首页> 外文期刊>Computer Science Education >Block-based versus text-based programming environments on novice student learning outcomes: a meta-analysis study
【24h】

Block-based versus text-based programming environments on novice student learning outcomes: a meta-analysis study

机译:基于块的与新手学生学习结果的基于文本的编程环境:Meta分析研究

获取原文
获取原文并翻译 | 示例
           

摘要

Background and Context: The use of block-based programming environments is purported to be a good way to gently introduce novice computer programmers to computer programming. A small, but growing body of research examines the differences between block-based and text-based programming environments. Objective: Thus, the purpose of this study was to examine the overall effect of block-based versus text-based programming environments on both cognitive and affective student learning outcomes. Method: Five academic databases were searched to identify literature meeting our inclusion criteria and resulted in 13 publications with 52 effect size comparisons on both cognitive and affective outcomes. Findings: We found small effect size (g = 0.245; p = .137; with a 95% confidence interval of -0.078 to 0.567) in favor of block-based programming environments on cognitive outcomes, and a trivial effect size (g = 0.195, p = .429; with a 95% confidence interval of -0.289 to 0.678) on affective outcomes. Both effect size calculations were statistically insignificant using random effects models. The effect sizes were examined for moderating effects by education level, learning environment, and study duration. Some evidence of publication bias was detected in these data. Implications: More research is needed to examine the utility and efficacy of block-based programming environments for novice programmers. Future studies should account for hybrid programming environments using novel research methods.
机译:背景和背景:基于块的编程环境的使用被声称为轻轻地将新手计算机程序员轻轻推出到计算机编程的好方法。一个小的,但越来越多的研究审查了基于块和基于文本的编程环境之间的差异。目的:因此,本研究的目的是研究基于块的基于文本的编程环境对认知和情感学生学习成果的总体影响。方法:搜索五个学术数据库,以识别满足我们纳入标准的文献,并导致13个出版物,对认知和情感结果进行了52个效果大小比较。结果:我们发现效果小(G = 0.245; P = .137;置信区间为-0.078至0.567),支持基于块的编程环境,对认知结果和琐碎的效果大小(g = 0.195 ,p = .429;在情感结果上,具有95%的置信区间-0.289至0.678)。两种效果大小计算使用随机效果模型统计上微不足道。通过教育水平,学习环境和研究持续时间检查效果大小以适度效果。在这些数据中检测到出版物偏差的一些证据。含义:需要更多的研究来检查基于块的编程环境对于新手程序员的实用性和功效。未来的研究应该考虑使用新型研究方法的混合编程环境。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号