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.

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.

scholarly journals SISTEMAS TUTORES INTELIGENTES COMO APOYO EN EL PROCESO DE APRENDIZAJE

2015 ◽  
Vol 6 (1) ◽  
pp. 25
Author(s):  
Yilver Estiven Molina Hurtatiz ◽  
Yois Smith Pascuas Rengifo ◽  
Edwin Eduardo Millan Rojas
Keyword(s):  
Teaching Methods ◽  
Intelligent Tutoring Systems ◽  
Teaching And Learning ◽  
Efficient Solution ◽  
Intelligent Tutoring ◽  
Learning Processes ◽  
Educational Context ◽  
Tutoring Systems ◽  
Teaching Learning ◽  
Excellent Tool

En los procesos de enseñanza-aprendizaje surgen diversos problemas en cuanto al entendimiento y la comprensión del conocimiento. Estas dificultades radican principalmente en que todas las personas tienen un estilo de aprendizaje diferente y los métodos clásicos de enseñanza no cubren sus necesidades particulares. El desarrollo de la tecnología ha impulsado la creación de herramientas que brindan una solución eficiente a dicha problemática: los Sistemas Tutores Inteligentes (STI). El objetivo principal de este artículo es la identificación de las principales características de estos tutores, haciendo énfasis en los beneficios que ofrece como apoyo en los procesos de enseñanza-aprendizaje en el contexto educativo. El método utilizado es el descriptivo y sistémico, el cual permite recopilar los datos necesarios. La investigación permitió reunir los aspectos más relevantes de los STI y presentarlos como una herramienta óptima para llevar a cabo un proceso de aprendizaje.Intelligent System Tutors as Support in the Learning ProcessAbstractIn the teaching and learning processes various problems arise as to the understanding and comprehension of knowledge. These difficulties are mainly in which everyone has a different way of learning and classic teaching methods do not meet your particular needs. The development of technology has led to the creation of tools that provides an efficient solution to this problem: Intelligent Tutoring Systems (ITS). The main objective of this article is to identify the main features of these tutors, emphasizing the benefits and support in the teaching-learning in the educational context. The method used is the descriptive and systemic, which allows you to collect the necessary data. The research brought together the most important aspects of ITS and present them as an excellent tool to perform a learning process.Keywords: intelligent applications, teaching strategies, Artificial Intelligence (IA), modules, knowledge.

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.

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.

scholarly journals Data-Driven Intelligent Tutoring Systems for STEM+C Learning and Teaching

2019 ◽  
Vol 4 (9) ◽  
pp. 202-206
Author(s):  
Hieu Trong Bui
Keyword(s):  
Problem Solving ◽  
Intelligent Tutoring Systems ◽  
Student Behavior ◽  
Teaching And Learning ◽  
Intelligent Tutoring ◽  
Data Driven ◽  
Tutoring Systems ◽  
Learning And Teaching ◽  
Past Data ◽  
Problem Solving Behavior

It is wide known that one of the most effective ways to learn is through problem solving. In recent years, it is widely known that problem solving is a central subject and fundamental ability in the teaching and learning. Besides, problem solving is integrated in the STEM+C (Science, Technology, Engineering, and Math plus Computing, Coding or Computer Science) fields. Intelligent tutoring systems (ITSs) have been shown to be effective in supporting students' domain-level learning through guided problem solving practice. Intelligent tutoring systems provide personalized feedback (in the form of hints) to students and improve learning at effect sizes approaching that of human tutors. However, creating an ITS to adapt to individual students requires the involvement of experts to provide knowledge about both the academic domain and novice student behavior in that domain’s curriculum. Creating an ITS requires time, resources, and multidisciplinary skills. Because of the large possible range of problem solving behavior for any individual topic, the amount of expert involvement required to create an effective, adaptable tutoring system can be high, especially in open-ended problem solving domains. Data-driven ITSs have shown much promise in increasing effectiveness by analyzing past data in order to quickly generate hints to individual students. However, the fundamental long term goal was to develop “better, faster, and cheaper” ITSs. In this work, the main goal of this paper is to: 1) present ITSs used in the STEM+C education; and 2) introduce data-driven ITSs for STEM+C education.

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.

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