Coordinating Curricula and User Preferences to Increase the Participation of Women and Students of Color in Engineering

几十年来，学术机构获得了财政资源，以扩大工程项目的参与。尽管有这些资助的招聘和保留努力，大多数工程项目在女性、有色人种学生、残疾人和其他未被充分代表的群体的参与方面几乎没有取得任何进步。解释这种差异的一个假设是，女性和有色人种学生在工程专业的低代表性是由于工程课程缺乏可及性。为了验证这一假设，本项目试图研究工程课程和学生的偏好。基于这些结果，它旨在开发一套课程指南和模型，以增加工程课程与学生的期望和学习偏好之间的一致性。这些结果有可能扩大女性和有色人种学生在工程领域的参与。该项目采用探索性顺序混合方法设计，从探索性活动开始，并建立更系统的研究问题测试，以了解特定用户偏好如何影响学生的参与。研究人员将从事教学大纲、课程内容、公共空间和教师材料的数据挖掘，以不同的表示形式（如方程、图像、叙述、模拟和视频）汇总有关课程的信息。从这些数据中，预计将生成课程表示的定性和定量不同的概况。调查人员将跟踪学生在STEM中的纵向持久性，与课程结构和个人学习者偏好的关系。了解学习者偏好与工程课程之间的交集，有可能改善工程教育，扩大工程领域的参与。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。

For several decades, academic institutions have received financial resources to broaden participation in engineering programs. Despite these funded recruitment and retention efforts, most engineering programs have achieved little improvement in the participation of women, students of color, individuals with disabilities, and other underrepresented groups. One hypothesis to explain this discrepancy is that the low representation of women and students of color in engineering results from the lack of accessibility of engineering curricula. To test this hypothesis, this project seeks to study engineering curricula and student preferences. Based on those results, it aims to develop a set of curriculum guidelines and models that may increase the alignment between engineering curricula and students' expectations and preferences for learning. These results have the potential to broaden participation of women and students of color in engineering. The project uses an exploratory sequential mixed methods design, which begins with exploratory activities and builds to more systematic testing of research questions concerning how particular user preferences influence student participation. Investigators will engage in data mining of syllabi, course content, public spaces, and instructor materials to aggregate information about curricula presented in different representational forms, such as equations, images, narratives, simulations, and videos. From these data, it is anticipated that qualitatively and quantitatively distinct profiles of course representations will be generated. The investigators will track longitudinal persistence of students in STEM, in relationship to course structure and individual learner preferences. Understanding the intersection between learner preferences and engineering curricula has the potential to improve engineering education and broaden participation in the field of engineering.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.