2026 ASEE Annual Conference & Exposition

Study of Flowchart Slippage

Presented at Electrical and Computer Engineering Division (ECE) Technical Session 13

How well do students follow faculty-defined flowcharts? Is student progress in lock step with flowcharts? How much does progress vary by major, or for part time students? How does advanced placement credit impact progress on a flowchart? Our study of student progress has yielded some surprising results to these questions and progress is far from lock step.

We used university archival data to compare actual progress to the ideal version depicted on a curriculum flowchart, using historical data. Delays in actual enrollment relative to the ideal are referred to as flowchart slippage. A regression analysis was used to model slippage, with the goal of identifying dependent variables that are correlated to changes in slippage along prerequisite chains. This study builds on concepts from prior work in curriculum complexity metrics. We extend the prior work by including comparisons with actual student data, and we use the regression to help identify the existence of trends. Analysis of the historical data has also revealed the benefit of specific structures of curricular requirements that mitigate and even reduce slippage.

A tenet of this work is that students are not to blame for flowchart slippage. Rather, the root causes are systemic in nature and slippage is merely a symptom. Examples of these systemic issues include work commitments, family care, and part-time enrollment. Additional issues include institutional constraints, such as courses not being offered every term, courses conflicted with each other, or there being insufficient seats for a particular course in a particular term. All these factors are in addition to curricular complexity.

We pose the following research questions:

RQ1 Are slippage patterns discernible in sequences of courses?
RQ2 Is slippage correlated to curriculum complexity metrics and academic data?
RQ3 Under what conditions does slippage tend to lessen?
RQ4 How much does slippage vary for different majors or populations (part-time, transfer)?

The full paper will include a description of the archival data and regression analysis. Results indicated correlation values as high as 0.67 between slippage and our dependent variables. Results also demonstrated instances where flowchart slippage was reduced! Our comparison of actual student progress versus the flowchart provided a means to confirm assumptions made by others in prior work.

This paper assesses curricula using a new method referred to as slippage analysis. Results over multiple cohorts and comparisons with related majors are included.

Authors

Dr. Fred W DePiero California Polytechnic State University, San Luis Obispo / Allan Hancock College [biography]

Dr. Fred DePiero earned his BS and MS degrees in Electrical Engineering at Michigan State University. After which he worked at Oak Ridge National Lab in the areas of robotics and machine vision. He then earned his PhD, also in EE, from the University of Tennessee. In 1996 he moved to San Luis Obispo, CA and joined the faculty of Cal Poly in EE. In 2005, Fred received the Distinguished Teaching Award, which is the University’s highest recognition for teaching. Subsequently, he served as an Associate Dean, then rejoined the faculty in the Computer Engineering Department, and retired in 2024. His areas of interest have branched out to include web applications for teaching and learning systems (see YourLearningCoach.org), as well as new approaches design nonlinear voltage transfer characteristics. Fred now teaches part time at Allan Hancock College.
Dr. Stephen R. Beard California Polytechnic State University, San Luis Obispo [biography]

Stephen R. Beard is an Assistant Professor at Cal Poly San Luis Obispo in the Computer Science and Software Engineering Department with a joint appointment in the Computer Engineering Department. Stephen's educational goal is to develop opportunities for diverse sets of students to get hands on experience with security, architecture, languages, and compilers. Stephen's research interests primarily revolve around security that involves the hardware-software boundary. This manifests in lots of ways, in particular, cyber-physical security, secure architectures, secure language design, and secure compilation.

As a former transfer student and beneficiary of a great deal of invaluable mentorship throughout his life, Stephen participates in multiple mentoring and advising programs. While many of these are focused on transfer students, he is interested in improving the lived experience of all students. His door is always open if you ever need advice, someone to just listen to you, or just want to chat!

Stephen received his PhD and MS degrees in Computer Science at Princeton University, under the guidance of David I. August as a proud member of the Liberty Research Group. Stephen received his BS degree in Computer Engineering from Cal Poly!
Dr. Jane L. Lehr California Polytechnic State University, San Luis Obispo [biography]

Jane Lehr is a Professor in Ethnic Studies and Women's and Gender Studies and Director of the Office of Student Research at California Polytechnic State University, San Luis Obispo. She is affiliated faculty in Computer Science & Software Engineering and

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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