Colton's Research

Colton Harper (He/They)

Ph.D. Candidate
School of Computing
University of Nebraska-Lincoln
Lincoln, NE, 68508

Office: Schorr 114
Phone: (620) 931-7482
Email: colton.harper {at} huskers.unl.edu

Google Scholar Profile

About Me

Colton Harper is a Computer Science Ph.D. Candidate at the University of Nebraska-Lincoln (UNL), working under the guidance of Dr. Stephen Cooper. Colton's Ph.D. work is focused on designing and facilitating personalized learning strategies to make computing education more inclusive, engaging, and equitable for students in higher education.

Research Overview:

Colton employ's mixed methods approaches centered around iteratively developing conceptual learning and assessment tools in computing education. He is currently exploring the power of student-generated analogies as a teaching and learning tool for computing concepts. This work primarily draws from cognitive and educational theories including analogical reasoning, conceptual metaphor theory, culturally responsive pedagogy, and constructivism. His current aim is to investigate the potential of student-generated analogies in introductory computing courses, by providing both a theoretical basis and practical recommendations.

Colton's research journey began in 2015 as a freshman in the Molecular and Biochemical Telecommunication (MBiTe) Lab, under the guidance of Dr. Massimiliano Pierobon. As a member of the MBiTe Lab, Colton participated in the 2016 UNL iGEM synthetic biology team. Colton continued his work in the MBiTe Lab through Fall 2021, researching biomolecular communication, developing synthetic biological models, carrying out simulations, and applying information theory to measure, develop metrics, and engineer communication in biological cells. In Fall 2021, Colton's passion for teaching, education, and ethics led him to transition to computing education research under Dr. Stephen Cooper's supervision. Throughout his academic career, Colton has received funding and additional support from UCARE, REU, McNair, the Othmer Graduate Fellowship, and graduate research assistantships.

Broader Involvement:

Apart from his research, Colton is committed to help address the ethical and societal impacts of emerging technologies. He has worked closely with the UNL Ethics Center to establish and maintain a grassroots embedded ethics program for UNL's School of Computing, making it the first land-grant state university to develop such an initiative. This program integrates ethics education touchpoints throughout the degree curriculum, fostering a more ethically-aware computing student body and future professionals. Colton's technology ethics involvement also extends to his contributions as a cofounder, prior program chair and grant writer for Initialize UNL and the Broader Considerations of Technology student groups, and associate conference organizer for the inaugural 2019 Ethics and Broader Considerations of Technology Conference.

Education

Ph.D. Candidate in Computer Science, University of Nebraska-Lincoln, 2019-Present
B.Sc. in Computer Science, University of Nebraska-Lincoln, 2019

Research

Research Overview

My research focuses on innovative strategies that leverage students' prior knowledge and cultural capital for more effective and inclusive teaching of abstract computing concepts. I aim to bridge complex computing ideas with familiar contexts, making computing curricula more accessible, engaging, and equitable for learners.

Drawing on theories of analogical reasoning, conceptual metaphor theory, constructivism, and culturally responsive pedagogy, I develop practical tools and scaffolding techniques for introductory computing courses. This student-centered approach is intended to enhance engagement while promoting inclusivity by valuing diverse perspectives and cultural backgrounds in the classroom.

Current Research

Student-Generated Analogies

Currently, I am focusing on the iterative development of scaffolding techniques for student-generated analogies as both learning and assessment tools in computing education. Traditional instructor-provided analogies may not resonate with all students due to cultural differences. By empowering students to create their own analogies, my research helps bridge abstract computing concepts to their personal experiences and cultural backgrounds.

My work aims to:

Develop Effective Scaffolding Techniques: Guide students in generating meaningful analogies that enhance their understanding of complex concepts by drawing on their unique cultural capital.
Create Interpretative Frameworks for Instructors: Provide educators with tools to analyze student-generated analogies, offering insights into learners' conceptual understanding and cultural perspectives, and identifying areas needing additional support.
Evaluate Educational Impact: Assess how analogy-based learning influences student engagement, comprehension, and inclusivity in university-level courses and high school programs.

