An investigation of the relationship between cognitive style and the diagnostic skills of novice COBOL student programmers Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/7m01bq982

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • For the past thirty years the majority of the research on the cognitive demands of learning computer programming has assumed that successful computer programmers display certain aptitudes. Some researchers indicate that studies linking different prerequisite profiles of abilities to different programming outcomes are needed. Such research might dispel many of these notions. There is evidence that personality variables are related to overall performance in computer programming. Only recently has this type of research been conducted. The purpose of this study was to investigate the influence of one personality variable, global-analytic cognitive style, on one of the component skills of programming, debugging. Thirty subjects were administered the Group Embedded Figures Test (GEFT) to determine their cognitive style. Instruments were developed to measure subjects' skills in diagnosing both syntactic and logic errors in COBOL programs. Weighting schemes, derived from results of previous research, were developed for scoring the diagnostic exams. Data were analyzed using Spearmans Rank Correlation Coefficient. Results of statistical analysis failed to support hypotheses (at the .05 level of significance) stating that GEFT scores were related to subjects' ability to locate and correct either syntactic or logic errors in computer programs. This result appears to indicate that measures of individuals' cognitive style represent an unsatisfactory means for predicting success on one aspect of computer programming skill for novices. However at higher alpha levels the results indicate support of the hypotheses.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces
Additional Information
  • description.provenance : Made available in DSpace on 2010-07-15T16:51:59Z (GMT). No. of bitstreams: 1 CavaianiThomasP1989.pdf: 1173456 bytes, checksum: 95787db6accbef07d974a00de2dd6156 (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2010-07-15T16:51:59Z (GMT) No. of bitstreams: 1 CavaianiThomasP1989.pdf: 1173456 bytes, checksum: 95787db6accbef07d974a00de2dd6156 (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2010-07-15T16:48:44Z (GMT) No. of bitstreams: 1 CavaianiThomasP1989.pdf: 1173456 bytes, checksum: 95787db6accbef07d974a00de2dd6156 (MD5)
  • description.provenance : Submitted by Joe Nguyen (jnscanner@gmail.com) on 2010-06-25T22:57:44Z No. of bitstreams: 1 CavaianiThomasP1989.pdf: 1173456 bytes, checksum: 95787db6accbef07d974a00de2dd6156 (MD5)

Relationships

In Administrative Set:
Last modified: 10/21/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items