Engineering Papers⌕ Search

Engineering topics

Fink, Pamela K.

Publications and source records attributed to Fink, Pamela K..

9 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A knowledge engineering taxonomy for intelligent tutoring system development

This paper describes a study addressing the issue of developing an appropriate mapping of knowledge acquisition methods to problem types for intelligent tutoring system development. Recent research has recognized that knowledge acquisition methodologies are not general across problem domains; the effectiveness of a method for obtaining knowledge depends on the characteristics of the domain and problem solving task. Southwest Research Institute developed a taxonomy of problem types by evaluating the characteristics that discriminate between problems and grouping problems that share critical characteristics. Along with the problem taxonomy, heuristics that guide the knowledge acquisition process based on the characteristics of the class are provided.

Fink, Pamela K.↗
NASA NTRS1991

Research into the development of a knowledge acquisition taxonomy

The focus of the research was on the development of a problem solving taxonomy that can support and direct the knowledge engineering process during the development of an intelligent tutoring system. The results of the research are necessarily general. Being only a small initial attempt at a fundamental problem in artificial intelligence and cognitive psychology, the process has had to be bootstrapped and the results can only provide pointers to further, more formal research designs.

Fink, Pamela K.↗
NASA NTRS1991

Research into the interaction between high performance and cognitive skills in an intelligent tutoring system

Two intelligent tutoring systems were developed. These tutoring systems are being used to study the effectiveness of intelligent tutoring systems in training high performance tasks and the interrelationship of high performance and cognitive tasks. The two tutoring systems, referred to as the Console Operations Tutors, were built using the same basic approach to the design of an intelligent tutoring system. This design approach allowed researchers to more rapidly implement the cognitively based tutor, the OMS Leak Detect Tutor, by using the foundation of code generated in the development of the high performance based tutor, the Manual Select Keyboard (MSK). It is believed that the approach can be further generalized to develop a generic intelligent tutoring system implementation tool.

Fink, Pamela K.↗
NASA NTRS1991

An intelligent tutoring system for the investigation of high performance skill acquisition

The issue of training high performance skills is of increasing concern. These skills include tasks such as driving a car, playing the piano, and flying an aircraft. Traditionally, the training of high performance skills has been accomplished through the use of expensive, high-fidelity, 3-D simulators, and/or on-the-job training using the actual equipment. Such an approach to training is quite expensive. The design, implementation, and deployment of an intelligent tutoring system developed for the purpose of studying the effectiveness of skill acquisition using lower-cost, lower-physical-fidelity, 2-D simulation. Preliminary experimental results are quite encouraging, indicating that intelligent tutoring systems are a cost-effective means of training high performance skills.

Fink, Pamela K.↗
NASA NTRS1991

Research into the development of a knowledge acquisition taxonomy

Monthly progress reports for September 1990 to January 1991 are given. Topics that are briefly covered include problem solving and learning taxonomies, knowledge acquisition techniques, software design, air traffic control, and space shuttle flight control.

Fink, Pamela K.↗
NASA NTRS1990

UFC advisor: An AI-based system for the automatic test environment

The Air Logistics Command within the Air Force is responsible for maintaining a wide variety of aircraft fleets and weapon systems. To maintain these fleets and systems requires specialized test equipment that provides data concerning the behavior of a particular device. The test equipment is used to 'poke and prod' the device to determine its functionality. The data represent voltages, pressures, torques, temperatures, etc. and are called testpoints. These testpoints can be defined numerically as being in or out of limits/tolerance. Some test equipment is termed 'automatic' because it is computer-controlled. Due to the fact that effective maintenance in the test arena requires a significant amount of expertise, it is an ideal area for the application of knowledge-based system technology. Such a system would take testpoint data, identify values out-of-limits, and determine potential underlying problems based on what is out-of-limits and how far. This paper discusses the application of this technology to a device called the Unified Fuel Control (UFC) which is maintained in this manner.

Lincoln, David T.↗
NASA NTRS1989

An intelligent tutor for a high performance domain

The use of intelligent tutoring systems based on the apprenticeship approach to training is explored as a possible solution to the problem of training individuals to operate and maintain complex devices, such as those used in the aerospace industry. A general approach to the development of such a system is presented, and a specific intelligent tutoring system designed for training mission control console operators is described as an example.

Fink, Pamela K.↗
NASA NTRS1988

NESSUS (Numerical Evaluation of Stochastic Structures Under Stress)/EXPERT: Bridging the gap between artificial intelligence and FORTRAN

The development of a probabilistic structural analysis methodology (PSAM) is described. In the near-term, the methodology will be applied to designing critical components of the next generation space shuttle main engine. In the long-term, PSAM will be applied very broadly, providing designers with a new technology for more effective design of structures whose character and performance are significantly affected by random variables. The software under development to implement the ideas developed in PSAM resembles, in many ways, conventional deterministic structural analysis code. However, several additional capabilities regarding the probabilistic analysis makes the input data requirements and the resulting output even more complex. As a result, an intelligent front- and back-end to the code is being developed to assist the design engineer in providing the input data in a correct and appropriate manner. The type of knowledge that this entails is, in general, heuristically-based, allowing the fairly well-understood technology of production rules to apply with little difficulty. However, the PSAM code, called NESSUS, is written in FORTRAN-77 and runs on a DEC VAX. Thus, the associated expert system, called NESSUS/EXPERT, must run on a DEC VAX as well, and integrate effectively and efficiently with the existing FORTRAN code. This paper discusses the process undergone to select a suitable tool, identify an appropriate division between the functions that should be performed in FORTRAN and those that should be performed by production rules, and how integration of the conventional and AI technologies was achieved.

Fink, Pamela K.↗