Understanding and Enhancing Self Regulated Learning in Introductory Computer Science Courses

在NSF改进本科STEM教育计划：教育和人力资源（IUSE：EHR）的支持下，该项目旨在为高质量计算机科学教育的国家利益服务。 考虑到计算机相关教育课程的急剧增长，提高学生在计算机科学入门课程中的学习成果非常重要。自我调节学习可能是实现这一目标的关键。 自我调节学习包括学习者设定自己的学习目标、监控自己的学习以及根据需要调整学习策略的能力。 研究表明，许多计算机科学专业的学生自我调节学习能力差。 因此，他们会做出一些干扰学习的行为，比如拖延和跳过内容。 本项目旨在帮助计算机科学教育工作者和研究人员了解和提高学生的自主学习能力。该项目将研究学生越来越多地使用自我调节学习策略与他们在计算机科学入门课程中的表现之间的关系。 预计培养自我调节学习技能的学生将在计算机科学入门课程中更成功，并坚持进入计算机科学专业和职业生涯。 因此，该项目有可能更广泛地参与计算机科学领域。该项目将侧重于在两种活动的交叉点出现的自我调节学习：在编程过程中审查概念材料和通过编写程序尝试想法。概念材料，在线教科书和编程集成开发环境，从一个介绍计算机科学课程将仪器记录所有学生的互动。 例如，它将记录学生何时完成交互式练习，或者学生在完成编程问题时如何参考文本。收集的数据将用于更好地了解自我调节学习，通过建模使用个别材料和不同材料的使用模式。该项目还将研究这些行为如何映射到学生的自我调节学习的发展，以及自我效能和信心，以及这些结构如何预测整个课程的计算机科学知识和技能的发展。它还将研究自我调节学习，信心，元认知，编程技能和计算机科学概念知识的发展如何与学生对计算机科学的长期兴趣相关联。在这样做时，该项目将试图了解导致计算机科学更大成功和保留在计算机科学管道的因素，并发展有关自我调节学习发展的理论知识。NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest in high-quality computer science education. Given the dramatic growth in computing-related educational programs, it is important to improve student learning outcomes in introductory computer science courses. Self-regulated learning may be a key to achieving this goal. Self-regulated learning includes the abilities of learners to set their own goals, monitor the own learning, and adjust learning strategies as needed. Research studies show that many computer science students have poor self-regulated learning abilities. As a result, they engage in behaviors that interfere with learning, such as procrastination and skipping content. This project seeks to help computer science educators and researchers understand and enhance students' self-regulated learning abilities. The project will examine the relationship between students' increased use of self-regulated learning strategies and their performance in introductory computer science courses. It is expected that students who develop skills in self-regulated learning will be more successful in introductory computer science courses and persist into computer science majors and careers. The project thus has the potential to broader participation within computer science fields.This project will focus on the self-regulated learning that emerges at the intersection of two types of activities: reviewing conceptual materials during programming and trying out ideas through writing programs. The conceptual materials, online textbook, and programming Integrated Development Environment from an introductory computer science course will be instrumented to record all student interactions. For example, it will record when a student completes interactive exercises or how a student refers to the text when completing a programming problem. The collected data will be used to better understand self-regulated learning by modeling patterns of use of individual materials and patterns of use across the different materials. The project will also examine how these behaviors map to students' development of self-regulated learning, as well as self-efficacy and confidence, and how each of these constructs predicts the development of computer science knowledge and skills across the course. It will also study how the developments in self-regulated learning, confidence, metacognition, programming skills, and computer science conceptual knowledge are associated with students' longer-term interest in computer science. In doing so, the project will attempt both to understand the factors that lead to greater success in computer science and retention in the computer science pipeline, and to develop theoretical knowledge about the development of self-regulated learning. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.