2026 ASEE Annual Conference & Exposition

Work‐in‐Progress: An Investigation into the Benefits of Tagged Assessment Scores

Presented at Computers in Education (CoED): Poster Session - Division Special Events (1 of 4) -- M208

Course grades, while widely used, have significant limitations as measures of student learning, progress, and potential. They tend to obscure the nuanced strengths and weaknesses of individual students, are often subjective or inconsistent, emphasize performance over learning, and provide little meaningful feedback to learners, instructors, or employers. Moreover, grades rarely capture critical skills such as creativity, collaboration, or resilience. Despite these shortcomings, grades persist due to their convenience, tradition, and perceived objectivity—they offer an easy way to standardize, compare, and report outcomes, even if they fail to reflect actual learning. Institutional inertia and the administrative simplicity of grading systems further reinforce their use. Compounding this, most educational data systems are built around the single-number course grade, constraining how learning is recorded and understood. Broadening these systems’ capabilities could allow for richer, more individualized representations of student growth, improving feedback and educational alignment overall.

To that end, we have developed software that provides features that are generally missing from most learning management systems. The key aspect of the tool is that every assessment score–e.g., scores on homeworks, labs, exams, etc.–can be associated with a collection of category labels called “tags.” An instructor may choose these labels freely, but possible tags may include “math”, “communication”, “team work”, and “creativity” for example. A score can be associated with multiple tags. The software system then allows instructors to easily upload tagged score spreadsheets to a web interface, which, in turn, shares the data with the students and their academic advisors. Besides listing the data in tagged tables one can also choose to view data through configurable histograms and timelines. The configuration interface allows students and faculty to select and view data associated with a collection of tags, whereby unions or intersections of tag associations can be chosen. With the resulting system it becomes possible to quickly obtain an overview of how individual students, as well as groups of students, perform across predefined categories and thereby providing nuance about weaknesses and strengths in individual student performance as well as the overall structure of the curriculum.

By offering these additional features to our instructors and students we want to ultimately learn how the fine grain information provided by this easy-to-use web platform may influence the learning process by the students and the teaching process for the instructors. The goal of this work-in-progress paper is, in a first step, to use survey data to report back on whether the system and its underlying concepts are perceived to be beneficial to faculty and students or not.

Authors

Prof. Robert M Nickel Bucknell University [biography]

Robert M. Nickel received a Dipl.-Ing. degree in electrical engineering from the RWTH Aachen, Germany, in 1994, and a Ph.D. in electrical engineering from the University of Michigan in 2001. During the 2001/2002 academic year he was an adjunct instructor at the Department of Electrical Engineering and Computer Science at the University of Michigan. From 2002 until 2007 he was a faculty member at Penn State University. Since the fall of 2007 he is a faculty member at the Electrical and Computer Engineering Department of Bucknell University, Lewisburg, Pennsylvania. While being a faculty at Bucknell he spent the 2010/2011 academic year as a Marie Curie Incoming International Fellow at the Institute of Communication Acoustics, Ruhr-Universität Bochum, Germany. During the 2022/2023 academic year he was on sabbatical as a Guest Researcher at the Electronic Systems of Medical Engineering Department, Technische Universität Berlin, Germany. Prof. Nickel's research interests include signal processing, artificial intelligence, machine learning, and engineering education.
Dr. Alan Cheville Bucknell University [biography]

Alan Cheville studied optoelectronics and ultrafast optics at Rice University, followed by 14 years as a faculty member at Oklahoma State University working on terahertz frequencies and engineering education. While at Oklahoma State, he developed courses
Dr. Stu Thompson http://orcid.org/0000-0002-3444-8503 Bucknell University [biography]

Stu is an associate professor and chair of the department of Electrical and Computer Engineering at Bucknell University, in Lewisburg, PA. While his teaching responsibilities typically include digital design, computer-related electives, and senior design, his focus
Dr. Rebecca Thomas http://orcid.org/https://0000-0003-2426-4759 Bucknell University [biography]

Rebecca Thomas is the inaugural director for the Pathways Program at Bucknell University, where she oversees the rollout of Bucknell’s ePortfolio initiative. She is also an Associate Teaching Professor in the Department of Electrical and Computer Engineering. She holds a B.S. and M.Eng. in Electrical Engineering from the University of Louisville and a Ph.D. in Electrical Engineering from North Carolina State University.
Dr. Stewart Thomas http://orcid.org/0000-0002-5554-1475 Bucknell University [biography]

Stewart J. Thomas received the B.S. and M.Eng. in Electrical Engineering from the University of Louisville in Louisville, Kentucky in 2006 and 2008, respectively, and the Ph.D. in Electrical and Computer Engineering from Duke University in Durham, North Carolina in 2013. He has served on the organizing committee for the IEEE International Conference on RFID series since 2014, serving as the Executive Chair in 2022, with research interests in areas of low-power backscatter communications systems and IoT devices. He is also interested in capabilities-based frameworks for supporting engineering education. He is currently an Assistant Professor at Bucknell University in the Electrical and Computer Engineering Department, Lewisburg, PA USA.
Jenny Tilsen http://orcid.org/https://0000-0003-4301-3592 Bucknell University [biography]

Dr. Jenny Tilsen has a background in Science and Technology Studies and STEM Education. She is also the creator or STEMtelling, a pedagogical storytelling tool.
Sarah Appelhans http://orcid.org/0000-0002-7313-3504 Lafayette College [biography]

Sarah Appelhans is an Assistant Professor of Engineering Studies at Lafayette College. She earned her PhD in Cultural Anthropology at the University at Albany (SUNY) where she conducted research on the cultural factors that contribute to inequalities in engineering. As a postdoc at Bucknell University, she was the resident ethnographer in the Electrical and Computer Engineering Department, exploring applications of Amartya Sen’s capabilities approach in engineering education. Her current book project, On the Bleeding Edge: Gender, Immigration and Precarity in Semiconductor Engineering, investigates the intersections of gender, race/ethnicity, and immigration status among semiconductor engineers.
Philip Asare University of Toronto

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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