This thesis considers how to teach novices to debug computer programs. The investigation is specifically aimed at students in first year of computer science at university. The goal is to find an effective method of improving the debugging ability of novice subjects. Novices are less effective than experts. Although weaker across the board, novices display a critical lack of strategic skills in the debugging domain. Novices become lost and discouraged easily. Novices do not make good use of program structure, do not use test cases intelligently, and do not track their progress. Even a slight improvement in these aspects has the potential to significantly improve performance. Expert debugging behaviour was examined. This provided the basis for a model of debugging to be used in instructing novices. Teaching materials were developed to instruct and support students in following the model. The model and training were then tested in both laboratory and classroom situations. Results were mixed, with a generally positive trend. The model by itself was not overly effective. When the model was accompanied by training materials containing examples and scaffolding, students who were willing to spend time examining the training usually showed some improvement. In a few cases, the student's debugging style was dramatically improved. The improved performance seems to come partially from improved skill and partially from motivation. The model and materials show potential, and are likely to be more effective when used in an environment that allows interaction, rather than the current paper-based, non-interactive tutorial.

Report (M.S.)--Virginia Polytechnic Institute and State University, 1994. / Abstract. Includes bibliographical references (leaves 40-45). Also available via the Internet.

Thesis (M.S.)--Ohio University, June, 1989. / Title from PDF t.p.

Thesis (M.S.)--Rochester Institute of Technology, 1985. / Typescript. Includes bibliographical references (leaves 74-75).

Thesis--University of Florida. / Description based on print version record. Typescript. Vita. Includes bibliographical references (leaves 125-129).

Thesis (M.B.A.)--University of Hong Kong, 1996. / Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 1998. / Vita. Includes bibliographical references (leaves 179-186). Available also in a digital version from Dissertation Abstracts.

Revision of thesis --Stanford University, 1980. / Includes index. Bibliography: p. [165]-169.

Thesis (M.A.)--Rowan University, 2008. / Typescript. Includes bibliographical references.

Object experts quickly and accurately discriminate objects within their domain of expertise. Although expert recognition has been extensively studied both at the behavioral- and neural-levels in both real-world and laboratory trained experts, we know little about the visual features and perceptual strategies that the expert learns to use in order to make fast and accurate recognition judgments. Thus, the aim of this work was to identify the visual features (e.g., color, form, motion) and perceptual strategies (e.g., fixation pattern) that real-world experts employ to recognize objects from their domain of expertise. Experiments 1 to 3 used psychophysical methods to test the role of color, form (spatial frequencies), and motion, respectively, in expert object recognition. Experiment 1 showed that although both experts and novices relied on color to recognize birds at the family level, analysis of the response time distribution revealed that color facilitated expert performance in the fastest and slowest trials whereas color only helped the novices in the slower trials. Experiment 2 showed that both experts and novices were more accurate when bird images contained the internal information represented by a middle range of SFs, described by a quadratic function. However, the experts, but not the novices, showed a similar quadratic relationship between response times and SF range. Experiment 3 showed that, contrary to our prediction, both groups were equally sensitivity to global bird motion. Experiment 4, which tested the perceptual stategies of expert recognition in a gaze-contingent eye-tracking paradigm, showed that only in the fastest trials did experts use a wider range of vision. Experiment 5, which examined the neural representations of categories within the expert domain, suggested that the mechanisms that represents within-categories of faces also represented within-categories from the domain of expertise, but not the novice domain. Collectively, these studies suggest that expertise influence visual discrimination mechanisms such that they become more sensitive to the visual dimensions upon which the expert domains are discriminated. / Graduate / 2018-12-12