Dukes, A., & Besterfield-Sacre, M. E., & Fullerton Shirey, S. K. (2025, February), Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge  Paper presented at 2025 Collaborative Network for Engineering & Computing Diversity (CoNECD), San Antonio, Texas. https://peer.asee.org/54106

\bibitem{asee_peer_54106}
  Dukes, A., \& Besterfield-Sacre, M. E., \& Fullerton Shirey, S. K. (2025, February), \emph{Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge}
  Paper presented at 2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD), San Antonio, Texas.
  https://peer.asee.org/54106

April Dukes, Mary E. Besterfield-Sacre, and Susan K Fullerton Shirey.  "Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge".  2025 Collaborative Network for Engineering & Computing Diversity (CoNECD), San Antonio, Texas, 2025, February.  ASEE Conferences, 2025.  https://peer.asee.org/54106 Internet.  24 Mar, 2025

\bibitem{asee_peer_54106}
  April Dukes, Mary E. Besterfield-Sacre, and Susan K Fullerton Shirey.
  "Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge".
  \emph{2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD), San Antonio, Texas, 2025, February}.
  ASEE Conferences, 2025.
  https://peer.asee.org/54106 Internet.  24 Mar, 2025

@INPROCEEDINGS{asee_peer_54106
author = "April Dukes, Mary E. Besterfield-Sacre, and Susan K Fullerton Shirey"
title = "Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge"
booktitle = "2025 Collaborative Network for Engineering \& Computing Diversity (CoNECD)"
year = "2025"
month = "February"
address = "San Antonio, Texas"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/54106}
}

TY  - CPAPER
AB  - Despite calls over the past twenty years to develop graduate STEM education models that prepare students for the new post-graduate workforce, few innovations in graduate STEM education have been disseminated. Given the diversity of graduate candidates’ prior skills, preparation, and individual career aspirations, modernizing STEM graduate programs is needed to support and empower student success in graduate programs and beyond. In this session, participants will learn about new research into the development and implementation of a personalized learning model (PLM) for graduate STEM education employed in a chemical engineering department at an R1 university. Our PLM integrates student-centered approaches in coursework, research, and professional development in multiple programmatic components. The key components of our PLM include guided student creation of independent development plans (IDPs), modularization of graduate courses and professional development streams, scaffolding curricular instruction to prioritize independence and mastery, using IDPs for directed research and career discussions and assessment of student performance and learning, and evaluation of the program from current students, alumni, faculty, and industry partners. Our comprehensive PLM plan is designed to maximize impact through personalized learning touchpoints throughout all aspects of graduate training.  

This presentation will focus on one element of our PLM, the modularization of the chemical engineering core graduate courses. To ensure the learning in core graduate courses reflects the diverse needs of chemical engineers, we generated a body of knowledge (BOK) for graduate chemical engineering in collaboration with our technical advisory board (TAB), which included chemical engineers and people that work with chemical engineers from industry, national labs, academia, and entrepreneurial representatives. We started by collecting the learning objectives (LO’s) from all core chemical engineering courses: Thermodynamics, Kinetics and Reactor Design, Transport Phenomena, Mathematical Methods, and Issues in Research and Teaching. The LO’s were refined by alignment with course assignments and activities and re-written using the most accurate Bloom’s Taxonomy verbs in collaboration with an instructional designer. We utilized GroupWisdomTM for group concept mapping of the new LO’s and provided an opportunity for the TAB to add new LO’s, identified by the individuals in the TAB to be critical for success in each member’s occupation. LO’s for the chemical engineering core courses were sorted on the level of knowledge (undergraduate, graduate, and specialized) and rated for importance by the TAB. Using GroupWisdom’sTM analytic tool for creating a similarity matrix for sorting the level of LO’s, multidimensional scaling, and hierarchical cluster analysis, all core course LO’s have been grouped into 6 clusters. These clusters, along with the current course list and the LO importance ratings, helped us visualize converting chemical engineering core courses into 1-credit hour modules. This restructured curriculum offers opportunities for ensuring that students have learned the requisite prior knowledge by review of essential undergraduate principles, streamlining essential graduate-level material, and supporting self-directed learning through the selection of specialized modules that align with students’ research and career goals. This proposed approach shifts core graduate chemical engineering education to an asset-based system, addressing knowledge gaps and ensuring rigorous, tailored learning experiences. 
AU  - April Dukes
AU  - Mary E. Besterfield-Sacre
AU  - Susan K Fullerton Shirey
CY  - San Antonio, Texas
DA  - 2025/02/09
PB  - ASEE Conferences
TI  - Piloting A Personalized Learning Model for Chemical Engineering Graduate Education – Lessons Learned from Creating a Chemical Engineering Body of Knowledge
UR  - https://peer.asee.org/54106
ER  -