2025 ASEE Annual Conference & Exposition

Work-in-progress: Evidence-based scope and selection of threshold concepts for the design of computational notebooks in undergraduate statistics courses for chemical engineering

Presented at Chemical Engineering Division (ChED) Poster Session

Computational tools continue to gain popularity across engineering curricula. Computational notebooks, such as Jupyter, Google Colab, and MATLAB live scripts, allow dynamic interactions between instructors and students with immediate feedback on a given topic. However, there are limited guidelines on how to design these computational notebooks to intentionally enhance student learning, specifically what concepts to include in the notebooks. There is limited literature on this topic in the context of general engineering education, especially at the undergraduate level. In this work-in-progress, we focus explicitly on an undergraduate introductory statistics course for students in a chemical engineering program. Our overarching research goal is to devise how these computational notebooks indeed facilitate student learning in the context of undergraduate instruction. We first engage in identifying relevant statistics concepts for chemical engineering that could be identified as threshold concepts (TCs). These are concepts that are essential for building understanding and applying the rest of the content in a course or subject. Therefore, the goal of this paper is to conduct a literature review of TCs related to undergraduate statistics for chemical engineering. We start with the current knowledge on the TCs in general undergraduate engineering education, present the common approaches for mapping and assessing TCs in engineering courses, and discuss specific works related to statistics courses for undergraduate students to showcase the main roadblocks students face when learning statistics and data analysis. This literature review will serve as a baseline to establish a set of concepts that will offer critical learning areas to focus the design of computational notebooks in the context of undergraduate chemical engineering education.

Authors

Dr. Viviana Monje http://orcid.org/0000-0002-9202-782X University at Buffalo, The State University of New York [biography]

Dr. Viviana Monje is an Assistant Professor in the Department of Chemical and Biological Engineering at the University at Buffalo (UB), SUNY. She teaches undergraduate statistics for chemical engineers and a course on molecular modeling theory and applications offered for graduate and undergraduate students. Her research expertise is on computational biophysics of lipid membranes and their interactions with other biomolecules. She is invested on promoting and mentoring underrepresented minorities in science and engineering, and is initiating her training in Engineering Education Research.
Jinhui Li Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York [biography]

Jane Doe is a PhD candidate in the Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York.
Dr. Ashlee N Ford Versypt http://orcid.org/0000-0001-9059-5703 University at Buffalo, The State University of New York [biography]

Dr. Ashlee N. Ford Versypt is Distinguished Member of ASEE and an Associate Professor in the Department of Chemical and Biological
Engineering at the University at Buffalo (UB), The State University of New York. She is also an Affiliated Faculty in the Department of Engineering Education, Department of Biomedical Engineering, Department of Pharmaceutical Sciences, and the Institute for Artificial Intelligence and Data Science.
Matilde Luz Sanchez-Pena http://orcid.org/0000-0002-3511-0694 University at Buffalo, The State University of New York [biography]

Dr. Matilde Sánchez-Peña is an assistant professor of Engineering Education at the University at Buffalo – SUNY where she leads the Diversity Assessment Research in Engineering to Catalyze the Advancement of Respect and Equity (DAREtoCARE) Lab. Her research focuses on developing cultures of care and well-being in engineering education spaces, assessing gains in institutional efforts to advance equity and inclusion, and using data science for training socially responsible engineers.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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