Development principles for intelligent tutoring systems: Integrating cognitive theory into the development of computer-based instruction

1993 ◽  
Vol 41 (1) ◽  
pp. 59-72 ◽  
Author(s):  
Michael A. Orey ◽  
Wayne A. Nelson
Keyword(s):  
Intelligent Tutoring Systems ◽  
Cognitive Theory ◽  
Intelligent Tutoring ◽  
Tutoring Systems ◽  
Computer Based Instruction ◽  
Computer Based ◽  
Based Instruction

scholarly journals Comparison and Efficacy of Synergistic Intelligent Tutoring Systems with Human Physiological Response

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 460 ◽  
Author(s):  
Fehaid Alqahtani ◽  
Naeem Ramzan
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Mental States ◽  
Physiological Signals ◽  
Experimental Comparison ◽  
High Precision Measurement ◽  
Tutoring Systems ◽  
Machine Learning Classification ◽  
Computer Based ◽  
Based Instruction

The analysis of physiological signals is ubiquitous in health and medical diagnosis as a primary tool for investigation and inquiry. Physiological signals are now being widely used for psychological and social fields. They have found promising application in the field of computer-based learning and tutoring. Intelligent Tutoring Systems (ITS) is a fast-paced growing field which deals with the design and implementation of customized computer-based instruction and feedback methods without human intervention. This paper introduces the key concepts and motivations behind the use of physiological signals. It presents a detailed discussion and experimental comparison of ITS. The synergism of ITS and physiological signals in automated tutoring systems adapted to the learner’s emotions and mental states are presented and compared. The insights are developed, and details are presented. The accuracy and classification methods of existing systems are highlighted as key areas of improvement. High-precision measurement systems and neural networks for machine-learning classification are deemed prospective directions for future improvements to existing systems.

An Investigation Into the Feasibility of Using Intelligent Tutoring Systems in Preparing Students for Laboratory Work

1998 ◽  
Vol 35 (2) ◽  
pp. 107-116 ◽  
Author(s):  
Barry Dwolatzky ◽  
Ashley Levin ◽  
Steven Shulman
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Controlled Experiment ◽  
Laboratory Work ◽  
Tutoring Systems ◽  
Computer Based Training ◽  
Training Systems ◽  
Computer Based

Intelligent Tutoring Systems (ITS) are computer based training systems with the ability to adapt to the requirements of each student A prototype ITS was developed to assess the feasibility of using such systems to prepare students for laboratory work. This prototype was evaluated in a controlled experiment involving 252 students.

Enhancing Intelligent Tutoring Systems with the Agent Paradigm

2011 ◽  
pp. 46-69 ◽  
Author(s):  
Xin Bai ◽  
John B. Black
Keyword(s):  
Learning Environment ◽  
Intelligent Tutoring Systems ◽  
Teaching And Learning ◽  
Intelligent Tutoring ◽  
Game Based Learning ◽  
Tutoring Systems ◽  
The Real ◽  
Future Design ◽  
Cognitive Framework ◽  
Computer Based

A cognitive framework called REflective Agent Learning environment (REAL) is developed in this study. REAL is a reusable framework that allows researchers to develop a simulation-based learning environment where users can learn through passing their thoughts to some computer-based agents and observe how the agents embodying their knowledge behave as the result of their instruction. Our research benefits from the research in Intelligent Tutoring Systems, game based learning systems, and agent technologies, stressing reflection as part of the thinking processes. It focuses on the design of the framework and the testing of its usability. The external evaluation of specific implementations serves as the guidance for the future design of the REAL applications. We hope, by grounding themselves in the needs of local practice, the REAL applications can give us opportunities to understand how theoretical claims about teaching and learning can be effectively transformed into meaningful learning.

Enhancing Intelligent Tutoring Systems with the Agent Paradigm

2011 ◽  
pp. 440-463
Author(s):  
Xin Bai ◽  
John B. Black
Keyword(s):  
Learning Environment ◽  
Intelligent Tutoring Systems ◽  
Teaching And Learning ◽  
Intelligent Tutoring ◽  
Game Based Learning ◽  
Tutoring Systems ◽  
The Real ◽  
Future Design ◽  
Cognitive Framework ◽  
Computer Based

A cognitive framework called REflective Agent Learning environment (REAL) is developed in this study. REAL is a reusable framework that allows researchers to develop a simulation-based learning environment where users can learn through passing their thoughts to some computer-based agents and observe how the agents embodying their knowledge behave as the result of their instruction. Our research benefits from the research in Intelligent Tutoring Systems, game based learning systems, and agent technologies, stressing reflection as part of the thinking processes. It focuses on the design of the framework and the testing of its usability. The external evaluation of specific implementations serves as the guidance for the future design of the REAL applications. We hope, by grounding themselves in the needs of local practice, the REAL applications can give us opportunities to understand how theoretical claims about teaching and learning can be effectively transformed into meaningful learning.

Integrating an Intelligent Tutoring Facility into a Gaming Simulation Environment

1997 ◽  
Vol 12 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Julika Siemer ◽  
Marios C. Angelides
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Simulation Game ◽  
Simulation Environment ◽  
Business Simulation ◽  
Educational Value ◽  
Tutoring Systems ◽  
Gaming Simulation ◽  
Computer Based ◽  
And Training

Gaming simulations and intelligent tutoring systems are both substantive research and development areas within the field of computer-based education and training which have the potential for mutual enhancement. This paper argues that the pedagogical effectiveness of gaming simulations can be increased through the integration of an intelligent tutoring facility and examines possible roles for such support within a gaming simulation environment. It then commences to present INTUITION, the implementation of the Metal Box Business Simulation game, that illustrates how an intelligent tutoring facility may be integrated within a gaming simulation environment in order to increase its educational value.

Towards knowledge-based tutors: a survey and appraisal of Intelligent Tutoring Systems

1991 ◽  
Vol 6 (2) ◽  
pp. 59-95 ◽  
Author(s):  
Tomas Sokolnicki
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Tutoring Systems ◽  
Computer Based Training ◽  
Training Systems ◽  
Knowledge Based ◽  
Engineering Discipline ◽  
Key Points ◽  
Key Issues ◽  
Computer Based

AbstractIntelligent tutoring systems can be seen as a next step for computer-based training systems, but also as an important by-product of knowledge-based expert systems. This paper surveys the development and progress in the area, with a special emphasis on the potential for an emerging engineering discipline as opposed to a mere crafting of systems. Major components in intelligent tutoring systems as realized so far are discussed, and key issues for successful future development identified. Knowledge representation, student modelling, planning, natural language issues, explanations and learning are discussed in more depth as being the cornerstones of both tutoring systems and artificial intelligence. Examples from specific implementations are used to illustrate key points. In the concluding discussion we present our attempt at dealing with some of the problems facing the area. In the project Knowledge-Linker, we aim at extending the functionality of a knowledge-based system with tutoring capabilities, and suggest one way of explicitly dealing with teaching strategies.

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