Collaborative Research: Understanding and Supporting Student Intrinsic Motivation in STEM Courses

协作研究：理解和支持 STEM 课程中学生的内在动机

• 批准号: 1322684
• 负责人: Jonathan Stolk
• 金额: $ 48万
• 依托单位: Franklin W. Olin College of Engineering
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1322684&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Supporting; Student

Building on prior work in motivation, this project is collecting and analyzing quantitative and qualitative data to improve the capability to characterize and explain key characteristics of student motivation in diverse undergraduate courses required for engineering education. This project is engaging instructors in the process of interpreting student motivation data, coupling these research data to motivation theory and course design, and developing course revisions aimed at enhancing STEM students' intrinsic drive.Intellectual MeritThis research rests on prior research that shows that instructors can directly influence student motivation, particularly intrinsic motivation, through their course design decisions. To capitalize on the potential of this relationship, instructors need both a more nuanced understanding of the types of student motivations for learning and access to clearer methods for translating theory and empirical data to course-level insights. This project is measuring individual student responses to diverse STEM environments, pedagogies, and assignments. The temporal evolution of these responses is a focal point in the development of transferable research and generalizable theories for STEM student motivational drive.The analysis of motivation data in more nuanced ways examines general trends in motivation by course activity, year of study, and gender. Motivation is dynamic and susceptible to frequent and sometimes rapid change. The analysis uses group-based clustering techniques to discover the strength, persistence, and distribution of different types of motivational responses. It employs qualitative analyses to explain the relationships between motivation and the learning environment and elucidate gendered differences in motivation. Using both variable- and cluster-based analyses in multiple course analyses has promise in developing better understanding of the impact of instructional design on effective practice. BROADER IMPACTSThe National Academy of Engineering exhorts us to prepare STEM graduates with "the tools needed for the world as it will be, not as it is today." Among these tools are creativity, critical thinking, resiliency, flexibility, and self-regulation. Educational research suggests that improved understanding of learner motivation is important to facilitate a systemic shift toward these high-level outcomes. However, a large gap remains between the research-based understanding of student motivation, and the application of those research insights to day-to-day classroom practice. The output from this project will have an immediate impact on over 20 STEM instructors at the 8 participating institutions, by highlighting activities that prompt different motivational responses and motivational shifts, explaining motivation-environment interactions, and by enabling instructors to use research data to make informed and strategic choices to better encourage self-determined behaviors. The project expands the pool of STEM faculty who can make informed, data-driven decisions by engaging early-career faculty and those with limited prior involvement in STEM educational reform.

在先前动机研究的基础上，本项目收集和分析定量和定性数据，以提高描述和解释工程教育所需的各种本科课程中学生动机的关键特征的能力。该项目让教师参与解释学生动机数据的过程，将这些研究数据与动机理论和课程设计相结合，并制定旨在增强STEM学生内在动力的课程修订。本研究基于先前的研究，该研究表明教师可以通过他们的课程设计决策直接影响学生的动机，特别是内在动机。为了充分利用这种关系的潜力，教师需要更细致地了解学生学习动机的类型，并获得更清晰的方法，将理论和经验数据转化为课程层面的见解。该项目旨在衡量学生个体对不同STEM环境、教学方法和作业的反应。这些反应的时间演变是STEM学生动机驱动的可转移研究和可推广理论发展的焦点。对动机数据的分析以更细致的方式考察了课程活动、学习年份和性别对动机的总体趋势。动机是动态的，容易受到频繁甚至有时是快速变化的影响。该分析使用基于群体的聚类技术来发现不同类型动机反应的强度、持久性和分布。本研究采用定性分析来解释动机与学习环境之间的关系，并阐明动机的性别差异。在多门课程分析中同时使用变量分析和基于聚类的分析有助于更好地理解教学设计对有效实践的影响。更广泛的影响美国国家工程院（National Academy of Engineering）告诫我们，为STEM毕业生准备好“未来世界所需的工具，而不是今天的世界。”这些工具包括创造力、批判性思维、弹性、灵活性和自我调节。教育研究表明，提高对学习者动机的理解对于促进向这些高水平结果的系统转变非常重要。然而，在以研究为基础的对学生动机的理解与将这些研究见解应用于日常课堂实践之间仍然存在很大差距。该项目的成果将对8所参与机构的20多名STEM教师产生直接影响，重点介绍促进不同动机反应和动机转变的活动，解释动机与环境的相互作用，并使教师能够使用研究数据做出明智的战略选择，以更好地鼓励自主行为。该项目通过吸引早期职业教师和之前参与STEM教育改革有限的教师，扩大了STEM教师的数量，使他们能够做出明智的、数据驱动的决策。