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NSFDirectorate for Engineering

IUSE/PFE:RED A&I: Professional Formation of Chemical Engineers through Cross-curricular Team-based Hands-on and Web-based Interactive Experiences

Active
Institution
Washington State University, WA
Principal investigator
Su Ha
Funding
$1.0M
Duration
2026–2031
Open portfolio

Moonbase score

Still being scored

Abstract

This project aims to transform chemical engineering education in the Gene and Linda Voiland School of Chemical Engineering and Bioengineering at Washington State University by integrating team-based, hands-on Desktop Learning Modules (DLMs), Web Interactive Digital Experiments (WIDEs), and engineering projects throughout the curriculum. The project addresses gaps in practical industrial knowledge and professional teamwork skills by implementing continuous, mentor-guided, team-based learning from the first year to the senior year. The project aligns closely with the NSF Professional Formation of Engineers (PFE) initiative that seeks to strengthen the nation’s engineering workforce. The project team will analyze how this integrated approach affects student learning, retention, and teamwork across different modes of student engagement, including interactive, constructive, active, and passive learning. This initiative will also foster a collaborative faculty culture and produce scalable, open-source educational tools for chemical engineering programs to help students connect individual unit components to larger chemical manufacturing systems. Ultimately, this department-wide revolution will deepen conceptual knowledge and advance PFE. We will conduct a longitudinal study comparing baseline student outcomes from conventional lectures against this new interactive paradigm. Educational tools, web alternatives, and low-cost equipment designs developed by graduate research assistants will be made available through open access on our website to help transform engineering pedagogy globally. The project focuses on transferring abstract concepts to real equipment to solve practical problems in multi-functional Chemical Engineering (ChE) teams. Five years of exit interviews reveal that graduating seniors lack cross-course connections and fail to link early curriculum topics to industrial practice. Furthermore, critical teamwork training is often delayed until the final year. To address these gaps, our goal is to train engineers who can seamlessly collaborate, manage deadlines, resolve conflicts, author cohesive reports, use AI professionally, and understand how individual process units fit into a broader manufacturing framework. To achieve this, the RED project team will execute three core initiatives: (1) Curriculum Transformation: We will integrate continuous, team-based hands-on learning using physical Desktop Learning Modules (DLMs) and Web Interactive Digital Experiments (WIDEs). Industry mentors will engage with student teams annually to help them connect isolated sub-component projects into complete chemical processing systems. (2) Faculty Culture Change: Guided by Bandura’s Social Cognitive Theory, we will foster a collaborative faculty environment focused on the step-by-step integration of DLMs and WIDEs. We will promote the Professional Formation of Engineers (PFE) through multi-unit team projects, evaluating success via concept tests, surveys, industry-reviewed reports, and retention metrics. And (3) Professional AI Integration: We will train students to utilize AI professionally for project documentation and equipment fault detection. We aim to expand educational research on how early, continuous exposure to physical and simulated equipment impacts high-level conceptual learning and practical understanding from semester one through graduation. Using pre- and post-tests, alongside surveys mapped to the ICAP engagement framework, we will assess how these interventions affect student knowledge, teamwork, and retention. We will also study how environmental and behavioral factors reshape the administrative culture based on Social Cognitive Theory to help other institutions replicate our model. 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.

Research team

  • Su HaPI
  • Bernard J Van WieCo-PI
  • David B ThiessenCo-PI
  • Steven R SaundersCo-PI
  • Colin S Lehman-ChongCo-PI

LOADING MOONBASE SCORE

Directorate for Engineering01002627DB NSF RESEARCH & RELATED ACTIVIT04002627DB NSF STEM EducationPFE\RED - Professional Formati, IUSEuniversitysystemsreviewchangegraduateintegrationinitiativecriteriameritfocuses

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