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19 - Computing for Other Disciplines

from New Milieux

Published online by Cambridge University Press:  15 February 2019

Sally A. Fincher
Affiliation:
University of Kent, Canterbury
Anthony V. Robins
Affiliation:
University of Otago, New Zealand
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Summary

Most people who learn to program are not preparing to be professional software developers. This chapter considers the role of programming in disciplines other than computer science. Programming is a powerful notation for learning; an important tool in disciplines including mathematics, science, and engineering; and a productivity enhancement for many professionals. Programming has been promoted as a tool for general thinking and problem-solving benefits, which is considered in this chapter.
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Publisher: Cambridge University Press
Print publication year: 2019

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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 the Mind (pp. 205234). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Antoniu, T., Steckler, P. A., Krishnamurthi, S., Neuwirth, E., & Felleisen, M. (2004). Validating the unit correctness of spreadsheet programs. In Proceedings of the 26th International Conference on Software Engineering (pp. 439448). Hoboken, NJ: IEEE Computer Society.Google Scholar
Blikstein, P., & Wilensky, U. (2009). An atom is known by the company it keeps: A constructionist learning environment for materials science using agent-based modeling. International Journal of Computers for Mathematical Learning, 14, 81119.CrossRefGoogle Scholar
Brennan, K., Hernández, A. M., & Resnick, M. (2009). Scratch: Creating and sharing interactive media. In CSCL’09: Proceedings of the 9th International Conference on Computer Supported Collaborative Learning (p. 217). Boulder, CO: International Society of the Learning Sciences.Google Scholar
Carver, S. M. (1986). Transfer of LOGO Debugging Skill: Analysis, Instruction, and Assessment (PhD thesis). Carnegie Mellon University.Google Scholar
Carver, S. M., & Klahr, D. (1986). Assessing children’s LOGO debugging skills with a formal model. Journal of Educational Computing Research, 2, 487525.CrossRefGoogle Scholar
Diethelm, I., Hubwieser, P., & Klaus, R. (2012). Students, teachers and phenomena: educational reconstruction for computer science education. In Proceedings of the 12th Koli Calling International Conference on Computing Education Research (pp. 164173). New York: ACM.Google Scholar
Disessa, A. (2001). Changing Minds. Cambridge, MA: MIT Press.Google Scholar
Disessa, A. A. (1985). A principled design for an integrated computational environment. Human–Computer Interaction, 1, 147.Google Scholar
Disessa, A. A., & Abelson, H. (1986). Boxer: A reconstructible computational medium. Communications of the ACM, 29, 859868.Google Scholar
Dorn, B. (2011). ScriptABLE: Supporting informal learning with cases. In ICER ‘11: Proceedings of the Seventh International Workshop on Computing Education Research (pp. 6976). New York: ACM.Google Scholar
Dorn, B., & Guzdial, M. (2006). Graphic designers who program as informal computer science learners. In ICER ‘06: Proceedings of the Second International Workshop on Computing Education Research (pp. 127134). New York: ACM.Google Scholar
Dorn, B., & Guzdial, M. (2010). Discovering computing: Perspectives of web designers. In ICER ‘10: Proceedings of the Sixth International Workshop on Computing Education Research (pp. 2330). New York: ACM.Google Scholar
Dorn, B. J. (2012). A Case-based Approach for Supporting the Informal Computing Education of End-user Programmers (PhD thesis). College of Computing, Georgia Institute of Technology.Google Scholar
Eisenstadt, M. (1979). A friendly software environment for psychology students. Communications of the ACM, 26, 10581064.Google Scholar
Ensmenger, N. L. (2010). The Computer Boys Take Over: Computers, Programmers, and the Politics of Technical Expertise. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Ericson, B., Guzdial, M., & Biggers, M. (2005). A model for improving secondary CS education. In SIGCSE ‘05: Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education (pp. 332336). New York: ACM.Google Scholar
Ericson, B., Guzdial, M., & Biggers, M. (2007). Improving secondary CS education: Progress and problems. SIGCSE Bulletin, 39, 298301.Google Scholar
Felleisen, M., & Krishnamurthi, S. (2009). Viewpoint: Why computer science doesn’t matter. Communications of the ACM, 52, 3740.CrossRefGoogle Scholar
Fincher, S., Cooper, S., Kölling, M., & Maloney, J. (2010). Comparing Alice, Greenfoot, & Scratch. In SIGCSE ‘10: Proceedings of the 41st ACM Technical Symposium on Computer Science Education (pp. 192193). New York: ACM.Google Scholar
Flanagan, D. (2006). JavaScript: The Definitive Guide. Newton, MA: O’Reilly Media, Inc.Google Scholar
Forte, A., & Guzdial, M. (2004). Computers for communication, not calculation: Media as a motivation and context for learning. In Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS’04) – Track 4 – Volume 4 (p. 10) Hoboken, NJ: IEEE Computer Society.Google Scholar
Forte, A., & Guzdial, M. (2005). Motivation and non-majors in computer science: Identifying discrete audiences for introductory courses. IEEE Transactions on Education, 48, 248253.Google Scholar
Green, T. R. G., & Petre, M. 1992. When visual programs are harder to read than textual programs. In Veer, G. C. V. D., Tauber, M. J., Bagnarola, S., & Antavolits, M. (Eds.), Human–Computer Interaction: Tasks and Organisation, Proceedings EECE-6 (6th European Conference on Cognitive Ergonomics) (pp. 167180) Rome, Italy: CUD.Google Scholar
