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)

基本信息

  • 批准号:
    1660643
  • 负责人:
  • 金额:
    $ 48.6万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-07-15 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

The complex societal problems of increasing agricultural production to meet the needs of 9 billion people by 2050, and caring for an aging population with increasingly more complex neurological and cardiovascular health issues require future scientists, physicians, and allied health professionals to develop expertise in organismal physiology. In physiology, as in other disciplines, becoming an expert in a field requires the abilities to recognize, understand and effectively reason using the principles of the discipline. During their college careers, science students often rely on rote memorization rather than principle-based reasoning to solve problems, and this leads to context-bound thinking that fails to build robust understandings. Such students can, for example, list the steps involved in muscle contraction, but cannot predict what will happen when a mutation is introduced in a muscle protein. This project will develop a "learning progression" to document how college students can develop more and more sophisticated principle-based reasoning over time to understand the physiology of animals and plants in both introductory biology and anatomy and physiology courses. Based on this learning progression, the project team will also develop open-ended assessment questions that can be scored via computer. Collectively, these tools will have the potential to transform how college students learn physiology, and to significantly enhance the quality of their resulting understanding and ability to solve related problems. The project, entitled Learning Progressions on the Development of Principle-based Reasoning in Undergraduate Physiology (LeaP UP), is supported by the Education and Human Resources Core Research Program, which funds fundamental research in STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.The LeaP UP project will develop a learning progression that describes how undergraduate students develop principle-based reasoning in the use of flux (flow down gradients) and mass balance (Conservation of Mass) in physiology. The learning progression will then guide the creation of constructed response assessments and associated computer scoring models that instructors can use to determine where their students are along the spectrum of understanding. The project team will capitalize on cutting edge advances in natural language processing and text analysis to create computer programs to accurately predict how experts would score students' responses to the conceptual constructed-response assessments. These automated scoring methods will rapidly score responses from large numbers of college students nationwide and allow the investigators to map national trends in students levels of understanding of students as they move through their undergraduate Biology and pre-Allied Health curricula at community colleges to large research universities. Thus, the tools developed will provide an organizing framework for the future redesign of undergraduate physiology curricula.
到2050年,增加农业生产以满足90亿人口的需求,并照顾越来越复杂的神经系统和心血管健康问题越来越复杂的人口的复杂社会问题需要未来的科学家,医生和盟友的卫生专业人员来发展有机体生理学的专业知识。在生理学中,就像在其他学科中一样,成为一个领域的专家都需要使用该学科原则来识别,理解和有效理解的能力。在他们的大学职业生涯中,科学专业的学生经常依靠死记硬背,而不是基于原则的推理来解决问题,这导致无法建立强大理解的背景思维。例如,这样的学生可以列出肌肉收缩涉及的步骤,但无法预测在肌肉蛋白中引入突变时会发生什么。该项目将开发一个“学习进步”,以记录大学生如何随着时间的推移发展越来越复杂的基于原则的推理,以了解入门生物学以及解剖学和生理学课程中动物和植物的生理学。基于这个学习的进步,项目团队还将制定可以通过计算机评分的开放式评估问题。总的来说,这些工具将有可能改变大学生学习生理学的方式,并显着提高他们所产生的理解和解决相关问题的能力的质量。该项目题为“学习进步有关基于原则的本科生理学推理(LEAP)的发展,受教育和人力资源核心研究计划的支持,该计划为STEM学习和学习环境提供了基础研究,扩大了STEM的参与以及STEM劳动力的参与以及STEM劳动力的发展。质量)生理学。然后,学习进展将指导创建构建的响应评估和相关的计算机评分模型,教师可以使用这些模型来确定学生沿着理解的范围。项目团队将利用自然语言处理和文本分析的最前沿进步,以创建计算机程序,以准确预测专家如何为学生对概念构建的响应评估的响应进行评分。这些自动评分方法将在全国范围内的大量大学生中迅速得分,并允许研究人员在学生通过本科生物学和社区学院的预先抗议健康课程中绘制学生对学生的了解水平。因此,开发的工具将为本科生理学课程的未来重新设计提供组织框架。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Covariational reasoning and item context affect language in undergraduate mass balance written explanations
  • DOI:
    10.1152/advan.00156.2022
  • 发表时间:
    2023-12-24
  • 期刊:
  • 影响因子:
    2.1
  • 作者:
    Shiroda,Megan;Doherty,Jennifer H.;Haudek,Kevin C.
  • 通讯作者:
    Haudek,Kevin C.
Ecological diversity methods improve quantitative examination of student language in short constructed responses in STEM
生态多样性方法改善了 STEM 中简短回答中学生语言的定量检查
  • DOI:
    10.3389/feduc.2023.989836
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    Shiroda, Megan;Fleming, Michael P.;Haudek, Kevin C.
  • 通讯作者:
    Haudek, Kevin C.
Comparison of Machine Learning Performance Using Analytic and Holistic Coding Approaches Across Constructed Response Assessments Aligned to a Science Learning Progression
使用分析和整体编码方法在与科学学习进展相一致的构建响应评估中比较机器学习性能
  • DOI:
    10.1007/s10956-020-09858-0
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Jescovitch, Lauren N.;Scott, Emily E.;Cerchiara, Jack A.;Merrill, John;Urban-Lurain, Mark;Doherty, Jennifer H.;Haudek, Kevin C.
  • 通讯作者:
    Haudek, Kevin C.
A new assessment to monitor student performance in introductory neurophysiology: Electrochemical Gradients Assessment Device
监测学生神经生理学入门表现的新评估:电化学梯度评估装置
  • DOI:
    10.1152/advan.00209.2018
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    2.1
  • 作者:
    Cerchiara, Jack A.;Kim, Kerry J.;Meir, Eli;Wenderoth, Mary Pat;Doherty, Jennifer H.
  • 通讯作者:
    Doherty, Jennifer H.
Oaks to arteries: the Physiology Core Concept of flow down gradients supports transfer of student reasoning
从橡树到动脉:向下梯度流动的生理学核心概念支持学生推理的迁移
  • DOI:
    10.1152/advan.00155.2022
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    2.1
  • 作者:
    Doherty, Jennifer H.;Cerchiara, Jack A.;Scott, Emily E.;Jescovitch, Lauren N.;McFarland, Jenny L.;Haudek, Kevin C.;Wenderoth, Mary Pat
  • 通讯作者:
    Wenderoth, Mary Pat
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Kevin Haudek其他文献

Kevin Haudek的其他文献

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{{ truncateString('Kevin Haudek', 18)}}的其他基金

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
  • 批准号:
    2235487
  • 财政年份:
    2023
  • 资助金额:
    $ 48.6万
  • 项目类别:
    Standard Grant
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:
    $ 48.6万
  • 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
  • 资助金额:
    $ 48.6万
  • 项目类别:
    Standard 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:
    $ 48.6万
  • 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:
    $ 48.6万
  • 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:
    $ 48.6万
  • 项目类别:
    Continuing Grant

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