Driving Advances in Computing Education through
Application of Educational Psychology Principles
GVU Research Grant Proposal
By Richard Catrambone (School of Psychology)
and Mark Guzdial (School of Interactive Computing)
Problems Addressed
Computing education research is just emerging from its Dark Ages. In the 1970’s
and 1980’s, foundational research on how and why people learn computing was
conducted by researchers such as John Anderson (Anderson et al., 1993), Elliot
Soloway (Soloway, Bonar, & Ehrlich, 1983), and Seymour Papert (Papert, 1980).
Then the funding from NSF and ONR dried up, and the field nearly withered away.
Then in the early 2000’s, NSF realized that knowing more about how to teach
computing-informed workers was important to having computing-informed
workers, and a program was created to develop computing education researchers
from current computing teachers (Fincher & Petre, 2004). Now, there are new
journals (ACM’s Transactions on Computing Education Research) and conferences
(ACM’s International Computing Education Research workshop).
In the two Dark Decades, a great deal of research in educational psychology has
changed how we think about learning and teaching. For example, we know more
about how students learn from examples (Atkinson, Derry, Renkl, & Wortham, 2000;
Bielaczyc, Pirolli, & Brown, 1995; Catrambone, 1994, 1996), how to use multiple
media to reduce cognitive load (Mayer, 2009), and how to teach through student’s
inquiry (Kolodner et al., 2008). The new practitioners of computing education
research, coming out of computer science, are not well-equipped for drawing on
these findings in education, psychology, and learning sciences.
The proposed seed grant is focused on creating examples of computer science
instruction that are informed by modern educational psychology. In so doing, we
hope to create a kernel for growing a research program and providing a set of
papers that connect the computing education research community to new ideas in
education, psychology, and learning sciences.
Overall Approach
Richard Catrambone is an expert in how students learn from examples, how to
create instructions that lead to effective execution and transferable knowledge, and
how to analyze learning situations for defining instruction. Mark Guzdial is a leader
in computing education research. Mark provides a new context for Richard’s
expertise, and has visibility in his research community to draw attention to new
approaches.
Our approach is simple, for execution in a single year. With one of Richard’s new
students, we will develop multimedia instruction to teach a particular topic in
computer science. Our student audience will be in-service high school teachers who
wish to become computer science teachers – new funding in NSF aims to train 8,000
new computer science teachers in the next four years. Our topic will be something
small, but documented as hard for adults to learn, such as manipulation of basic
variables (Dorn, 2010) or looping and conditionals in The Rainfall Problem (Whalley
et al., 2006). We will explicitly choose the topic from those highlighted as critical in
the new Computer Science: Principles advanced placement course under
development1. In this way, we choose the most fundable audience and the most
relevant content. Our plan is to analyze the learning situation using Richard’s
methods, construct multimedia instruction using best-practices in educational
psychology, and evaluate that instruction with volunteer high school teachers as
study participants.
Benefits Anticipated
There are two goals for this project: (1) to demonstrate to the computing education
research community how modern educational psychology can inform computing
education instruction; and (2) to create the preliminary or pilot findings to support
funding. A recent NSF proposal was rejected due to a lack of pilot findings, and the
reviewers suggested something very much like the proposed work.
How the Grant will Enable Subsequent External Funding
There are now funding programs in the National Science Foundation for doing work
in computing education research. In particular, we refer to the Cyberlearning:
Transforming Education and the Computing Education in the 21st Century (CE21)
programs. However, it is hard to introduce new directions in these programs. Even
in the Cyberlearning “Exploratory” funding program, reviewers expect to see
“preliminary or pilot” results before providing funding, even when the “radical”
approach is simply applying educational psychology findings from one field to
computing education2. We hope to produce those preliminary results with GVUfunded research.
Outline of Required Budget
Half-time (20 hrs/week) psychology GRA for 9 months: $16,445; tuition remission
$954/month.
We expect to use the funding for a new PhD student working with Richard, Lauren
Margulieux.
http://www.csprinciples.org
http://computinged.wordpress.com/2011/06/28/the-high-cost-of-preparing-forproposals/
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2
References
Anderson, J. R., Conrad, F., Corbett, A. T., Fincham, J. M., Hoffman, D., & Wu, Q. (1993).
Computer programming and transfer. In J. R. Anderson (Ed.), Rules of Mind
(pp. 205-234). Hillsdale, NJ: Lawrence Erlbaum Associates.
Atkinson, R. K., Derry, S. J., Renkl, A., & Wortham, D. (2000). Learning from
Examples: Instructional Principles from the Worked Examples Research.
Review of the Educational Research, 70(2), 181-214.
Bielaczyc, K., Pirolli, P., & Brown, A. L. (1995). Training in self-explanation and selfregulation strategies: Investigating the effects of knowledge acquistion
activities on problem solving. Cognition and Instruction, 13, 221-252.
Catrambone, R. (1994). Improving examples to improve transfer to novel problems.
Memory and Cognition, 22, 605-615.
Catrambone, R. (1996). Generalizing solution procedures learned from examples.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 22,
1020-1031.
Dorn, B. J. (2010). A case-based approach for supporting the informal computing
education of end-user programmers. Georgia Institute of Technology, Atlanta,
GA.
Fincher, S., & Petre, M. (2004). Computer science education research: Routledge
Falmer.
Kolodner, J. L., Starr, M. L., Edelson, D., Hug, B., Krajcik, J., Lancaster, J., et al. (2008).
Implementing what we know about learning in a middle-school curriculum for
widespread dissemination: The Project-Based Inquiry Science (PBIS) Story.
Paper presented at the 2008 International Conference of the Learning
Sciences.
Mayer, R. (2009). Multimedia Learning, Second Edition (Second ed.). New York, NY:
Cambridge University Press.
Papert, S. (1980). Mindstorms. New York: Basic Books.
Soloway, E., Bonar, J., & Ehrlich, K. (1983). Cognitive strategies and looping
constructs: an empirical study. Commun. ACM, 26(11), 853-860.
Whalley, J. L., Lister, R., Thompson, E., Clear, T., Robbins, P., Kumar, P. K. A., et al.
(2006). An Australasian study of reading and comprehension skills in novice
programmers, using the bloom and SOLO taxonomies. Paper presented at the
Proceedings of the 8th Austalian conference on Computing education Volume 52.