Craig S. Miller
Professor

School of Computing
DePaul University

Research

My research includes the areas of Cognitive Science, Human-Computer Interaction, and Computing Education. Selected publications from each area appear below. A nearly comprehensive list is available on Google Scholar. Most of the research involves the study of human learning and problem solving through the construction and evaluation of cognitive models, often realized as working computer programs.

Computing Education

  • Craig S. Miller and Amber Settle (2021). Mixing and Matching Loop Strategies: By Value or By Index? In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE '21). Association for Computing Machinery, New York, NY, USA, 1048–1054. DOI:https://doi.org/10.1145/3408877.3432368
  • Sally Fincher, Johan Jeuring, Craig S. Miller, Peter Donaldson, Benedict du Boulay, Matthias Hauswirth, Arto Hellas, Felienne Hermans, Colleen Lewis, Andreas Mühling, Janice L. Pearce, and Andrew Petersen (2020). Notional Machines in Computing Education: The Education of Attention. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR '20). Association for Computing Machinery, New York, NY, USA, 21–50. DOI:https://doi.org/10.1145/3437800.3439202.
  • C. S. Miller and A. Settle (2019). Learning to Get Literal: Investigating Reference-Point Difficulties in Novice Programming. ACM Transactions on Computing Education (TOCE), Volume 19, Issue 3, 17 pages. Document link.
  • C. S. Miller and A. Settle (2016). Some Trouble with Transparency: An Analysis of Student Errors with Object-oriented Python. In ICER '16 Proceedings of the 2016 ACM Conference on International Computing Education Research. ACM, New York, NY, USA, 133-141. Document link.
  • Craig S. Miller (2015). Usability Evaluation: Learning When Method Findings Converge--And When They Don't. In Proceedings of the 16th Annual Conference on Information Technology Education (SIGITE '15). ACM, New York, NY, USA, 167-172. Document link.
  • C. S. Miller, A. Settle, and J. Lalor (2015). Learning Object-Oriented Programming in Python: Towards an Inventory of Difficulties and Testing Pitfalls. In Proceedings of the 16th Annual Conference on Information Technology Education (SIGITE '15). ACM, New York, NY, USA, 59-64. Document link.
  • C. S. Miller and R. Connolly (2015). Introduction to the Special Issue on Web Development. Trans. Comput. Educ. 15, 1, Article 1 (March 2015). Document link.
  • A. Vihavainen, C. S. Miller, and A. Settle (2015). Benefits of self-explanation in introductory programming. In SIGCSE 2015: The Proceedings of the 45th Annual SIGCSE Technical Symposium on Computer Science Education. Document link.
  • C. S. Miller (2014). Metonymy and reference-point errors in novice programming. Computer Science Education, 24(3). This is an Accepted Manuscript of an article published by Taylor & Francis Group in Computer Science Education to appear in September 2014 and online: http://www.tandfonline.com/10.1080/08993408.2014.952500
  • A. Settle, A. Vihavainen, and C. S. Miller (2014). Research directions for teaching programming online. In FECS 2014: The International Conference on Frontiers in Education: Computer Science and Computer Engineering. Document link.
  • Craig S. Miller, Jack Zheng, Randy Connolly, and Amos Olagunju. 2013. Keeping up with web development trends. In Proceedings of the 14th annual ACM SIGITE conference on Information technology education (SIGITE '13). ACM, New York, NY, USA, 59-60. Document link
  • C. S. Miller. (2012). Metonymic errors in a web development course. In Proceedings of the 13th Annual Conference on Information Technology Education (SIGITE '12). ACM, New York, NY, USA, 65-70. Document link
  • C. S. Miller and A. Settle. (2011). When Practice Doesn't Make Perfect: Effects of Task Goals on Learning Computing Concepts. ACM Transactions on Computing Education (TOCE) 11 (4), 22. Document link
  • C. S. Miller, L. Perkovic and A. Settle. (2010). File references, trees, and computational thinking. Proceedings of the fifteenth annual conference on Innovation and technology in computer science education (pp. 132 - 135). ACM. Document link
  • C. S. Miller and L. Dettori. (2008). Employers' perspectives on IT learning outcomes. In Proceedings of the 9th ACM SIGITE Conference on information Technology Education (pp. 213-218). SIGITE '08. New York, NY: ACM. Document link
  • G. Braught, C. S. Miller and D. Reed. Core Empirical Concepts and Skills for Computer Science. In Proceedings of the 35th SIGCSE Technical Symposium on Computer Science Education, ACM Press, 2004. Document link.
  • C. S. Miller (2003). Relating Theory to Actual Results in Computer Science and Human-Computer Interaction. Computer Science Education, 13, 227 - 240. Document link at publisher's Web site.
  • David Reed, Craig Miller, and Grant Braught. Empirical Investigation throughout the CS Curriculum. In Proceedings of the 31st SIGCSE Technical Symposium on Computer Science Education, Haller (ed.), ACM Press, 2000. Document link.

