EXP: Understanding Computational Thinking Process and Practices in Open-Ended Programming Environments

网络学习和未来学习技术计划资助的努力将有助于展望下一代学习技术，并促进我们对人们在技术丰富的环境中如何学习的了解。网络学习探索(EXP)项目通过设计和构建新的学习技术，并研究它们促进学习的可能性和有效使用它们的挑战，来探索新类型的学习技术的可行性。该项目结合了两种方法来帮助K-12学生学习编程和计算机科学：开放式学习环境和基于计算机的学习分析，以帮助创造一种环境，在这种环境中，年轻人可以获得帮助和支架，以适应他们对编程的了解，而不必参加考试或参加僵化的教科书练习，以便系统了解他们所知道的。该项目建议使用教育数据挖掘和学习分析的技术来处理Alice编程环境中的学生数据。在循证设计评价设计模型的基础上，结合NGSS和计算思维评价研究等新兴标准，利用学生日志数据构建学生个体计算思维实践模型。最初，该系统将基于现有的约600名学生的结对编程日志数据语料库，通过游戏设计练习与手动编码的编程成绩评估进行三角测量。在第二阶段的工作中，将创建课程和专业发展，以使该系统能够在斯坦福大学CS暑期研讨会上与代表性不足的女孩进行测试，并让来自不同高中的学生实施探索计算机科学课程。采用直接观察法和访谈法对模型进行改进。研究将解决学习者如何在构建计算人工制品中实施计算思维实践，什么行为模式作为学习CT实践的证据，以及如何更好地设计建构主义编程环境，以便提供个性化的学习者脚手架。通过与流行的编程环境(Alice)和广泛使用的计算机科学课程(探索计算机科学)保持一致，该项目可以对计算机科学教育产生广泛的影响；开发的软件将在BSD样式的许可下发布，以便其他人可以在此基础上进行构建。

The Cyberlearning and Future Learning Technologies Program funds efforts that will help envision the next generation of learning technologies and advance what we know about how people learn in technology-rich environments. Cyberlearning Exploration (EXP) Projects explore the viability of new kinds of learning technologies by designing and building new kinds of learning technologies and studying their possibilities for fostering learning and challenges to using them effectively. This project brings together two approaches to help K-12 students learn programming and computer science: open-ended learning environments, and computer-based learning analytics, to help create a setting where youth can get help and scaffolding tailored to what they know about programming without having to take tests or participate in rigid textbook exercises for the system to know what they know. The project proposes to use techniques from educational data mining and learning analytics to process student data in the Alice programming environment. Building on the assessment design model of Evidence-Centered Design, student log data will be used to construct a model of individual students' computational thinking practices, aligned with emerging standards including NGSS and research on assessment of computational thinking. Initially, the system will be developed based on an existing corpus of pair-programming log data from approximately 600 students, triangulating with manually-coded performance assessments of programming through game design exercises. In the second phase of the work, curricula and professional development will be created to allow the system to be tested with underrepresented girls at Stanford's CS summer workshops and with students from diverse high schools implementing the Exploring Computer Science curriculum. Direct observation and interviews will be used to improve the model. Research will address how learners enact computational thinking practices in building computational artifacts, what patters of behavior serve as evidence of learning CT practices, and how to better design constructionist programming environments so that personalized learner scaffolding can be provided. By aligning with a popular programming environment (Alice) and a widely-used computer science curriculum (Exploring Computer Science), the project can have broad impact on computer science education; software developed will be released under a BSD-style license so others can build on it.