Improving Teaching and Learning in Computer Science Using Structured Post-Exam Interviews and Remediation
Improving Teaching and Learning in Computer Science Using Structured Post-Exam Interviews and Remediation
批准号:
2141772
负责人:
Pablo Frank Bolton
金额:
$14.91万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-01 至 2025-06-30
中文摘要
该项目旨在通过使用两阶段的考试过程来确定学生的知识差距并改善学生在计算机科学方面的学习,从而为国家利益服务。对于教育工作者来说,考试是可靠和方便的评估工具,然而,考试也会引起学生的焦虑。考试往往是一次性事件,没有激励学生纠正任何学习缺陷。对学生考试答案的及时反馈可以帮助学生发现知识差距。本项目将为计算机编程入门课程开发和评估一个两阶段的考试过程。学生将参加多项选择考试,他们将为每个选择的答案提供理由。对于有明显知识差距的学生,将进行面试,为学生提供第二次机会来展示他们的理解。面试结束后,将为每位学生提供一份行动计划,以帮助他们实现学习成果。预计该项目将有助于提高学生在基础计算机科学课程中的学习成果,这将有助于学生为计算机工作的专业实践做好准备。该项目的目标是:(1)提高学生的学习成果,(2)减少考试焦虑,(3)支持学术诚信。这个项目建立在以前物理教育界关于两阶段考试的工作的基础上。在第一阶段,改进的多项选择评估将用于识别学生的知识差距。第二阶段包括一对一的面试,重点是与第一阶段确定的知识差距相关的问题。然后,教师将为每个学生制定个性化的学习计划。研究问题包括:(1)与标准选择题相比,改进后的选择题考试将提供哪些额外的见解?2)面试阶段在多大程度上有助于提高学生的学习成果?为了回答这些问题,测试结果将使用传统的和改进的选择题考试进行比较。学生的学习成果将在有或没有面试阶段进行评估。建议项目的结果将在计算机科学教育会议和一个由计算机协会教育委员会举办的计算机教育社区网站上公布。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。通过参与学生学习轨道,该计划支持有前途的实践和工具的创建,探索和实施。该奖项反映了美国国家科学基金会的法定使命,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。
英文摘要
This project aims to serve the national interest by using a two-stage exam process to identify students’ knowledge gaps and improve student learning in computer science. Exams are dependable and convenient assessment tools for educators, however, they can cause student anxiety. Exams are often one-shot events resulting in no incentive for students to correct any learning deficiencies. Timely feedback on student exam answers can help students identify knowledge gaps. This project will develop and assess a two-stage exam process for an introductory computer programming course. Students will take a multiple choice exam in which they will provide a justification for each selected answer. For students who have significant knowledge gaps, an interview will follow, providing a second opportunity for students to demonstrate their understanding. After the interview, a plan of action will be provided for each student to help them achieve the learning outcomes. It is expected that the project will help improve student learning outcomes in a foundational computer science course, which will help prepare students for professional practice in the computing workforce.The goals of this project are to: (1) improve student learning outcomes, (2) reduce test anxiety, and (3) support academic integrity. This project builds on previous work on two-stage exams in the physics education community. In the first stage, an improved multiple-choice assessment will be used to identify student knowledge gaps. The second stage consists of a one-on-one interview which will focus on questions related to the knowledge gaps identified in the first stage. Instructors will then develop a plan of study that will be personalized for each student. Research questions include: (1) What additional insights will the improved multiple-choice exam provide over a standard multiple-choice exam? 2) To what extent does the interview stage help to improve students’ learning outcomes? To answer these questions, test results will be compared using traditional versus the improved multiple choice exam. Student learning gains will be assessed with and without the interview stage. The results of the proposed project will be disseminated at computer science education conferences and one computing education community site organized by Association for Computing Machinery education board. 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.
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