Integrating Self-Regulated Learning Into STEM Courses: Maximizing Learning Outcomes With The Success Through Self-Regulated Learning Framework

这个IUSE 2级参与式学生学习项目旨在通过吸引更多在科学、技术、工程和数学（STEM）领域具有不同背景的人来服务于国家利益。该项目旨在通过自我调节学习的成功（StSRL）框架，提高高等教育学生在STEM学科中的学业成功和保留率。在自我调节学习中，学生在学习任务之前、期间和之后管理自己的行为，使他们能够掌握手头的任务或概念。基于理论和经验，StSRL框架将针对自我调节学习的五个相关组成部分：策略使用、元认知、动机、管理和内容实践。该框架将为教师提供一个平台，以生成动态的、双向的提示，学生可以通过应用程序或课程学习管理系统（LMS）做出回应，从而在科学课程环境中嵌入有效的自我调节学习实践。提示将根据格式（例如，多项选择，开放式回答，滑块）以及预期的学习功能（例如，元认知，策略，动机，内容，管理）而变化。初步数据表明，StSRL框架有望提高学生在STEM管道中的学习和记忆。该项目计划首先关注生物学课程的学生，然后将扩展到其他STEM背景。从这个项目中收集的数据将允许项目团队研究如何最大限度地干预，并将为教师的专业发展提供信息，以支持学生的自我调节学习。项目团队计划测试“通过自我调节学习取得成功”（StSRL）框架和系统干预措施的有效性，这些干预措施旨在提高成功的学习成果、学生成绩和中学后STEM课程的保留率。本项目旨在解决四个总体目标：1)进一步测试教师和学生使用StSRL框架对SRL、自我效能感和成就结果的影响；2)检查教师使用框架的差异如何影响干预的成功；3)测试StSRL的普遍性，并在STEM领域和学习环境中扩展；4)迭代设计并提供教师专业发展SRL STEM干预。将采用定量方法来研究这些目标是否已经实现。该项目计划通过丰富的数据源衡量框架和干预措施对STEM学生成绩和保留率的影响。项目数据将包括学生的人口统计、课程表现、StSRL提示表现，以及SRL结果，如元认知、动机变量和学习策略的使用。此外，双向实时干预的数据分析将有助于了解大规模技术支持干预措施的实施情况。对教师使用该框架的严格研究将为教师的专业发展提供信息和改进，并作为扩展干预措施的模型。由学习研究人员和科学教师组成的跨学科团队将提供教育理论专业知识与基于学科的教育研究知识的结合，为学术界做出广泛贡献。该项目不仅希望直接影响学生的自主学习、学习成果和记忆，还希望为学习专家和科学内容专家之间的深度合作提供路线图，以推动STEM背景下循证教学法的发展。以前在生物和物理环境下的研究结果将扩大到包括其他学科，更重要的是，包括在地区学院注册的学习者，在线环境中的成人STEM学习者，以及参加夏季桥梁项目的代表性不足的少数民族学生。NSF IUSE: EDU项目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。该奖项反映了美国国家科学基金会的法定使命，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。

This IUSE Level 2 Engaged Student Learning project aims to serve the national interest by engaging more people with diverse backgrounds in science, technology, engineering, and mathematics (STEM) fields. The project aims to improve postsecondary students' academic success and retention within STEM disciplines using the Success through Self-Regulated Learning (StSRL) framework. In self-regulated learning, students manage their behavior before, during, and after a learning task to allow them to master the task or concept at hand. Theoretically and empirically grounded, the StSRL framework will target five related components of self-regulated learning: strategy use, metacognition, motivation, management, and content practice. The framework will provide a platform for instructors to generate dynamic, bidirectional prompts that students respond to through an app or a course learning management system (LMS), thereby embedding effective self-regulated learning practices within scientific course contexts. Prompts will vary by format (e.g., multiple choice, open-ended response, slider), as well as by intended learning function (i.e., metacognition, strategy, motivation, content, management). Preliminary data suggest the StSRL framework holds promise to increase students’ learning and retention in STEM pipelines. This project plans to first focus on students enrolled in biology courses and then will scale to additional STEM contexts. Data collected from this project will allow the project team to study how to maximize the intervention and will inform faculty professional development to support students’ self-regulated learning. The project team plans to test the efficacy of the Success through Self-Regulated Learning (StSRL) framework and systematic interventions designed to increase successful learning outcomes, student achievement, and retention in post-secondary STEM coursework. This project intends to address four overarching objectives: 1) Further test the impact of instructor and student use of the StSRL framework on SRL, self-efficacy, and achievement outcomes, 2) Examine how differences in instructors’ use of the framework inform intervention success, 3) Test StSRL generalizability and scale up across STEM domains and learning contexts, and 4) Iteratively design and provide faculty professional development for SRL STEM interventions. Quantitative methods will be employed to study whether such objectives have been met. This project plans to measure the impact of the framework and interventions on student achievement and retention in STEM through rich data sources. Project data will include students’ demographics, course performance, and StSRL prompt performance, as well as SRL outcomes, such as metacognition, motivational variables, and learning strategy use. In addition, data analytics from the bidirectional, real-time interventions will contribute to understanding the implementation of large-scale, technology-supported interventions. Rigorous study of instructors’ use of the framework will inform and improve faculty professional development to serve as a model for scaling interventions. An interdisciplinary team of learning researchers and science faculty will offer a combination of education theory expertise with discipline-based education research knowledge to contribute broadly to scholarly communities. This project hopes to not only directly impact students’ self-regulated learning, learning outcomes, and retention, but also provide a roadmap for deep collaborations among learning experts and science-content experts to drive advancement of evidence-based pedagogies in STEM contexts. Results from previous work in biology and physics settings will be scaled to include other disciplines and, importantly, other populations, including learners enrolled in regional colleges, adult STEM learners in online settings, and underrepresented minority students participating in summer bridge programs. The NSF IUSE: EDU 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.