Exploring Second-Chance Testing as a Practical Form of Mastery Learning

探索第二次机会测试作为掌握学习的实用形式

• 批准号: 1915257
• 负责人: Craig Zilles
• 金额: $ 60万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1915257&HistoricalAwards=false
• 关键词: Exploring; Second; Chance; Testing; Practical

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by investigating how second-chance testing improves student learning and retention. The significance of this work is rooted in the observation that some students fail courses, even though they have to ability to succeed and willingness to work. These students often fail because they overestimate the adequacy of their preparation for an exam or misunderstand course expectations. This failure can prevent these qualified students from persisting in STEM majors and joining the STEM workforce. Second-chance testing is the practice of allowing students to take an exam and then giving them feedback on their performance. They are then allowed to further study the material and then take a second, equivalent exam for some form of grade replacement. Preliminary data show that second-chance testing improves average exam scores and reduces exam failure rates. This project will investigate best practices with respect to second-chance testing and characterize its benefits. The project will also study whether second-chance testing disproportionately helps students who are traditionally under-served by existing course structures. It will also study what can be done to help instructors adopt this practice.Second-chance testing can be a powerful technique because it exploits both the "testing effect" (increased long-term memory resulting from deliberate retrieval practice) and "test-potentiated learning" (increased ability of a learner to benefit from an opportunity to restudy a concept). In addition, it offers the potential to mitigate students' failures on exams due to their inability to correctly assess course expectations and their level of readiness. Preliminary data at the University of Illinois on second-chance testing has shown improvements in student performance measured by mean exam scores and a reduction in exam failure rates. In addition, this data showed that variations in the grading policy can exert considerable influence on which students choose to take the second chance exam. The goals of this project are to more rigorously measure the benefits of second-chance testing, map out the scope of grading policies and their impacts, and better understand the factors involved in faculty adoption of second-chance testing. The project will focus on three research questions. First, how much does second-chance testing improve students' cognitive and non-cognitive outcomes? Second, how do second-chance grading policies affect students' cognitive and non-cognitive outcomes on first-chance and subsequent second-chance exams? Third, does second-chance testing disproportionately help students who are traditionally under-served by single opportunity exam structures? 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.

在 NSF 改善本科生 STEM 教育计划：教育和人力资源（IUSE：EHR）的支持下，该项目旨在通过调查第二次机会测试如何提高学生的学习和保留率来服务于国家利益。这项工作的意义在于观察到一些学生未能通过课程，尽管他们有能力取得成功并愿意工作。这些学生经常会失败，因为他们高估了自己考试准备的充分性或误解了课程期望。这种失败可能会阻止这些合格的学生坚持 STEM 专业并加入 STEM 劳动力队伍。第二次机会测试是允许学生参加考试然后向他们提供表现反馈的做法。然后他们可以进一步学习这些材料，然后参加第二次同等考试以进行某种形式的成绩替换。初步数据显示，第二次机会测试可以提高平均考试成绩并降低考试失败率。该项目将研究有关二次机会测试的最佳实践并描述其好处。该项目还将研究二次机会测试是否对传统上现有课程结构服务不足的学生提供了不成比例的帮助。它还将研究可以采取哪些措施来帮助教师采用这种做法。第二次机会测试可以是一种强大的技术，因为它同时利用了“测试效果”（通过刻意检索练习而增加的长期记忆）和“测试增强”学习”（提高学习者从重新学习概念的机会中受益的能力）。此外，它还可以减少学生因无法正确评估课程期望和准备水平而导致考试失败的情况。伊利诺伊大学关于第二次机会测试的初步数据显示，通过平均考试成绩衡量的学生成绩有所提高，考试失败率有所下降。此外，这些数据表明，评分政策的变化会对学生选择参加第二次机会考试产生相当大的影响。该项目的目标是更严格地衡量二次机会测试的好处，制定评分政策的范围及其影响，并更好地了解教师采用二次机会测试所涉及的因素。该项目将重点关注三个研究问题。首先，第二次机会测试对学生的认知和非认知结果有多大改善？其次，第二次机会评分政策如何影响学生在第一次和随后的第二次机会考试中的认知和非认知结果？第三，第二次机会考试是否对传统上单一机会考试结构服务不足的学生提供了不成比例的帮助？ 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 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。

项目成果

Learning to Cheat: Quantifying Changes in Score Advantage of Unproctored Assessments Over Time

学习作弊：量化无人监考评估的分数优势随时间的变化

• DOI: 10.1145/3386527.3405925
• 发表时间: 2020-08
• 期刊: Proceedings of the Seventh ACM Conference on Learning @ Scale
• 作者: Chen, Binglin;Azad, Sushmita;Fowler, Ma;West, Matthew;Zilles, Craig
• 通讯作者: Zilles, Craig

Investigating the Effects of Testing Frequency on Programming Performance and Students' Behavior

研究测试频率对编程表现和学生行为的影响

• DOI: 10.1145/3545945.3569821
• 发表时间: 2023-03
• 期刊: SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education
• 作者: Smith, David H.;Emeka, Chinedu;Fowler, Ma;West, Matthew;Zilles, Craig
• 通讯作者: Zilles, Craig

Student Perceptions of Fairness and Security in a Versioned Programming Exam

学生对版本化编程考试中公平性和安全性的看法

• DOI: 10.1145/3372782.3406275
• 发表时间: 2020-08
• 期刊: Proceedings of the 2020 ACM Conference on International Computing Education Research
• 作者: Emeka, Chinedu;Zilles, Craig
• 通讯作者: Zilles, Craig

Comparison of Grade Replacement and Weighted Averages for Second-Chance Exams

第二次机会考试的成绩替换和加权平均数比较

• DOI: 10.1145/3372782.3406260
• 发表时间: 2020-08
• 期刊: Proceedings of the 2020 ACM Conference on International Computing Education Research
• 作者: Herman, Geoffrey L.;Cai, Zhouxiang;Bretl, Timothy;Zilles, Craig;West, Matthew
• 通讯作者: West, Matthew

Strategies for Deploying Unreliable AI Graders in High-Transparency High-Stakes Exams

在高透明度、高风险的考试中部署不可靠的人工智能评分者的策略

• DOI: 10.1007/978-3-030-52237-7_2
• 发表时间: 2020-06-09
• 期刊: Artificial Intelligence in Education
• 作者: Azad S;Chen B;Fowler M;West M;Zilles C
• 通讯作者: Zilles C