Human-Computer Interaction

  • R. C. Omanson, C. S. Miller and S. V. Joseph. (2014). Effects of Item Grouping on Selection Efficiency. In the Human Factors and Ergonomics Society Annual Meeting Proceedings. Human Factors and Ergonomics Society. Document link
  • C. S. Miller. (2011). Item Sampling for Information Architecture. In Proceedings of the SIGCHI conference on Human factors in computing systems (CHI 2011). Document link
  • C. S. Miller, S. Denkov and R. C. Omanson. (2011). Categorization Costs for Hierarchical Keyboard Commands. In Proceedings of the SIGCHI conference on Human factors in computing systems (CHI 2011). Document link
  • R. C. Omanson, C. S. Miller, E. Young and D. Schwantes. (2010). Comparison of Mouse and Keyboard Efficiency. Human Factors and Ergonomics Society Annual Meeting Proceedings (pp. 600 - 604). Human Factors and Ergonomics Society. Document link
  • S. Wu and C. S. Miller (2008). Top-down and bottom-up processes in web search navigation. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 64-70). Download PDF file
  • S. Wu and C. S. Miller. (2007). Preliminary evidence for top-down and bottom-up processes in web search navigation. In CHI '07 Extended Abstracts on Human Factors in Computing Systems (San Jose, CA, USA, April 28 - May 03, 2007). CHI '07. ACM Press, New York, NY, 2765-2770. Download PDF file. ACM document link.
  • C. S. Miller, S. Fuchs, N. S. Anantharaman, P. Kulkarni (2007). Evaluating Category Membership for Information Architecture, January 2007. DePaul CTI Technical Report 07-001. Download PDF file. A condensed version of this paper, entitled Comparing Two Methods for Predicting Navigation, appears in the Conference of the Human Factors and Ergonomics Society (HFES) in October, 2007. Document link
  • C. S. Miller, Modeling Web Navigation: Methods and Challenges, Lecture Notes in Computer Science, Volume 3169, Nov 2005, Pages 37 - 52. Download article. Document link at publisher's site.
  • C. S. Miller and R. W. Remington (2004). Modeling information navigation: Implications for information architecture. Human-Computer Interaction, 19, 225-271. Document link at publisher's site.
  • C. S. Miller and R. W. Remington. Effects of structure and label ambiguity on information navigation. In CHI 2002, Conference on Human Factors in Computing Systems, pp. 630-631, ACM Press, 2002. Download PDF file.
  • C. S. Miller and R. W. Remington. A computational model of Web navigation: Exploring interactions between hierarchical depth and link ambiguity. In the proceedings of The 6th Conference on Human Factors and the Web, 2000. View HTML file.

Cognitive Science

  • S. Wu and C. S. Miller (2008). Top-down and bottom-up processes in web search navigation. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp. 64-70). Download PDF file
  • C. S. Miller and R. W. Remington. Modeling an opportunistic strategy for information navigation. In Proceedings of the Twenty-Third Conference of the Cognitive Science Society, Lawrence Erlbaum Associates, 2001. Download PDF file.
  • Miller, C. S., Lehman, J. F. and Koedinger, K. R. (1999). Goals and Learning in Microworlds. Cognitive Science, 23, 305-336. Download PDF
  • Miller, C. S. & Laird, J. E. (1996). Accounting for graded performance within a discrete search framework. Cognitive Science, 20, 499-537. Download PDF
  • Miller, C. S. (1997) The Source and Character of Graded Performance in a Symbolic Rule-based Model. In Proceedings of the Nineteenth Annual Conference of the Cognitive Science Society, pp. 514-518.