Developing Open Response Assessments to Evaluate How Undergraduates Engage in Mathematical Sensemaking in Biology, Chemistry, and Physics
开发开放式反应评估来评估本科生如何参与生物学、化学和物理领域的数学意义建构
基本信息
- 批准号:2235487
- 负责人:
- 金额:$ 69.99万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-03-15 至 2027-02-28
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
This project aims to serve the national interest by developing new tools to assess how students engage in making sense of quantitative problems in biology, chemistry, and physics. Mathematical sensemaking in science focuses on students’ ability to blend core disciplinary science ideas with cross-cutting mathematical concepts, such as patterns and proportions, while engaging in scientific practices such as computational thinking, making predictions, and reasoning from evidence. Current visions for undergraduate STEM education stress the need to integrate i) key disciplinary ideas and ii) crosscutting concepts with iii) authentic scientific practices, resulting in what is called three-dimensional learning. This requires developing new assessments with the ability to detect when students engage in three-dimensional learning and reveal this to instructors. This project seeks to extend previous work to identify opportunities to observe mathematical sensemaking in science in the classroom. The project plans to develop open-ended questions to explore undergraduate mathematical sensemaking in science using three dimensional learning assessments. This serves the goal of improving STEM education at the undergraduate level by providing engaging and authentic assessments capable of revealing student thinking. Findings from this project should help inform teaching practice in undergraduate STEM courses and help students foster computational thinking skills. The project will target two aims. Aim 1 is to apply an evidence-centered design process to develop open-ended assessment items that elicit mathematical sensemaking in science (MaSS) and align with a three-dimensional learning (3DL) assessment framework. The evidence-centered design approach for the assessments will provide an opportunity to collect validity evidence throughout the process and allow development of similar items across disciplines. Assessment tasks and coding rubrics will be based on frameworks for 3DL and MaSS, and will be iteratively revised to elicit and categorize student MaSS. The project will conduct interviews with undergraduates to examine their MaSS while completing the assessment items, and with college faculty to ensure alignment with disciplinary topics and phenomena common in college courses. Aim 2 is to administer constructed response items across undergraduate science disciplines to explore how undergraduates engage in MaSS across biology, chemistry, and physics. The project will administer the assessment items from Aim 1 at a diverse set of undergraduate institutions to collect student responses. These responses will be used to establish evidence of the validity, reliability, and fairness of the items quantitatively. Further, the responses will be used to explore how undergraduates engage in MaSS in varied science disciplines. The project meets the need for developing rich, formative assessment items for undergraduate 3DL that reveal student thinking, which is essential for instruction aimed to foster MaSS. The project will also advance understanding of how undergraduates integrate thinking about key STEM concepts and mathematics across disciplines by following a 3DL assessment framework. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its 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.
