Transforming Undergraduate Engineering Education through Adaptive Learning and Student Data Analytics

该项目旨在通过整合个性化的课前体验来改善学生在STEM方面的学习，从而为国家利益服务，这些体验分别适应每个学生的知识水平。课堂上的主动学习已被证明对加强学生参与和提高学生学习成果有效。翻转课堂是一种流行的主动学习方法。在翻转教室中，学生可以从在线课程视频和自动测试等资源中学习基本信息。 这种学习发生在每个学生自己的节奏，在常规课堂讲座之前。 然后，在讲座期间，学生与他们的同龄人合作解决应用他们在课堂外学到的知识的问题。该项目旨在通过将个性化和自适应的课前内容整合到每个学生的学习体验中来改进翻转课堂方法。自适应课程的使用与美国国家工程院21世纪世纪重大挑战之一“推进个性化学习”非常吻合。大多数工程问题都很复杂;它们可能需要很长时间才能解决，并且通常没有单一的解决方案。为了培养解决这些问题的能力，大多数本科STEM学生都参加了数值方法课程。该项目涉及的发展适应性课程的数值方法和评估的认知和情感学习成果的学生在这样的课程在三个不同的机构：南佛罗里达，亚利桑那州立大学，和亚拉巴马A M大学。评估工作的一个重要组成部分将集中在各种人口部分，包括代表性不足的少数民族，女性和佩尔助学金的学生，以确保所有材料在不同的学生群体中工作良好。学生在适应性课程中的参与和表现也将被实时分析，以支持学生的成功。例如，将创建积极的干预措施和资源，一旦学生在课程中表现出挣扎的迹象，就可以实施。该项目将数值方法课程重组为具有个性化，自适应学习的翻转课堂。该项目还将通过分析学生学习数据，比较使用和不使用自适应课程的翻转课堂与学生认知和情感学习成果的关系。调查中使用的方法包括多项评估的定性和定量措施，以核实调查结果的一致性。该项目将提供教学材料，促进以翻转模式教授STEM课程的最佳做法，并提供自适应学习课程，从而为推进个性化学习提供知识基础。 传播途径包括研讨会、手稿、开放教育资源门户网站和社交媒体。该项目由NSF改善本科STEM教育：教育和人力资源计划资助，该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。

This project aims to serve the national interest by improving student learning in STEM by integrating personalized pre-class experiences that adapt individually to each student’s level of knowledge. Active learning in the classroom has been proven effective for strengthening student engagement and improving student learning outcomes. The flipped classroom is one popular active learning approach. In flipped classrooms, students learn basic information from resources such as online lecture videos and automated testing. This learning takes place at each students’ own pace, prior to the regular class lecture. Then, during the lecture period, students collaborate with their peers to solve problems that apply the knowledge they learned outside of class. This project aims to improve the flipped classroom approach by integrating personalized and adaptive pre-class content into each student's learning experiences. The use of adaptive lessons aligns well with "Advancing Personalized Learning," one of the National Academy of Engineering's 21st Century Grand Challenges. Most engineering problems are complex; they may take a long time to solve and often do not have single solutions. To develop the ability to solve such problems, most undergraduate STEM students take a course in Numerical Methods. This project involves the development of adaptive lessons for a course in Numerical Methods and the assessment of the cognitive and affective learning outcomes of students in such courses at three diverse institutions: the University of South Florida, Arizona State University, and Alabama A&M University. A significant part of the assessment effort will focus on various demographic segments, including underrepresented minority, female, and Pell Grant students, to ensure that all materials work well across diverse student populations. Students' engagement with and performance in the adaptive lessons will also be analyzed in real-time to support student success. For example, proactive interventions and resources will be created that can be implemented as soon as students show signs of struggling in the course. The project restructures the Numerical Methods course as a flipped classroom with personalized, adaptive learning. This project will also compare a flipped classroom with and without the use of adaptive lessons relative to student cognitive and affective learning outcomes, and through analytics of student learning data. Metrics used in the investigation include both qualitative and quantitative measures of multiple assessments to verify the consistency of findings. The project will deliver instructional materials that facilitate best practices for teaching STEM courses in flipped mode with adaptive learning lessons, thereby contributing to the knowledge base for advancing personalized learning. Dissemination avenues include workshops, manuscripts, open education resource portals, and social media. This project is funded by the NSF Improving Undergraduate STEM Education: Education and Human Resources program, which 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.