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King, Emily C.; Benson, Max; Raysor, Sandra; Holme, Thomas A.; Sewall, Jonathan; Koedinger, Kenneth R.; Aleven, Vincent; Yaron, David J. – Journal of Chemical Education, 2022
This report showcases a new type of online homework system that provides students with a free-form interface and dynamic feedback. The ORCCA Tutor (Open-Response Chemistry Cognitive Assistance Tutor) is a production rules-based online tutoring system utilizing the Cognitive Tutoring Authoring Tools (CTAT) developed by Carnegie Mellon University.…
Descriptors: Intelligent Tutoring Systems, Chemistry, Homework, Feedback (Response)
Arnau, David; Arevalillo-Herraez, Miguel; Puig, Luis; Gonzalez-Calero, Jose Antonio – Computers & Education, 2013
Designers of interactive learning environments with a focus on word problem solving usually have to compromise between the amount of resolution paths that a user is allowed to follow and the quality of the feedback provided. We have built an intelligent tutoring system (ITS) that is able to both track the user's actions and provide adequate…
Descriptors: Intelligent Tutoring Systems, Computer System Design, Word Problems (Mathematics), Problem Solving
Scheuer, O.; McLaren, B. M. – IEEE Transactions on Learning Technologies, 2013
One of the main challenges in tapping the full potential of modern educational software is to devise mechanisms to automatically analyze and adaptively support students' problem solving and learning. A number of such approaches have been developed to teach argumentation skills in domains as diverse as science, the Law, and ethics. Yet,…
Descriptors: Intelligent Tutoring Systems, Persuasive Discourse, Cooperative Learning, Legal Education (Professions)
Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels – Computers & Education, 2013
Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem. But does greater freedom mean that students…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Algebra, Mathematics Instruction
Cifuentes, Laurent; Mercer, Rene; Alverez, Omar; Bettati, Riccardo – TechTrends: Linking Research and Practice to Improve Learning, 2010
We report on the design, development, implementation, and evaluation of a case-based instructional environment designed for learning network engineering skills for cybersecurity. We describe the societal problem addressed, the theory-based solution, and the preliminary testing and evaluation of that solution. We identify an architecture for…
Descriptors: Case Method (Teaching Technique), Problem Solving, Scaffolding (Teaching Technique), Instructional Design
Lynch, Collin; Ashley, Kevin D.; Pinkwart, Niels; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2009
In this paper we consider prior definitions of the terms "ill-defined domain" and "ill-defined problem". We then present alternate definitions that better support research at the intersection of Artificial Intelligence and Education. In our view both problems and domains are ill-defined when essential concepts, relations, or criteria are un- or…
Descriptors: Definitions, Artificial Intelligence, Problem Solving, Educational Research
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
Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2009
In well-defined domains such as Physics, Mathematics, and Chemistry, solutions to a posed problem can objectively be classified as correct or incorrect. In ill-defined domains such as medicine, the classification of solutions to a patient problem as correct or incorrect is much more complex. Typical tutoring systems accept only a small set of…
Descriptors: Foreign Countries, Problem Based Learning, Problem Solving, Correlation
Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey – International Working Group on Educational Data Mining, 2009
This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…
Descriptors: Programming, Evidence, Intelligent Tutoring Systems, Regression (Statistics)
Takaoka, Ryo; Okamoto, Toshio – 1994
As a person learns, his problem solving ability improves and one reason for this is the increased acquisition of "macro-rules" which make problem solving more efficient. An intelligent computer assisted learning (ICAI) system is being developed which automatically acquires the useful knowledge from the domain experts; as experts give the learning…
Descriptors: Cognitive Development, Cognitive Processes, Computer Assisted Instruction, Computer System Design
Sidhu, S. Manjit; Selvanathan, N. – Campus-Wide Information Systems, 2005
Purpose: To expose engineering students to using modern technologies, such as multimedia packages, to learn, visualize and solve engineering problems, such as in mechanics dynamics. Design/methodology/approach: A multimedia problem-solving prototype package is developed to help students solve an engineering problem in a step-by-step approach. A…
Descriptors: Engineering Education, Mechanical Skills, Mechanics (Physics), Learning Modules
Schwarz, Elmar; Brusilovsky, Peter; Weber, Gerhard – Journal of Educational Technology, 2005
New WWW technologies allow for integrating distance education power of WWW with interactivity and intelligence. Integrating on-line presentation of learning materials with the interactivity of problem solving environments and the intelligence of intelligent tutoring systems results in a new quality of learning materials that we call I3-textbooks.…
Descriptors: Distance Education, Problem Solving, Intelligent Tutoring Systems, Multimedia Materials
Lu, Chun-Hung; Wu, Chia-Wei; Wu, Shih-Hung; Chiou, Guey-Fa; Hsu, Wen-Lian – Educational Technology & Society, 2005
This paper presents a new model for simulating procedural knowledge in the problem solving process with our ontological system, InfoMap. The method divides procedural knowledge into two parts: process control and action performer. By adopting InfoMap, we hope to help teachers construct curricula (declarative knowledge) and teaching strategies by…
Descriptors: Problem Solving, Teaching Methods, Models, Educational Games
Baylor, Amy L.; Kozbe, Barcin – 1998
This paper describes a Personal Intelligent Mentor (PIM) that facilitates metacognitive development in the domain of solving logic word puzzles. Metacognition is an important aspect for critical thinking skills. High school students must develop logical and critical thinking abilities as a prerequisite for higher-level math and computer…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer System Design, Computer Uses in Education
Pon-Barry, Heather; Clark, Brady; Schultz, Karl; Bratt, Elizabeth Owen; Peters, Stanley; Haley, David – Educational Technology & Society, 2005
In this paper we describe the ways that SCoT, a Spoken Conversational Tutor, uses flexible and adaptive planning as well as multimodal task modeling to support the contextualization of learning in reflective dialogues. Past research on human tutoring has shown reflective discussions (discussions occurring after problem-solving) to be effective in…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Knowledge Representation, Educational Technology