An Evolution of Tutoring and Training from Humans to Intelligent Systems: Human Factors Considerations

2009 ◽  
Vol 53 (26) ◽  
pp. 1898-1902
Author(s):  
Jessica M. Ray ◽  
John S. Barnett
Keyword(s):  
Human Factors ◽  
Intelligent Tutoring Systems ◽  
Intelligent Systems ◽  
Tutoring Systems ◽  
Technological Advances ◽  
Effective Form ◽  
Computer Based ◽  
Training Research ◽  
Learning Issues ◽  
And Training

As training researchers and developers, we strive to understand and produce effective and efficient training. Research suggests the most effective form of instruction is individualized human tutoring. Yet this is rarely the most efficient form of instruction monetarily or in instructor time. Technological advances and a vision of effective, yet more efficient, computer based tutors has led to the development of sophisticated new training technologies such as Intelligent Tutoring Systems (ITSs). These systems have yet to reach their full forecast potential. In this paper we theorize that issues key to successful advancement of ITSs are human factors issues. Primary of these issues is determining how technology mediation impacts not only cognition, but also other key learning issues such as affect, emotions, motivation, and trust.

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.

Machine Learning and Human Factors: Status, Applications, and Future Directions

2018 ◽  
Vol 62 (1) ◽  
pp. 135-138 ◽  
Author(s):  
Nathan Lau ◽  
Lex Fridman ◽  
Brett J. Borghetti ◽  
John D. Lee
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Interaction Design ◽  
Intelligent Systems ◽  
Consumer Products ◽  
Learning Approaches ◽  
Future Directions ◽  
Industrial Systems ◽  
Human Factors Research ◽  
And Training

As machine learning approaches ubiquity in industrial systems and consumer products, human factors research must attend to machine learning, specifically on how intelligent systems built on machine learning are different from early generations of automated systems, and what these differences mean for human-system interaction, design, evaluation and training. This panel invites five researchers in different domains to discuss how human factors can contribute to machine learning research and applications, as well as how machine learning presents both challenges and contributions for human factors.

Learning Issues for Intelligent Tutoring Systems

1989 ◽  
Vol 102 (4) ◽  
pp. 581 ◽  
Author(s):  
Joseph Psotka ◽  
Heinz Mandl ◽  
Alan Lesgold
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Tutoring Systems ◽  
Learning Issues

Special Session: Intelligent Tutoring and Help Systems

1987 ◽  
Vol 31 (3) ◽  
pp. 280-280
Author(s):  
Philip J. Smith ◽  
Elliot Soloway ◽  
John Carroll
Keyword(s):  
Human Factors ◽  
Intelligent Tutoring Systems ◽  
Computational Models ◽  
Human Performance ◽  
Intelligent System ◽  
Intelligent Tutoring ◽  
Special Session ◽  
Research Issues ◽  
Tutoring Systems ◽  
Area Of Interest

In recent years, considerable effort has been focused on the development of computational models of expert human performance. One class of expertise that has been studied is that of human tutors. The resultant intelligent tutoring systems are intended to provide the user with the “instructional advantage that a sophisticated human tutor can provide,” (Anderson, Boyle and Reiser, 1985). This line of research is of interest to the human factors community for two reasons: 1. Intelligent tutoring systems offer potential tools for use in training and educational programs, a long-standing area of interest to human factors researchers and practitioners; 2. There are many human factors and human performance issues that should be addressed in the design of such tutoring systems. The speakers in this special session will provide an overview of research issues in the design of intelligent tutoring systems. Relevant conceptual issues and approaches will be highlighted in the context of a variety of application areas. Included will be a discussion of the “use of intelligent system monitors that allow users to integrate the time and effort spent on learning with actual use of a system”, (Carroll and McKendree, 1987).

scholarly journals The Challenges of Building Intelligent Tutoring Systems for Teams

2016 ◽  
Vol 60 (1) ◽  
pp. 1981-1985 ◽  
Author(s):  
Desmond Bonner ◽  
Stephen Gilbert ◽  
Michael C. Dorneich ◽  
Eliot Winer ◽  
Anne M. Sinatra ◽  
...  
Keyword(s):  
Intelligent Tutoring Systems ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
Lessons Learned ◽  
Tutoring System ◽  
Tutoring Systems ◽  
Team Research ◽  
Individual Instruction ◽  
Individual Task ◽  
And Training

Intelligent Tutoring Systems have been useful for individual instruction and training, but have not been widely created for teams, despite the widespread use of team training and learning in groups. This paper reviews two projects that developed team tutors: the Team Multiple Errands Task (TMET) and the Recon Task developed using the Generalized Intelligent Framework for Tutoring (GIFT). Specifically, this paper 1) analyzes why team tasks have significantly more complexity than an individual task, 2) describes the two team-based platforms for team research, and 3) explores the complexities of team tutor authoring. Results include a recommended process for authoring a team intelligent tutoring system based on our lessons learned that highlights the differences between tutors for individuals and team tutors.

U.S. Bureau of Mines Training and Evaluation Research: Overview of the Present and the Future

1981 ◽  
Vol 25 (1) ◽  
pp. 554-554
Author(s):  
Jeanne T. Bernard
Keyword(s):  
Human Factors ◽  
Health And Safety ◽  
Skills Training ◽  
Mine Safety ◽  
Performance Criteria ◽  
Occupational Training ◽  
Error Type ◽  
Ongoing Research ◽  
Training Research ◽  
And Training

In order to assist the mining community in its effort to reduce human-error type accidents, the Bureau of Mines has directed part of its training research efforts to the development of performance-based methods of evaluating employee training. Additional training research efforts have been in (1) developing a base of content material, (2) designing methods for structuring and evaluating health and safety training, and (3) the continuing investigation/application of current learning technology. The results of this ongoing research will significantly enhance the effectiveness of the training opportunities available to the mining population today. This presentation will focus on the development of innovative training methodologies and evaluation techniques designed to assist the trainers in assessing and improving their health and safety and occupational training. A brief overview of current human factors (ergonomics) research will demonstrate the complementary objectives that ergonomics and training serve to enhance mine safety. A discussion of the systematic approach on the analysis and use of a needs-assessment, the specification of instructional objectives, the use of controlled training experiences (both classroom and on-the-job training) and the identification of a performance-criteria will be highlighted. Once evaluation procedures are established, the resultant findings can be used to improve the training process. To better disseminate this resultant information to aid in upgrading miner training, it is imperative that data-collection methods and analysis procedures be improved for evaluating health and safety and occupational skills training. The Bureau's current efforts in developing such a management-information system for the collection and cataloging of human factors and training data, and the development of methods of evaluating and focusing health and safety investments at the mines will also be addressed.

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.

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