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Christopher D. Hundhausen

Christopher D. Hundhausen

D-Index & Metrics

Computer Science

D-Index
30
Citations
4573
World Ranking
14001
National Ranking
5563

Overview

Christopher D. Hundhausen is affiliated with Oregon State University in the United States. Their research primarily focuses on areas within computer science, particularly software engineering techniques and practices, software engineering research, online learning and analytics, innovative teaching and learning methods, open source software innovations, teaching and learning programming, and online and blended learning.

Their work spans multiple subfields including information systems, computer science applications, developmental and educational psychology, and education.

Hundhausen has published several recent papers in reputable venues. These include:

  • Combining GitHub, Chat, and Peer Evaluation Data to Assess Individual Contributions to Team Software Development Projects (2023, ACM Transactions on Computing Education)
  • Assessing individual contributions to software engineering projects: a replication study (2022, Computer Science Education)
  • Designing IDE Interventions to Promote Social Interaction and Improved Programming Outcomes in Early Computing Courses (2021, ACM Transactions on Computing Education)
  • HELPd Empathy Tool: A Tool for Generating Emotional Learning Process Data-based Interventions to Support Community Building in Computing Courses (2025, ACM Transactions on Computing Education)
  • Comprehension-Performance Gap in GenAI-Assisted Brownfield Programming: A Replication and Extension (2025, arXiv (Cornell University))

Their frequent coauthors reflect collaboration across related domains. Notable collaborators include:

  • Olusola Adesope
  • Phillip Conrad
  • Ahsun Tariq
  • A.S. Carter
  • Daniel Olivares

Christopher D. Hundhausen has contributed frequently to several publication venues. These include:

  • ACM Transactions on Computing Education (3 publications)
  • Computer Science Education (1 publication)
  • arXiv (Cornell University) (1 publication)

The scientist's research topics range across multiple aspects of software engineering and education:

  • Software Engineering Techniques and Practices
  • Software Engineering Research
  • Online Learning and Analytics
  • Innovative Teaching and Learning Methods
  • Open Source Software Innovations
  • Teaching and Learning Programming
  • Online and Blended Learning

Christopher D. Hundhausen's body of work integrates aspects of computing education with empirical software engineering, often using data-driven methods to assess individual and collaborative contributions in software development. The research also explores educational tools and interventions designed to improve programming outcomes and community building within computing courses.

Best Publications

  • A Meta-Study of Algorithm Visualization Effectiveness

    Christopher D. Hundhausen;Sarah A. Douglas;John T. Stasko

  • Exploring the role of visualization and engagement in computer science education

    Thomas L. Naps;Guido Rößling;Vicki Almstrum;Wanda Dann

  • An Experimental Study of the Effects of Representational Guidance on Collaborative Learning Processes.

    Daniel D. Suthers;Christopher D. Hundhausen

  • Learning by Constructing Collaborative Representations: An Empirical Comparison of Three Alternatives.

    Daniel D. Suthers;Christopher D. Hundhausen

  • An Empirical Study of the Effects of Representational Guidance on Collaborative Learning.

    Daniel D. Suthers;Christopher Hundhausen

  • The Normalized Programming State Model: Predicting Student Performance in Computing Courses Based on Programming Behavior

    Adam S. Carter;Christopher D. Hundhausen;Olusola Adesope

  • What You See Is What You Code: A live algorithm development and visualization environment for novice learners

    Christopher D. Hundhausen;Jonathan L. Brown

  • Exploring studio-based instructional models for computing education

    Christopher D. Hundhausen;N Hari Narayanan;Martha E. Crosby

  • Integrating algorithm visualization technology into an undergraduate algorithms course: ethnographic studies of a social constructivist approach

    Christopher D. Hundhausen

  • Comparing the roles of representations in face-to-face and online computer supported collaborative learning

    Daniel D. Suthers;Christopher D. Hundhausen;Laura E. Girardeau

  • On the design of an educational infrastructure for the blind and visually impaired in computer science

    Andreas M. Stefik;Christopher Hundhausen;Derrick Smith

  • Talking about code: Integrating pedagogical code reviews into early computing courses

    Christopher D. Hundhausen;Anukrati Agrawal;Pawan Agarwal

  • Deictic Roles of External Representations in Face-to-Face and Online Collaboration

    Daniel D. Suthers;Laura E. Girardeau;Christopher D. Hundhausen

  • Using visualizations to learn algorithms: should students construct their own, or view an expert's?

    C. Hundhausen;S. Douglas

  • Can direct manipulation lower the barriers to computer programming and promote transfer of training?: An experimental study

    Christopher D. Hundhausen;Sean F. Farley;Jonathan L. Brown

  • An Empirical Study of the “Prototype Walkthrough”: A Studio-Based Activity for HCI Education

    C. D. Hundhausen;D. Fairbrother;M. Petre

  • Blending Measures of Programming and Social Behavior into Predictive Models of Student Achievement in Early Computing Courses

    Adam S. Carter;Christopher D. Hundhausen;Olusola Adesope

  • Integrating pedagogical code reviews into a CS 1 course: an empirical study

    Christopher Hundhausen;Anukrati Agrawal;Dana Fairbrother;Michael Trevisan

  • Designing, visualizing, and discussing algorithms within a CS 1 studio experience: An empirical study

    Christopher D. Hundhausen;Jonathan L. Brown

  • An experimental study of the impact of visual semantic feedback on novice programming

    Christopher D. Hundhausen;Jonathan Lee Brown

  • An empirical investigation into the design of auditory cues to enhance computer program comprehension

    Andreas Stefik;Christopher Hundhausen;Robert Patterson

  • Does studio-based instruction work in CS 1?: an empirical comparison with a traditional approach

    Christopher Hundhausen;Anukrati Agrawal;Dana Fairbrother;Michael Trevisan

  • IDE-Based Learning Analytics for Computing Education: A Process Model, Critical Review, and Research Agenda

    C. D. Hundhausen;D. M. Olivares;A. S. Carter

Frequent Co-Authors

Daniel D. Suthers
Daniel D. Suthers University of Hawaii at Manoa
Rainer Koschke
Rainer Koschke University of Bremen
Alexandru Telea
Alexandru Telea Utrecht University
Marian Petre
Marian Petre The Open University
Beth Simon
Beth Simon University of California, San Diego
John Stasko
John Stasko Georgia Institute of Technology
Diane J. Cook
Diane J. Cook Washington State University
Mark Guzdial
Mark Guzdial University of Michigan–Ann Arbor
Dragan Gasevic
Dragan Gasevic Monash University
Maureen Schmitter-Edgecombe
Maureen Schmitter-Edgecombe Washington State University

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