“它必须包含规则”

E. Wiese, M. Linn
{"title":"“它必须包含规则”","authors":"E. Wiese, M. Linn","doi":"10.1145/3415582","DOIUrl":null,"url":null,"abstract":"When middle school students encounter computer models of science phenomenon in science class, how do they think those computer models work? Computer models operationalize real-world behaviors of selected variables, and can simulate interactions between the modeled elements through programmed instructions. This study explores how middle school students think about the high-level semantic meaning of those instructions, which we term rules. To investigate this aspect of students’ computational thinking, we developed the Computational Modeling Inventory and administered it to 253 7th grade students. The Inventory included three computer models that students interacted with during the assessment. In our sample, 99% of students identified at least one key rule underlying a model, but only 14% identified all key rules; 65% believed that model rules can contradict; and 98% could not distinguish between emergent patterns and behaviors that directly resulted from model rules. Despite these misconceptions, compared to the “typical” questions about the science content alone, questions about model rules elicited deeper science thinking, with 2--10 times more responses including reasoning about scientific mechanisms. These results suggest that incorporating computational thinking instruction into middle school science courses might yield deeper learning and more precise assessments around scientific models.","PeriodicalId":322583,"journal":{"name":"ACM Transactions on Computer-Human Interaction (TOCHI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"“It Must Include Rules”\",\"authors\":\"E. Wiese, M. Linn\",\"doi\":\"10.1145/3415582\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When middle school students encounter computer models of science phenomenon in science class, how do they think those computer models work? Computer models operationalize real-world behaviors of selected variables, and can simulate interactions between the modeled elements through programmed instructions. This study explores how middle school students think about the high-level semantic meaning of those instructions, which we term rules. To investigate this aspect of students’ computational thinking, we developed the Computational Modeling Inventory and administered it to 253 7th grade students. The Inventory included three computer models that students interacted with during the assessment. In our sample, 99% of students identified at least one key rule underlying a model, but only 14% identified all key rules; 65% believed that model rules can contradict; and 98% could not distinguish between emergent patterns and behaviors that directly resulted from model rules. Despite these misconceptions, compared to the “typical” questions about the science content alone, questions about model rules elicited deeper science thinking, with 2--10 times more responses including reasoning about scientific mechanisms. These results suggest that incorporating computational thinking instruction into middle school science courses might yield deeper learning and more precise assessments around scientific models.\",\"PeriodicalId\":322583,\"journal\":{\"name\":\"ACM Transactions on Computer-Human Interaction (TOCHI)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Computer-Human Interaction (TOCHI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3415582\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Computer-Human Interaction (TOCHI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3415582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

当中学生在科学课上遇到科学现象的计算机模型时,他们认为这些计算机模型是如何工作的?计算机模型操作选定变量的现实世界行为,并可以通过编程指令模拟建模元素之间的相互作用。本研究探讨中学生如何思考这些指令的高级语义,我们称之为规则。为了研究这方面的学生计算思维,我们开发了计算建模量表,并对253名七年级学生进行了调查。该量表包括三个计算机模型,学生在评估过程中与之互动。在我们的样本中,99%的学生至少确定了一个模型的关键规则,但只有14%的学生确定了所有关键规则;65%的人认为示范规则可能相互矛盾;98%的人不能区分紧急模式和直接由模型规则引起的行为。尽管存在这些误解,但与仅关于科学内容的“典型”问题相比,关于模型规则的问题引发了更深层次的科学思考,包括对科学机制的推理在内的回答多出2- 10倍。这些结果表明,将计算思维教学纳入中学科学课程可能会产生更深层次的学习,并围绕科学模型进行更精确的评估。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
“It Must Include Rules”
When middle school students encounter computer models of science phenomenon in science class, how do they think those computer models work? Computer models operationalize real-world behaviors of selected variables, and can simulate interactions between the modeled elements through programmed instructions. This study explores how middle school students think about the high-level semantic meaning of those instructions, which we term rules. To investigate this aspect of students’ computational thinking, we developed the Computational Modeling Inventory and administered it to 253 7th grade students. The Inventory included three computer models that students interacted with during the assessment. In our sample, 99% of students identified at least one key rule underlying a model, but only 14% identified all key rules; 65% believed that model rules can contradict; and 98% could not distinguish between emergent patterns and behaviors that directly resulted from model rules. Despite these misconceptions, compared to the “typical” questions about the science content alone, questions about model rules elicited deeper science thinking, with 2--10 times more responses including reasoning about scientific mechanisms. These results suggest that incorporating computational thinking instruction into middle school science courses might yield deeper learning and more precise assessments around scientific models.
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
自引率
0.00%
发文量
0
期刊最新文献
Designing PairBuddy—A Conversational Agent for Pair Programming Iteratively Designing Gesture Vocabularies: A Survey and Analysis of Best Practices in the HCI Literature Understanding HCI Practices and Challenges of Experiment Reporting with Brain Signals: Towards Reproducibility and Reuse Understanding, Addressing, and Analysing Digital Eye Strain in Virtual Reality Head-Mounted Displays It’s Complicated: The Relationship between User Trust, Model Accuracy and Explanations in AI
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1