该项目旨在通过开发新的工具来评估学生如何理解生物学,化学和物理学中的定量问题来服务于国家利益。科学中的数学意义建构侧重于学生将核心学科科学思想与交叉数学概念(如模式和比例)相结合的能力,同时参与科学实践,如计算思维,预测和证据推理。 目前本科STEM教育的愿景强调需要整合i)关键学科思想和ii)跨学科概念与iii)真实的科学实践,从而实现所谓的三维学习。这就需要开发新的评估方法,能够检测学生何时进行三维学习,并将其透露给教师。该项目旨在扩展以前的工作,以确定在课堂上观察科学中的数学意义建构的机会。 该项目计划开发开放式问题,探索本科生的数学意义建构科学使用三维学习评估。这有助于通过提供能够揭示学生思维的引人入胜和真实的评估来改善本科阶段的STEM教育。该项目的研究结果应有助于为本科STEM课程的教学实践提供信息,并帮助学生培养计算思维能力。该项目有两个目标。目的1是应用以证据为中心的设计过程,开发开放式的评估项目,引起数学在科学(MaSS)和三维学习(3DL)的评估框架。以证据为中心的评估设计方法将提供一个机会,在整个过程中收集有效性证据,并允许跨学科开发类似的项目。评估任务和编码规则将基于3DL和MaSS的框架,并将反复修订以引出学生MaSS并对其进行分类。该项目将与本科生进行访谈,在完成评估项目的同时检查他们的MaSS,并与大学教师进行访谈,以确保与大学课程中常见的学科主题和现象保持一致。目标2是管理跨本科科学学科的构建响应项目,以探索本科生如何在生物学,化学和物理学上参与MaSS。该项目将在不同的本科院校管理目标1的评估项目,以收集学生的反应。这些回答将用于定量地建立项目的有效性、可靠性和公平性的证据。此外,这些回答将用于探讨本科生如何在不同的科学学科中参与MaSS。该项目满足了为本科生3DL开发丰富的形成性评估项目的需求,这些项目揭示了学生的思维,这对于旨在培养MaSS的教学至关重要。该项目还将通过遵循3DL评估框架,促进理解本科生如何整合对关键STEM概念和跨学科数学的思考。NSF IUSE:EDU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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Kevin Haudek其他文献
Utilizing Deep Learning AI to Analyze Scientific Models: Overcoming Challenges
- DOI:
10.1007/s10956-025-10217-0 - 发表时间:
2025-04-01 - 期刊:
- 影响因子:5.500
- 作者:
Tingting Li;Kevin Haudek;Joseph Krajcik - 通讯作者:
Joseph Krajcik
Employing automatic analysis tools aligned to learning progressions to assess knowledge application and support learning in STEM
- DOI:
10.1186/s40594-024-00516-0 - 发表时间:
2024-11-08 - 期刊:
- 影响因子:8.000
- 作者:
Leonora Kaldaras;Kevin Haudek;Joseph Krajcik - 通讯作者:
Joseph Krajcik
Kevin Haudek的其他文献
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{{ truncateString('Kevin Haudek', 18)}}的其他基金
Evaluating Effects of Automatic Feedback Aligned to a Learning Progression to Promote Knowledge-In-Use
评估与学习进度相一致的自动反馈对促进知识使用的效果
- 批准号:
2200757 - 财政年份:2022
- 资助金额:
$ 69.99万 - 项目类别:
Continuing Grant
Developing a Next Generation Concept Inventory to Help Environmental Programs Evaluate Student Knowledge of Complex Food-Energy-Water Systems
开发下一代概念清单,以帮助环境项目评估学生对复杂食物-能源-水系统的了解
- 批准号:
2013359 - 财政年份:2020
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$ 69.99万 - 项目类别:
Standard Grant
COLLABORATIVE RESEARCH: Learning Progressions on the Development of Principle-based Reasoning in Undergraduate Physiology (LeaP UP)
合作研究:本科生生理学中基于原理的推理发展的学习进展(LeaP UP)
- 批准号:
1660643 - 财政年份:2017
- 资助金额:
$ 69.99万 - 项目类别:
Continuing Grant
Collaborative Research: ArguLex - Applying Automated Analysis to a Learning Progression for Argumentation
协作研究:ArguLex - 将自动分析应用于论证的学习进程
- 批准号:
1561159 - 财政年份:2016
- 资助金额:
$ 69.99万 - 项目类别:
Standard Grant
Collaborative Research: PCK*Lex: Applying Computerized Lexical Analysis to Develop a Cost-Effective Measure of Science Teacher Pedagogical Content Knowledge
合作研究:PCK*Lex:应用计算机词汇分析来开发科学教师教学内容知识的经济有效的衡量标准
- 批准号:
1438739 - 财政年份:2014
- 资助金额:
$ 69.99万 - 项目类别:
Standard Grant
Collaborative Research: Expanding a National Network for Automated Analysis of Constructed Response Assessments to Reveal Student Thinking in STEM
合作研究:扩大构建反应评估自动分析的国家网络,以揭示学生在 STEM 中的思维
- 批准号:
1323162 - 财政年份:2013
- 资助金额:
$ 69.99万 - 项目类别:
Continuing Grant
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