, 2013
Deaf children have significant difficulties in comprehending written text. This is mainly due to the hearing loss that prevents them from being exposed to oral language when they were an infant. However, it is also due to the type of educational intervention they are faced with, which accustoms them to decoding single words and isolated sentences,…
Descriptors: Reading Comprehension, Usability, Deafness, Story Telling
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Lin, Huan-Yu; Tseng, Shian-Shyong; Weng, Jui-Feng; Su, Jun-Ming – Educational Technology & Society, 2009
With the development of e-learning technology, many specifications of instructional design have been proposed to make learning activity sharable and reusable. With the specifications and sufficient learning resources, the researches further focus on how to provide learners more appropriate learning activities to improve their learning performance.…
Descriptors: Electronic Learning, Science Instruction, Scaffolding (Teaching Technique), Misconceptions
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Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
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Blessing, Stephen B.; Gilbert, Stephen B.; Ourada, Stephen; Ritter, Steven – International Journal of Artificial Intelligence in Education, 2009
Intelligent Tutoring Systems (ITSs) that employ a model-tracing methodology have consistently shown their effectiveness. However, what evidently makes these tutors effective, the cognitive model embedded within them, has traditionally been difficult to create, requiring great expertise and time, both of which come at a cost. Furthermore, an…
Descriptors: Intelligent Tutoring Systems, Cognitive Processes, Models, Expertise
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Curilem, S. Gloria; Barbosa, Andrea R.; de Azevedo, Fernando M. – Computers & Education, 2007
This article proposes a mathematical model of Intelligent Tutoring Systems (ITS), based on observations of the behaviour of these systems. One of the most important problems of pedagogical software is to establish a common language between the knowledge areas involved in their development, basically pedagogical, computing and domain areas. A…
Descriptors: Student Characteristics, Mathematical Models, Intelligent Tutoring Systems, Computer Software
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Mitrovic, Antonija; Martin, Brent; Suraweera, Pramuditha; Zakharov, Konstantin; Milik, Nancy; Holland, Jay; McGuigan, Nicholas – International Journal of Artificial Intelligence in Education, 2009
Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized.…
Descriptors: Foreign Countries, Investment, Intelligent Tutoring Systems, Artificial Intelligence
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Zhang, Li; Gillies, Marco; Dhaliwal, Kulwant; Gower, Amanda; Robertson, Dale; Crabtree, Barry – International Journal of Artificial Intelligence in Education, 2009
This paper describes a multi-user role-playing environment, referred to as "e-drama", which enables groups of people to converse online, in scenario driven virtual environments. The starting point of this research, is an existing application known as "edrama", a 2D graphical environment in which users are represented by static…
Descriptors: Disabilities, Cartoons, Interpersonal Relationship, Interaction
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Baghaei, Nilufar; Mitrovic, Antonija; Irwin, Warwick – International Journal of Computer-Supported Collaborative Learning, 2007
We present COLLECT-UML, a constraint-based intelligent tutoring system (ITS) that teaches object-oriented analysis and design using Unified Modelling Language (UML). UML is easily the most popular object-oriented modelling technology in current practice. While teaching how to design UML class diagrams, COLLECT-UML also provides feedback on…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Cooperation, Problem Solving
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Ferrell, Joe – Journal of Interactive Instruction Development, 1999
Discusses the design of an innovative learning system that uses new technologies for the man-machine interface, incorporating a combination of Automatic Speech Recognition (ASR) and Text To Speech (TTS) synthesis. Highlights include using speech technologies to mimic the attributes of the ideal tutor and design features. (AEF)
Descriptors: Computer Interfaces, Computer System Design, Design Preferences, Information Technology
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Aroyo, Lora; Mizoguchi, Riichiro – Journal of Interactive Learning Research, 2004
The ultimate aim of this research is to specify and implement a general authoring framework for content and knowledge engineering for Intelligent Educational Systems (IES). In this context we attempt to develop an authoring tool supporting this framework that is powerful in its functionality, generic in its support of instructional strategies and…
Descriptors: Educational Strategies, Engineering, Programming, Intelligent Tutoring Systems
Hijon-Neira, Raquel, Ed. – InTech, 2009
The education industry has obviously been influenced by the Internet revolution. Teaching and learning methods have changed significantly since the coming of the Web and it is very likely they will keep evolving many years to come thanks to it. A good example of this changing reality is the spectacular development of e-Learning. In a more…
Descriptors: Computer Assisted Instruction, Educational Technology, Internet, Feedback (Response)