Identifying and Extracting Meaningful Indicators of Children's Moment-to-Moment Programming Processes in Scratch

该项目旨在通过制定和验证学生编程过程的指标，服务于STEM和计算思维方面的国家利益。建议的探索性研究将开发一个Scratch数据记录模块，以收集学生的即时编程行为。项目组将制定数据处理规则或算法，以得出方案编制过程的指标(例如调试)。该项目将促进对学生使用什么编程过程的理解，这些过程是如何随着时间的推移而展开的，以及这些过程如何与编程和计算思维的措施相关联。数据记录模块和算法将分发给临时社区，以便能够大规模研究方案编制过程。这项研究还将产生一种系统的和可复制的方法论，以加速算法的开发和用于研究编程过程的工具、技术和方法的广泛传播。研究将观察五年级和本科生从零开始学习编程。学生的过程数据将被用来得出编程过程的指标。这些指标将在不同年龄段之间、每个年龄段内随时间推移进行比较，并与现有的方案编制概念和技能的外部衡量标准进行比较。这项研究将对学生表现出什么、如何以及潜在的原因产生深刻的见解。得出方案编制过程指标的能力将补充静态临时代码评分的现有方法。算法开发将侧重于理论驱动的、基于规则的、可直接解释的方案编制进程指标，以及使算法开发进程系统化和加速的方法。算法开发方法将适用于其他基于块的环境和应用程序，涉及过程数据，如游戏、模拟和教育评估中的创新项目类型。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest in STEM and computational thinking by developing and validating indicators of students' programming processes. The proposed exploratory research will develop a data logging module for Scratch to collect students' moment-to-moment programming behavior. The project team will develop data processing rules or algorithms to derive indicators of programming processes (e.g., debugging). The project will advance the understanding of what programming processes students use, how these processes unfold over time, and how these processes relate to measures of programming and computational thinking. The data logging module and algorithms will be distributed to the Scratch community to allow the study of programming processes at scale. The research will also produce a systematic and replicable methodology to accelerate the development of algorithms and widespread dissemination of the tools, techniques, and methods used to study programming processes.The research will observe novice fifth grade and undergraduate students learning to program in Scratch. Students' process data will be used to derive indicators of programming processes. The indicators will be compared between age groups, within each age group over time, and to existing external measures of programming concepts and skills. This research will generate insights about what, how, and potentially why students perform the way they do. The capability to derive indicators of programming processes will complement existing methods of scoring static Scratch code. Algorithm development will focus on theoretically-driven, rule-based indicators of programming processes that are directly interpretable and on methods that systematize and accelerate the algorithm development process. The algorithm development methodology will apply to other block-based environments and applications involving process data such as games, simulations, and innovative item types in educational assessment.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.