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Representing and Teaching Knowledge for Troubleshooting/Debugging. Technical Report No. 292.

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Title: Representing and Teaching Knowledge for Troubleshooting/Debugging. Technical Report No. 292.
Authors: Wescourt, Keith T., Hemphill, Linda, Stanford Univ., CA. Inst. for Mathematical Studies in Social Science.
Peer Reviewed: N
Page Count: 150
Publication Date: 1978
Sponsoring Agency: Advanced Research Projects Agency (DOD), Washington, DC.
Office of Naval Research, Washington, DC. Personnel and Training Branch.
Contract Number: N00014-77-C-0124
Document Type: Reports - Research
Descriptors: Artificial Intelligence, Computer Programs, Concept Teaching, Information Processing, Instructional Design, Models, Problem Solving, Programers, Programing Problems, Skill Development
Abstract: The goal of the present project was to identify the types of knowledge necessary and useful for competent troubleshooting/debugging and to examine how new approaches to formal instruction might influence the attainment of competence by students. The research focused on the role of general strategies in troubleshooting/debugging, and how they might be represented and taught explicitly and directly in order to avoid the cost and other drawbacks of learning indirectly by observation and practice. Related work on troubleshooting/debugging was examined, and in conjunction with a logical analysis, contributed to a characterization of troubleshooting/debugging problems that emphasizes their generality across a number of technical fields and informal contexts. Further data gathered from students learning computer programming suggest that expert debuggers do not necessarily have superior general strategies; rather, their expertise derives from specific and sometimes idiosyncratic knowledge acquired through experience. An attempt to obtain a rigorous characterization of the differences and defects in the debugging strategy of students by applying a model-oriented data analysis method was unsuccessful. Another study was conducted to determine the effects of presenting a tutorial text which describes a few general heuristics designed to correct strategy deficits; results indicated a marginal increase in the apparent use of some of the heuristics by those who studied the text compared to a group who did not. The several methodological limitations and problems encountered suggest that, if the causes of differences in ability are to be specified in detail, and if the effects of direct problem-solving instruction are to be assessed, then it will be necessary to perfect model-based data analysis methods. (Author/DAG)
Journal Code: RIEAUG1978
Entry Date: 1978
Accession Number: ED152321
Database: ERIC
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  Data: Representing and Teaching Knowledge for Troubleshooting/Debugging. Technical Report No. 292.
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  Data: <searchLink fieldCode="AR" term="%22Wescourt%2C+Keith+T%2E%22">Wescourt, Keith T.</searchLink><br /><searchLink fieldCode="AR" term="%22Hemphill%2C+Linda%22">Hemphill, Linda</searchLink><br /><searchLink fieldCode="AR" term="%22Stanford+Univ%2E%2C+CA%2E+Inst%2E+for+Mathematical+Studies+in+Social+Science%2E%22">Stanford Univ., CA. Inst. for Mathematical Studies in Social Science.</searchLink>
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  Data: N
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  Data: 150
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  Data: 1978
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  Data: Advanced Research Projects Agency (DOD), Washington, DC.<br />Office of Naval Research, Washington, DC. Personnel and Training Branch.
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  Data: N00014-77-C-0124
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Programs%22">Computer Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Concept+Teaching%22">Concept Teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Information+Processing%22">Information Processing</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Design%22">Instructional Design</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+Solving%22">Problem Solving</searchLink><br /><searchLink fieldCode="DE" term="%22Programers%22">Programers</searchLink><br /><searchLink fieldCode="DE" term="%22Programing+Problems%22">Programing Problems</searchLink><br /><searchLink fieldCode="DE" term="%22Skill+Development%22">Skill Development</searchLink>
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  Data: The goal of the present project was to identify the types of knowledge necessary and useful for competent troubleshooting/debugging and to examine how new approaches to formal instruction might influence the attainment of competence by students. The research focused on the role of general strategies in troubleshooting/debugging, and how they might be represented and taught explicitly and directly in order to avoid the cost and other drawbacks of learning indirectly by observation and practice. Related work on troubleshooting/debugging was examined, and in conjunction with a logical analysis, contributed to a characterization of troubleshooting/debugging problems that emphasizes their generality across a number of technical fields and informal contexts. Further data gathered from students learning computer programming suggest that expert debuggers do not necessarily have superior general strategies; rather, their expertise derives from specific and sometimes idiosyncratic knowledge acquired through experience. An attempt to obtain a rigorous characterization of the differences and defects in the debugging strategy of students by applying a model-oriented data analysis method was unsuccessful. Another study was conducted to determine the effects of presenting a tutorial text which describes a few general heuristics designed to correct strategy deficits; results indicated a marginal increase in the apparent use of some of the heuristics by those who studied the text compared to a group who did not. The several methodological limitations and problems encountered suggest that, if the causes of differences in ability are to be specified in detail, and if the effects of direct problem-solving instruction are to be assessed, then it will be necessary to perfect model-based data analysis methods. (Author/DAG)
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      Pagination:
        PageCount: 150
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Computer Programs
        Type: general
      – SubjectFull: Concept Teaching
        Type: general
      – SubjectFull: Information Processing
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      – SubjectFull: Instructional Design
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      – SubjectFull: Models
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      – SubjectFull: Problem Solving
        Type: general
      – SubjectFull: Programers
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      – SubjectFull: Programing Problems
        Type: general
      – SubjectFull: Skill Development
        Type: general
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      – TitleFull: Representing and Teaching Knowledge for Troubleshooting/Debugging. Technical Report No. 292.
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            NameFull: Stanford Univ., CA. Inst. for Mathematical Studies in Social Science.
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            NameFull: Wescourt, Keith T.
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            NameFull: Hemphill, Linda
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              Type: published
              Y: 1978
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