Cognitive Task Analyses for Life Science Automation Training Program Design.

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Title: Cognitive Task Analyses for Life Science Automation Training Program Design.
Author: Green, Rebecca
Advisors: Regina Stoll, Committee Member
Robert St. Amant, Committee Member
Christopher Mayhorn, Committee Co-Chair
David Kaber, Committee Chair
Abstract: The purpose of this study was to develop a systematic approach to the translation of Cognitive Task Analyses (CTAs), including Goal Directed Task Analysis (GDTA) and Abstraction Hierarchy (AH) models, into a Situation Awareness (SA) based training program for operators of High-throughput (biological) screening (HTS) systems. Traditional on-the-job (OTJ) training of new HTS operators usually consists of several weeks of assisting a lead biochemist to become familiar with methods and automated systems. Unfortunately, this approach to training is typically unstructured and learning results may be highly variable. In order to design instruction to support learning of cognitive processes as part of HTS, the information demands engendered by the task need to be identified. This can be achieved using CTAs as the basis for training program design. Various CTA methods, including the Critical Decision Method (CDM) and Precursor-Action-Results-Interpretation, have been used to develop training. However, no standardized methods exist for relating the outcomes of the integration of multiple CTA methods to support training program design. This study, therefore, combined information requirements from a GDTA and system resource requirements identified through AH models to establish content on HTS processes for delivery through an electronic training program. The goals and sequences of task steps within the training program were identified by the GDTA. The use of AH models of the HTS system provided a method for determining the purpose and function of the software and devices relative to different operator functional requirements. This combination of information from the CTAs provided a systematic approach for specifying training strategies and parameters. The training program presented learners with content for development of the three levels of operator SA (perception, comprehension, and projection) and knowledge structures pertaining to HTS system operations. Following development of the prototype electronic training program and the comparison traditional training program, an evaluation occurred through a three-part survey with comparison to the traditional lab training provided to expert operators of an HTS system. The evaluation incorporated two knowledge assessment tests, a usability survey, and a survey of the effectiveness of the SA elements of the training program. Results provided preliminary evidence that a CTA-based training program can improve operators' knowledge structures beyond OTJ training. Furthermore, operator performance on SA questions indicated improvements in knowledge structures associated with perceptual elements, comprehension of those elements, and projection of the future states of HTS systems. Additionally, since experience can lead to differences in operator mental models pertaining to HTS systems, the effect of two types of overall experience and individual task experience were measured. Results indicated that the CTA-based training program was effective in providing improved SA knowledge and general knowledge structures for HTS operators beyond their initial knowledge of the system (i.e., considering work experience and education). A heuristic-based evaluation of both training programs identified few unique usability problems, suggesting the usability of the training programs did not interfere with the development of learner knowledge structures. Finally, on the basis of these results, a set of general guidelines for the design of the CTA-based training programs was developed. These guidelines included methods for structuring the components of the training program to support the three levels of SA and the amount of text that should be shown for each task.
Date: 2008-08-11
Degree: PhD
Discipline: Psychology

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