By exploring the alignment between student and instructor language through conceptual metaphor theory, this research seeks to facilitate more effective communication and knowledge transfer in the classroom. Promoting culturally responsive teaching practices enhances the educational experience for all students, particularly those from underrepresented groups.

My research seeks to foster a more inclusive and equitable computing education environment, empowering students to take charge of their learning and preparing them to become the next generation of computing professionals.

Publications

Harper, C., Mohammed, K., & Cooper, S. 2025. A Conceptual Metaphor Analysis of Recursion in a CS1 Course. In Proceedings of the 56th ACM Technical Symposium on Computer Science Education (SIGCSE '25). Accepted, to Appear.
Harper, C., & Enersen, A. 2024. Scaffolding Student-Generated Analogies in CS1. In Proceedings of the 2024 ACM Virtual Global Computing Education Conference Vol. 1 (SIGCSE Virtual '24), ACM. PDF
Harper, C., Tran, K., & Cooper, S. 2024. Conceptual Metaphor Theory in Action: Insights into Student Understanding of Computing Concepts. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE '24) (pp. 463-469). PDF
Harper, C., Rance, J., Owens, P., & Cooper, S. 2024. Tool-Driven Scaffolding of Student-Generated Analogies in CS1. In Proceedings of the 8th Conference on Computing Education Practice (CEP '23) (pp. 5-8).PDF
Harper, C., Bockmon, R., & Cooper, S. 2023. Investigating Themes of Student-Generated Analogies. In Proceedings of the ACM Conference on Global Computing Education Vol 1 (CompEd '23) (pp. 64-70).PDF
Harper, C. 2022. Developing and Evaluating Scaffolding for Student-Generated Analogies in CS1. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education Vol. 2 (ITiCSE '22). ACM, 656–657. (Doctoral Consortium Abstract) PDF
Ratti, F., Harper, C., Magarini, M., and Pierobon, M. 2021. Optimizing Information Transfer Through Chemical Channels in Molecular Communication. In 2021 IEEE Global Communications Conference (GLOBECOM '21). IEEE, 1–6. PDF
Harper, C., Pierobon, M., and Magarini, M. 2018. Estimating Information Exchange Performance of Engineered Cell-to-Cell Molecular Communications: A Computational Approach. In IEEE INFOCOM 2018 - IEEE Conference on Computer Communications (INFOCOM '18). IEEE, 729–737. PDF

Talks

Thompson, A., Harper, C., & Wrublewski, Z. (2023, March 2). Embedding Ethics Modules in Computer Science and Engineering Courses. Oral presentation at the 32nd Annual APPE International Conference, Portland, Oregon.
Harper, C., Pierobon, M. (2017, July). Analyzing Information Exchange of Engineered Communication Between Biological Cells. Oral presentation at the California McNair Scholars Symposium, University of California, Berkeley, Berkeley, California.
Harper, C., Bierman, M., Dooling, D., Mueller, J., Ninh, P., Schwabauer, B. (2016, October). Nitrate Reduction in Water Systems by Engineered E. coli. Oral presentation at the international Genetically Engineered Machines (iGEM) international conference, Hynes Convention Center, Boston, Massachusetts.

Teaching

CSCE 155T: Computer Science I: Informatics Focus

Fall 2022 & Fall 2023

Course Overview

This introductory course provided students with a solid foundation in computer science principles, computational problem solving, and data science using Python. Students with little or no prior programming experience were guided through topics including Python basics, functions, data structures, object-oriented programming, data processing, analysis, and visualization. The course also integrates some discussions and activities to help highlight the importance of ethical reasoning and the intersection of society and technology, particularly as it relates to data science, course topics, and timely recent events. Students engaged with the material through lectures, labs, and assignments to develop basic programming skills and understanding foundational computing concepts.

Link to Syllabus

View the course syllabus