{"title":"基于抽象的计算思维编程方法:发现、提取、创建和组装","authors":"Ndudi O. Ezeamuzie","doi":"10.1177/07356331221134423","DOIUrl":null,"url":null,"abstract":"Most studies suggest that students develop computational thinking (CT) through learning programming. However, when the target of CT is decoupled from programming, emerging evidence challenges the assertion of CT transferability from programming. In this study, CT was operationalized in everyday problem-solving contexts in a learning experiment (n = 59) that investigated whether learning programming enhances students’ CT skills. Specifically, this study examined the influence of a novel, systematic and micro instructional strategy that is grounded in abstraction and comprised of four independent but related processes – discover, extract, create, and assemble (DECA) towards simplification of problem-solving. Subsidiary questions explored the effects of students’ age, gender, computer proficiency, and prior programming experience on the development of CT. No significant difference was found between the CT skill and programming knowledge of the groups at the posttest. However, within-group paired t-tests showed that the experimental group that integrated DECA had significant improvement in CT but not in the control group across the pretest-posttest axis. Implications of the inconclusive finding about the transfer of programming skills to CT are emphasized and the arguments for disentangling CT from programming are highlighted.","PeriodicalId":47865,"journal":{"name":"Journal of Educational Computing Research","volume":"61 1","pages":"605 - 638"},"PeriodicalIF":4.0000,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Abstractive-Based Programming Approach to Computational Thinking: Discover, Extract, Create, and Assemble\",\"authors\":\"Ndudi O. Ezeamuzie\",\"doi\":\"10.1177/07356331221134423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most studies suggest that students develop computational thinking (CT) through learning programming. However, when the target of CT is decoupled from programming, emerging evidence challenges the assertion of CT transferability from programming. In this study, CT was operationalized in everyday problem-solving contexts in a learning experiment (n = 59) that investigated whether learning programming enhances students’ CT skills. Specifically, this study examined the influence of a novel, systematic and micro instructional strategy that is grounded in abstraction and comprised of four independent but related processes – discover, extract, create, and assemble (DECA) towards simplification of problem-solving. Subsidiary questions explored the effects of students’ age, gender, computer proficiency, and prior programming experience on the development of CT. No significant difference was found between the CT skill and programming knowledge of the groups at the posttest. However, within-group paired t-tests showed that the experimental group that integrated DECA had significant improvement in CT but not in the control group across the pretest-posttest axis. Implications of the inconclusive finding about the transfer of programming skills to CT are emphasized and the arguments for disentangling CT from programming are highlighted.\",\"PeriodicalId\":47865,\"journal\":{\"name\":\"Journal of Educational Computing Research\",\"volume\":\"61 1\",\"pages\":\"605 - 638\"},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2022-10-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Educational Computing Research\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://doi.org/10.1177/07356331221134423\",\"RegionNum\":2,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Educational Computing Research","FirstCategoryId":"95","ListUrlMain":"https://doi.org/10.1177/07356331221134423","RegionNum":2,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Abstractive-Based Programming Approach to Computational Thinking: Discover, Extract, Create, and Assemble
Most studies suggest that students develop computational thinking (CT) through learning programming. However, when the target of CT is decoupled from programming, emerging evidence challenges the assertion of CT transferability from programming. In this study, CT was operationalized in everyday problem-solving contexts in a learning experiment (n = 59) that investigated whether learning programming enhances students’ CT skills. Specifically, this study examined the influence of a novel, systematic and micro instructional strategy that is grounded in abstraction and comprised of four independent but related processes – discover, extract, create, and assemble (DECA) towards simplification of problem-solving. Subsidiary questions explored the effects of students’ age, gender, computer proficiency, and prior programming experience on the development of CT. No significant difference was found between the CT skill and programming knowledge of the groups at the posttest. However, within-group paired t-tests showed that the experimental group that integrated DECA had significant improvement in CT but not in the control group across the pretest-posttest axis. Implications of the inconclusive finding about the transfer of programming skills to CT are emphasized and the arguments for disentangling CT from programming are highlighted.
期刊介绍:
The goal of this Journal is to provide an international scholarly publication forum for peer-reviewed interdisciplinary research into the applications, effects, and implications of computer-based education. The Journal features articles useful for practitioners and theorists alike. The terms "education" and "computing" are viewed broadly. “Education” refers to the use of computer-based technologies at all levels of the formal education system, business and industry, home-schooling, lifelong learning, and unintentional learning environments. “Computing” refers to all forms of computer applications and innovations - both hardware and software. For example, this could range from mobile and ubiquitous computing to immersive 3D simulations and games to computing-enhanced virtual learning environments.