Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website

Learnersourcing at Scale to Overcome Expert Blind Spots for Introductory Programming: A Three-Year Deployment Study on the Python Tutor Website
复制标题

大规模学习者资源以克服入门编程的专家盲点:Python 导师网站上为期三年的部署研究

DOI:
10.1145/3386527.3406733
复制
发表时间:
2020
期刊:
Learning at Scale
影响因子:
--
通讯作者:
Zhang, Xiong
Zhang, Xiong
中科院分区:
--
文献类型:
--
作者:
Guo, Philip J.;Markel, Julia M.;Zhang, Xiong

文献摘要

参考文献

被引文献

相似文献

专家很难创造出好的教学资源,这是由于一种被称为专家盲点的现象:他们忘记了新手是什么样的,所以他们不能准确地指出新手通常在哪里挣扎,以及如何最好地表达他们的解释。为了帮助克服计算机编程主题的这些专家盲点,我们创建了一个learnersourcing系统,可以在学习者编码时直接从他们那里解释误解。在过去的三年里,我们已经将这个系统部署到广泛使用的Python Tutor编码网站(pythontutor.com),并收集了16,791个学习者编写的解释。据我们所知,这是解释编程误解的最大数据集。通过检查这个数据集,我们发现了令人惊讶的见解,这是我们最初没有想到的,因为我们自己作为编程教师的专家盲点。我们现在正在使用这些见解来改进编译器和运行时错误消息,以解释常见的新手误解。
It is hard for experts to create good instructional resources due to a phenomenon known as the expert blind spot: They forget what it was like to be a novice, so they cannot pinpoint exactly where novices commonly struggle and how to best phrase their explanations. To help overcome these expert blind spots for computer programming topics, we created a learnersourcing system that elicits explanations of misconceptions directly from learners while they are coding. We have deployed this system for the past three years to the widely-used Python Tutor coding website (pythontutor.com) and collected 16,791 learner-written explanations. To our knowledge, this is the largest dataset of explanations for programming misconceptions. By inspecting this dataset, we found surprising insights that we did not originally think of due to our own expert blind spots as programming instructors. We are now using these insights to improve compiler and run-time error messages to explain common novice misconceptions.
DOI: --
发表时间: 2017
影响因子: 2.4
作者:
Yizhou Qian;James Lehman
通讯作者: James Lehman
学习者采购操作视频的子目标标签
DOI: 10.1145/2675133.2675219
发表时间: 2015
期刊: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing
影响因子: --
作者:
Sarah A. Weir;Juho Kim;Krzysztof Z Gajos;Rob Miller
通讯作者: Rob Miller