CAREER: The Measurement and Influence of Mathematics Motivation in a Digital Context

ECR计划强调基础STEM教育研究，将产生该领域的基础知识。这个早期教师职业发展项目支持知识的生成，通过建立一个坚实的基础，在STEM学科整合教育和研究的领导终身。它将研究如何通过提高学生的数学内容知识和学习数学的动机来解决国家对加强学生数学能力的关注。该研究将重点关注学生的学习动机，作为学生选择，坚持和成就STEM职业的重要预测因素。它将推动研究超越研究，只研究动机和数学成绩之间的联系，以了解动机如何发挥作用，以支持学生在学习过程中的选择。该项目将：（1）在时空数学数字平台中嵌入经验抽样问题和增强的选择选项;（2）检查情境学生动机，选择和学术成果之间的关联;（3）基于这些关联开发轻推干预措施，并在平台内的一系列实验中反复测试轻推;（4）评估轻推在随机试验中的影响。该项目将收集超过3万名三至五年级学生为期一年的数据。经验抽样和数据挖掘方法将用于收集学生在符合国家标准的数字化数学学习平台上从事时空数学的动机数据。方法包括调查、访谈、观察和其他与学生相关的测试和学校数据。试点研究将提供必要的数据，以制定干预措施，促进更深入的学习借鉴动机理论和行为经济学。从这个项目的结果将推进理论和分析基础，了解动机和选择位于现实世界的学习环境。这些新进展将有助于改变对学生动机和行为的理解，并为数学教学和学习的改进提供信息。除了将直接受到这项研究影响的30 K之外;在真实的时间里，该项目将有助于改善数字平台100多万现有用户的学习。因此，通过提高学生的内容知识和激励实践，同时为在挑战数学事业中取得成功奠定基础，结果将造福社会。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。

The ECR program emphasizes fundamental STEM education research that will generate fundamental knowledge in the field. This Early Faculty Career Development project supports the generation of knowledge through the building of a firm foundation for a lifetime of leadership in integrating education and research in STEM disciplines. It will examine ways to address a national concern for strengthening students' mathematics competency by enhancing their content knowledge in and motivation for learning mathematics. The study will focus on student motivation for learning as an important predictor of student choice, persistence, and achievement in STEM careers. It will advance research beyond studies that only examine links between motivation and mathematics achievement to lesser known aspects about how motivation functions to support students' in-the-moment choices during learning. The project will: (1) embed experience sampling questions and enhanced choice options within a Spatial Temporal Math digital platform; (2) examine associations between situated student motivation, choice, and academic outcomes; (3) develop nudge interventions based on these associations and iteratively test nudges in a series of experiments within the platform; and (4) assess the impact of nudges in a randomized trial. This project will collect data from over 30K third through fifth grade students for a period of one year.Experience sampling and data mining methods will be used to collect data about student motivation as they engage Spatial Temporal Math on a digitized mathematics learning platform aligned with state standards. Methods will include surveys, interviews, observations, and other student related tests and school data. Pilot studies will provide data essential to developing interventions that promote deeper learning drawing on motivation theory and behavioral economics. Results from this project will advance theoretical and analytic bases for understanding motivation and choice situated in real-world learning contexts. These new advances will help transform understanding about student motivation and behaviors as well as inform improvements in the teaching and learning of mathematics. In addition to the 30K that will be directly impacted by this study; in real time, the project will help improve learning for more than a million existing users of the digital platform. Thus, results will benefit society by enhancing student content knowledge and motivational practices while simultaneously developing a foundation for being successful in challenging mathematics undertakings.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.