面向编程任务复杂性的细粒度分析

Proceedings of the 2017 ACM Conference on International Computing Education Research Pub Date : 2017-08-14 DOI:10.1145/3105726.3105731

Rodrigo Duran

{"title":"面向编程任务复杂性的细粒度分析","authors":"Rodrigo Duran","doi":"10.1145/3105726.3105731","DOIUrl":null,"url":null,"abstract":"Bloom's and SOLO taxonomies have been used to describe the complexity of computer science tasks and student's outcome. However, using these taxonomies have coarse granularity and programming tasks with very different demands could be equally classified at the same level. My research proposes a new framework using Neo-Piagetian stages of development based on the Model of Hierarchical Complexity (MHC) that enable formal definition and fine-grained evaluation of programming tasks nuances in paradigms, languages, and constructs. By empirically validating the model, I expect it to be a valuable tool to provide best practices to develop pedagogical approaches and tools.","PeriodicalId":267640,"journal":{"name":"Proceedings of the 2017 ACM Conference on International Computing Education Research","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards a Fine-grained Analysis of Complexity of Programming Tasks\",\"authors\":\"Rodrigo Duran\",\"doi\":\"10.1145/3105726.3105731\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bloom's and SOLO taxonomies have been used to describe the complexity of computer science tasks and student's outcome. However, using these taxonomies have coarse granularity and programming tasks with very different demands could be equally classified at the same level. My research proposes a new framework using Neo-Piagetian stages of development based on the Model of Hierarchical Complexity (MHC) that enable formal definition and fine-grained evaluation of programming tasks nuances in paradigms, languages, and constructs. By empirically validating the model, I expect it to be a valuable tool to provide best practices to develop pedagogical approaches and tools.\",\"PeriodicalId\":267640,\"journal\":{\"name\":\"Proceedings of the 2017 ACM Conference on International Computing Education Research\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM Conference on International Computing Education Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3105726.3105731\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM Conference on International Computing Education Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3105726.3105731","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

Bloom和SOLO分类法被用来描述计算机科学任务的复杂性和学生的成果。然而，使用这些分类法具有粗粒度，并且具有非常不同需求的编程任务可以在同一级别上进行相同的分类。我的研究提出了一个基于分层复杂性模型(MHC)的新皮亚吉发展阶段的新框架，该框架能够对范式、语言和结构中的编程任务细微差别进行正式定义和细粒度评估。通过对模型的经验验证，我希望它能成为一个有价值的工具，为开发教学方法和工具提供最佳实践。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Towards a Fine-grained Analysis of Complexity of Programming Tasks

Bloom's and SOLO taxonomies have been used to describe the complexity of computer science tasks and student's outcome. However, using these taxonomies have coarse granularity and programming tasks with very different demands could be equally classified at the same level. My research proposes a new framework using Neo-Piagetian stages of development based on the Model of Hierarchical Complexity (MHC) that enable formal definition and fine-grained evaluation of programming tasks nuances in paradigms, languages, and constructs. By empirically validating the model, I expect it to be a valuable tool to provide best practices to develop pedagogical approaches and tools.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of the 2017 ACM Conference on International Computing Education Research

自引率

0.00%

发文量