An Online Tool to Support Productive Struggles and Improve the Self-Efficacy of Undergraduate Students in Introductory Computer Science Courses.

该项目旨在通过开发一个在线平台来服务于国家利益，该平台将有助于提高计算机入门课程的保留率。美国劳工统计局预测，未来几年对计算工作的需求将继续增长。然而，预计的计算机科学毕业生人数并不能满足预测的需求。其中一个原因是计算机专业的高辍学率。计算机科学学位与发展技术技能有关，这些技能可以在学生解决涉及挑战性任务的问题时教授。解决这些具有挑战性的任务有助于学生学习，但往往导致与材料的斗争。虽然这种挣扎通常与自我效能感下降有关，但这些挣扎可以成为促进学习和自我效能感的工具，从而成为富有成效的挣扎。将课堂挑战转化为富有成效的斗争作为学习手段可能有助于提高计算机科学入门课程的保留率。这个名为PULSE（Productive Struggle for DeveLoping Self Efficacy）的在线平台旨在促进富有成效的斗争，提高自我效能，并加强技能发展。PULSE将在课堂外使用长格式的计算机编程作业。该平台将使用机器学习驱动的方法来识别学生在解决编程任务时面临的障碍。这将使教师能够在学生挣扎时进行干预，让学生从挣扎中学习，并在提交截止日期前改进他们的工作。该项目应该通过产生关于学生在课堂外解决编码问题的斗争和编程活动模式的新知识来推进计算机科学教育。拟议研究的见解可能会提供降低大学计算机入门课程学生辍学率的方法。PULSE将作为开源软件发布，允许其他机构在其编程课程中部署它。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。通过“学生参与学习”轨道，该计划支持创建、探索和实施有前途的实践和工具。该项目还得到了NSF IUSE：HSI项目的支持，该项目的目标是提高本科STEM教育的质量，并提高攻读STEM副学士或学士学位学生的录取率、保留率和毕业率。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值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 by developing an online platform that will help to improve retention in introductory computing courses. The US Bureau of Labor Statistics predicts that the demand for computing jobs will continue to grow in the coming years. However, the projected number of computer science graduates does not meet the predicted demand. One of the reasons for this is the high dropout rates of computing majors. A computer science degree is tied to developing technical skills, which may be taught while students solve problems involving challenging tasks. Solving such challenging tasks helps students to learn but often results in struggles with the material. While such struggles are usually linked with diminishing self-efficacy, these struggles can become instruments to promote learning and self-efficacy, thus becoming productive struggles. Converting classroom challenges to productive struggles as a means for learning may help to improve retention in introductory computer science classes. The online platform, called PULSE (Productive strUggle for deveLoping Self Efficacy), is intended to foster productive struggles, improve self-efficacy, and enhance skill development. PULSE will make use of long-form computer programming assignments outside the classroom. The platform will use machine learning-driven approaches to identify the obstacles students face while solving a programming assignment. This will enable instructors to intervene when students struggle, allowing students to learn from the struggles and improve their work before the submission deadline. The project should advance computer science education by generating new knowledge about student struggles and programming activity patterns in solving coding problems outside the classroom. The insights of the proposed research may provide ways to reduce student dropout rates in introductory computing classes in college. PULSE will be released as open-source software allowing other institutions to deploy it in their programming courses. 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 project is also supported by the NSF IUSE:HSI program, which has the goals of enhancing the quality of undergraduate STEM education, and increasing the recruitment, retention, and graduation rates of students pursuing associate’s or baccalaureate degrees in STEM.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.