{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/64669"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/64669","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"The effect of computer programming experience on mathematical problem solving ability","abstract":"Five component problem-solving skills (general strategy, planning, logical thinking, algebraic variables, and debugging) were identified as common elements of both computer programming and mathematical problem-solving. Based on the similarities of these general skills in specific contexts, a theory was generated that the skills would transfer and that experience in computer programming would cause an improvement in mathematical problem-solving achievement. A path model was constructed to illustrate this hypothesized causal relationship between computer programming and mathematical problem-solving achievement. In order to control for other relevant variables, the model also included mathematics experience, access to a home computer, ability, socioeconomic status, and gender. The model was tested with a sample of 800 high school students in seven southwest Virginia high schools. Results indicated that ability had the largest causal effect on mathematical problem-solving achievement. Three variables had a moderate effect: computer programming experience, mathematics experience, and gender. The other two variables in the model (access to a home computer and socioeconomic status) were only very slightly related to mathematical problem-solving achievement. The conclusion of the study was that there was evidence to support the theory of transfer of skills from computer programming experience to mathematical problem-solving. Once ability and gender were controlled, computer programming experience and mathematics experience both had causal effects on mathematical problem-solving achievement. This suggests that to maximize mathematical problem-solving scores, a curriculum should include both mathematics and computer programming experiences.","abstract_html":"Five component problem-solving skills (general strategy, planning, logical thinking, algebraic variables, and debugging) were identified as common elements of both computer programming and mathematical problem-solving. Based on the similarities of these general skills in specific contexts, a theory was generated that the skills would transfer and that experience in computer programming would cause an improvement in mathematical problem-solving achievement. A path model was constructed to illustrate this hypothesized causal relationship between computer programming and mathematical problem-solving achievement. In order to control for other relevant variables, the model also included mathematics experience, access to a home computer, ability, socioeconomic status, and gender. The model was tested with a sample of 800 high school students in seven southwest Virginia high schools. Results indicated that ability had the largest causal effect on mathematical problem-solving achievement. Three variables had a moderate effect: computer programming experience, mathematics experience, and gender. The other two variables in the model (access to a home computer and socioeconomic status) were only very slightly related to mathematical problem-solving achievement. The conclusion of the study was that there was evidence to support the theory of transfer of skills from computer programming experience to mathematical problem-solving. Once ability and gender were controlled, computer programming experience and mathematics experience both had causal effects on mathematical problem-solving achievement. This suggests that to maximize mathematical problem-solving scores, a curriculum should include both mathematics and computer programming experiences.","abstract_has_math":false,"creators":["McCoy, Leah Paulette"],"institution":"Virginia Polytechnic Institute and State University","degree_name":"Ed. D.","degree_level":"doctoral","degree_discipline":"Curriculum and Instruction","degree_department":"Curriculum and Instruction","school":null,"contributors":[],"advisors":[],"committee_chairs":["Dodl, Norman R."],"committee_members":["Burton, John K.","Weber, Larry J.","Brown, Catherine A.","Garrison, James W.","Wolfle, Lee M."],"year":1987,"date_issued":"1987","date_published":"1987","updated_at":"2026-07-22T22:20:32Z","subjects":[],"languages":["en_US"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/64669","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Dodl, Norman R."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Burton, John K.","Weber, Larry J.","Brown, Catherine A.","Garrison, James W.","Wolfle, Lee M."]},{"key":"dc:contributor.department","label":"Department","values":["Curriculum and Instruction"]},{"key":"dc:creator","label":"Author","values":["McCoy, Leah Paulette"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2016-02-01T15:31:36Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2016-02-01T15:31:36Z"]},{"key":"dc:date.issued","label":"Date","values":["1987"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Polytechnic Institute and State University"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Curriculum and Instruction"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ed. 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Based on the similarities of these general skills in specific contexts, a theory was generated that the skills would transfer and that experience in computer programming would cause an improvement in mathematical problem-solving achievement. A path model was constructed to illustrate this hypothesized causal relationship between computer programming and mathematical problem-solving achievement. In order to control for other relevant variables, the model also included mathematics experience, access to a home computer, ability, socioeconomic status, and gender. The model was tested with a sample of 800 high school students in seven southwest Virginia high schools. Results indicated that ability had the largest causal effect on mathematical problem-solving achievement. Three variables had a moderate effect: computer programming experience, mathematics experience, and gender. The other two variables in the model (access to a home computer and socioeconomic status) were only very slightly related to mathematical problem-solving achievement. The conclusion of the study was that there was evidence to support the theory of transfer of skills from computer programming experience to mathematical problem-solving. Once ability and gender were controlled, computer programming experience and mathematics experience both had causal effects on mathematical problem-solving achievement. This suggests that to maximize mathematical problem-solving scores, a curriculum should include both mathematics and computer programming experiences."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ed. 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Based on the similarities of these general skills in specific contexts, a theory was generated that the skills would transfer and that experience in computer programming would cause an improvement in mathematical problem-solving achievement. A path model was constructed to illustrate this hypothesized causal relationship between computer programming and mathematical problem-solving achievement. In order to control for other relevant variables, the model also included mathematics experience, access to a home computer, ability, socioeconomic status, and gender. The model was tested with a sample of 800 high school students in seven southwest Virginia high schools. Results indicated that ability had the largest causal effect on mathematical problem-solving achievement. Three variables had a moderate effect: computer programming experience, mathematics experience, and gender. The other two variables in the model (access to a home computer and socioeconomic status) were only very slightly related to mathematical problem-solving achievement. The conclusion of the study was that there was evidence to support the theory of transfer of skills from computer programming experience to mathematical problem-solving. Once ability and gender were controlled, computer programming experience and mathematics experience both had causal effects on mathematical problem-solving achievement. This suggests that to maximize mathematical problem-solving scores, a curriculum should include both mathematics and computer programming experiences."],"dc:description.degree":["Ed. 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