Collaborative Research: Connecting Professional and Educational Communities to Prepare Construction Engineering Students for the Workplace

虽然大学为学生提供了STEM的理论知识，但在运用这些理论解决现实问题方面可能存在挑战。这一挑战导致了毕业生进入劳动力市场的准备与行业需求之间的不平衡。这种脱节在建筑行业持续存在，因为建筑从业者不断强调技能短缺导致低绩效和低生产率。该研究项目旨在将学习者与实践社区联系起来，从而使他们能够获得了解，思考，推理和解决现实生活问题的专家方法。研究团队将开发一种工具，将建筑工程项目与实践社区联系起来，从而使教师能够接触到具有适当专业知识的行业从业者，以满足他们的实践课程支持需求（例如，实地考察、客座讲座和顶点项目的导师）。当学习者与实践社区互动时，这有可能告知学习者感知职业的方式和他们自己的职业身份的发展。这两种现象将通过定性研究来检验。该项目旨在创建一个协作网络（称为ConPEC），以调查建筑行业从业者对教师的可及性如何影响建筑工程专业学生的纪律感知和职业认同发展。ConPEC平台将采用机器学习算法和复杂的数据分析，以便将教师与其实践社区配对。为此，本研究将首先调查建筑工程讲师的实际课程支持需求和行业从业者的特点。接下来，ConPEC框架将被设计为包括学习驱动算法，以利用教师和行业从业者之间的动态匹配模式。最后，团队将使用与学生和行业从业者的半结构化访谈来收集定性数据，这些数据将使用扎根理论进行分析。研究小组将研究学生自律认知和职业认同发展的变化。本项目由美国国家科学基金会EHR核心研究（ECR）项目支持。ECR项目强调在该领域产生基础知识的基础STEM教育研究。投资在至关重要、广泛和持久的关键领域：STEM学习和STEM学习环境，扩大STEM参与，以及STEM劳动力发展。该项目支持积累有力的证据，为理解、构建理论进行解释提供依据，并提出干预和创新建议，以应对教育中持续存在的挑战。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。

While universities equip students with theoretical knowledge for STEM, there can be challenges in employing those theories to solve real-life problems. This challenge has resulted in an imbalance between the preparation of graduates entering the workforce and the demands of the industry. This disconnection is persistent in the construction industry as construction practitioners continue to highlight skill shortages that have resulted in low performance and low productivity. This research project is designed to connect learners with communities of practice thereby giving them access to expert ways of knowing, thinking, reasoning, and solving real-life problems. The research team will develop a tool that connects construction engineering programs with communities of practice thereby enabling instructors access to industry practitioners with the appropriate expertise to meet their practical course-support needs (e.g., site visits, guest lectures, and mentors for capstone projects). As learners interact with communities of practice, this has the potential to inform the ways learners perceive the profession and the development of their own professional identity. These two phenomena will be examined through a qualitative study. This project is designed to create a collaborative network (called ConPEC) to investigate how the accessibility of construction industry practitioners to instructors, influences construction engineering students’ disciplined perception and professional identity development. The ConPEC platform will employ machine learning algorithms and complex data analysis to allow for pairing instructors with their community of practice. To achieve this, the research will first investigate the practical course-support needs of construction engineering instructors and the characteristics of industry practitioners. Next, the ConPEC framework will be designed to include learning-driven algorithms to exploit dynamic matching patterns between instructors and industry practitioners. Finally, the team will use semi-structured interviews with both students and industry practitioners to gather qualitative data that will be analyzed using Grounded Theory. The research team will examine changes in students’ disciplined perception and professional identity development.This project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in education.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.