Automated exercise progression in simulation-based training

Dept. of Electr. & Comput. Eng., Central Florida Univ., Orlando, FL
IEEE Transactions on Systems Man and Cybernetics 07/1994; 24(6):863 - 874. DOI: 10.1109/21.293505
Source: IEEE Xplore

ABSTRACT As simulator-based training systems become more complex, the
amount of effort required to generate, monitor, and maintain training
exercises multiplies greatly. This has significantly increased the
burden on the instructors, potentially making the training experience
less efficient as well as less effective. Research on intelligent
tutoring systems (ITS) has largely addressed this issue by replacing the
instructor with a computer model of the appropriate pedagogical concepts
and the domain expertise. While this approach is highly desirable, the
effort required to develop and maintain an ITS can be quite significant.
A more modest as well as practical alternative to an ITS is the
development of intelligent computer-based tools that can support the
instructors in their tasks. The advantage of this approach is that
various tools can be developed to address the different aspects of the
instructor's duties. Moreover, without the burden of having to replace
the instructor, these tools are more easily developed and fielded in
existing trainers. One aspect of an instructor's task is to assess the
students' performance after each training exercise and select the next
exercise based on their previous performances. It would clearly be
advantageous if this exercise selection process were to be automated,
thus relieving the instructor of a significant burden and allowing him
to concentrate on other tasks. Therefore, the focus of this paper is the
development of a stand-alone system capable of determining exercise
progression and remediation automatically during a training session in a
simulator-based trainer, on the basis of the students's past
performance. Instructional heuristics were developed to carry out the
exercise progression process. A prototype was developed and applied to
gunnery training on the Army M1 main battle tank

  • [Show abstract] [Hide abstract]
    ABSTRACT: In the past decade, researchers have attempted to develop computer‐assisted learning and testing systems to help students improve their learning performance. Conventional testing systems simply provide students with a score, and do not offer sufficient information in order to improve their learning performance. It would be of more benefit to students if the test results could be critically analysed and hence learning suggestions could be offered accordingly. This study proposes an algorithm for diagnosing students’ learning problems and provides personalised learning suggestions for Science and Mathematics courses. An intelligent tutoring, evaluation and diagnosis system has been implemented based on the novel approach. Experimental results on a Mathematics course have demonstrated the feasibility of this approach in enhancing students’ learning performance, making it highly promising for further study.
    Innovations in Education and Teaching International 02/2008; 45(1):77-89. DOI:10.1080/14703290701757476 · 0.79 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Situated tutors combine features of intelligent tutoring systems with simulated environments. A construct definition for situated tutors was newly developed, and, in this article, we use it to classify an extensive review of operational instructional technologies in order to identify a robust set of situated tutors. We document 86 situated tutors, half of which directly support military training. Initial empirical evidence from these systems suggests that situated tutors may outperform traditional simulations or intelligent tutors. As additional evidence is gathered, we hypothesize that situated tutors will also demonstrate efficiency and effectiveness in cognitive readiness instruction.
    Military Psychology 01/2012; 24(2):166-193. DOI:10.1080/08995605.2012.672910 · 0.72 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Continuously motivating people to exercise regularly is more important than finding a way out of barriers such as lack of time, cost of equipment, lack of nearby facilities, and poor weather. Our proposed system presents practicable methods of motivation through a diverse exercise aid system. The Health Improvement and Management System (all-in-one system which saves space and maintenance costs) measures and evaluates a diverse body shape analysis and physical fitness test and directs users to automated personalized exercise prescription which is prescribed by the expert system of three types of exercise templates: aerobics, anaerobics, and leisure sports. Automated personalized exercise prescriptions are built into XML based documents because the data needs to be in the form of flexible, expansible, and convertible structures in order to process various exercise templates, BIOFIT, a digital exercise trainer, monitors and provides feedback on the physiological parameters while users are working out in the gymnasium. If these parameters do not range within the prescribed target zone, the device will alarm users to control the exercise and make the exercise trainer adjust systemically the proper exercise level. Numeric health information such as the report of the physical fitness test and the exercise prescription makes people stay interested in exercising. In addition, this service can be delivered through the Internet.
    01/2005; 26(5).