Green, T. R. G., & Petre, M. (1996). Usability analysis of visual programming environments: A “cognitive dimensions” framework. Journal of Visual Languages and Computing, 7, 131174.Google Scholar
Green, T. R. G., Petre, M., & Bellamy, R. K. E. 1991. Comprehensibility of visual and textual programs: A test of “superlativism” against the “match–mismatch” conjecture. In Koenemann-Belliveau, J., Moher, T., & Robertson, S. (Eds.), Empirical Studies of Programmers: Fourth Workshop (pp. 121146). Norwood, NJ: Ablex.Google Scholar
Guo, Y., Wagh, A., Brady, C., Levy, S. T., Horn, M. S., & Wilensky, U. (2016). Frogs to think with: Improving students’ computational thinking and understanding of evolution in a code-first learning environment. In Proceedings of the 15th International Conference on Interaction Design and Children (pp. 246254). New York: ACM.CrossRefGoogle Scholar
Guzdial, M. (1995). Software-realized scaffolding to facilitate programming for science learning. Interactive Learning Environments, 4, 144.Google Scholar
Guzdial, M. (2003). A media computation course for non-majors. SIGCSE Bulletin, 35, 104108.CrossRefGoogle Scholar
Guzdial, M. (2009). Education: Teaching computing to everyone. Communications of the ACM, 52, 3133.Google Scholar
Guzdial, M. (2013). Exploring hypotheses about media computation. In Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research (pp. 1926). New York: ACM.Google Scholar
Guzdial, M. (2015). Learner-Centered Design of Computing Education: Research on Computing for Everyone. San Rafael, CA: Morgan & Claypool Publishers.Google Scholar
Guzdial, M., & Forte, A. (2005). Design process for a non-majors computing course. SIGCSE Bulletin, 37, 361365.CrossRefGoogle Scholar
Guzdial, M., & Tew, A. E. (2006). Imagineering inauthentic legitimate peripheral participation: An instructional design approach for motivating computing education. In Proceedings of the Second International Workshop on Computing Education Research (pp. 5158). New York: ACM.Google Scholar
Harel, I., & Papert, S. (1990). Software design as a learning environment. Interactive Learning Environments, 1, 132.CrossRefGoogle Scholar
Hewner, M., & Guzdial, M. (2008). Attitudes about computing in postsecondary graduates. In ICER ‘08: Proceeding of the Fourth International Workshop on Computing Education Research (pp. 7178). New York: ACM.Google Scholar
Hubwieser, P. (2012). Computer science education in secondary schools – The introduction of a new compulsory subject. Transactions on Computing Education, 12, 16:1–16:41.Google Scholar
Humphreys, P. (2004). Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford, UK: Oxford University Press.Google Scholar
Hundhausen, C. D., Farley, S., & Brown, J. L. (2006). Can direct manipulation lower the barriers to programming and promote positive transfer to textual programming? An experimental study. In Visual Languages and Human-Centric Computing, 2006. VL/HCC 2006 (pp. 157164). Hoboken, NJ: IEEE.Google Scholar
Kafai, Y. B. (1995). Minds in Play: Computer Game Design As a Context for Children’s Learning. Abingdon, UK: Routledge.Google Scholar
Kafai, Y. B. (1998). Video game designs by girls and boys: Variability and consistency of gender differences. In From Barbie to Mortal Kombat: Gender and Computer Games (pp. 90114). Cambridge, MA: MIT Press.Google Scholar
Kafai, Y. B., & Ching, C. C. (2001). Affordances of collaborative software design planning for elementary students’ science talk. Journal of the Learning Sciences, 10, 321363.Google Scholar
Kafai, Y. B., Lee, E., Searle, K., Fields, D., Kaplan, E., & Lui, D. (2014). A crafts-oriented approach to computing in high school: Introducing computational concepts, practices, and perspectives with electronic textiles. Transactions on Computing Education, 14, 120.Google Scholar
Katz, E. E., & Porter, H. S. (1991). HyperTalk as an overture to CS1. SIGCSE Bulletin, 23, 4854.Google Scholar
Kay, A., & Goldberg, A. (1977). Personal dynamic media. Computer, 10(3), 3141.CrossRefGoogle Scholar
Kay, A. C. (1972). A personal computer for children of all ages. In Proceedings of the ACM Annual Conference – Volume 1. New York: ACM.Google Scholar
Kay, A. C. (1993). The early history of Smalltalk. In The Second ACM SIGPLAN Conference on History of Programming Languages (pp. 6995). New York: ACM.CrossRefGoogle Scholar
Kemeny, J. G., & Kurtz, T. E. (1980). Basic Programming. Hoboken, NJ: John Wiley & Sons, Inc.Google Scholar
Kemeny, J. G., & Kurtz, T. E. (1985). Back to Basic: The History, Corruption, and Future of the Language. Boston, MA: Addison-Wesley Longman Publishing Co., Inc.Google Scholar
Klahr, D., & Carver, S. M. (1988). Cognitive objectives in a LOGO debugging curriculum: Instruction, learning, and transfer. Cognitive Psychology, 20, 362404.Google Scholar
Ko, A. J., Abraham, R., Beckwith, L., Blackwell, A., Burnett, M., Erwig, M., Scaffidi, C., Lawrance, J., Lieberman, H., & Myers, B. (2011). The state of the art in end-user software engineering. ACM Computing Surveys (CSUR), 43(3), 21.Google Scholar
Koushik, V., & Lewis, C. (2016). An accessible blocks language: Work in progress. In Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (pp. 317318). New York: ACM.Google Scholar
Kurland, D. M., Pea, R. D., Clement, C., & Mawby, R. (1986). A study of the development of programming ability and thinking skills in high school students. Journal of Educational Computing Research, 2, 429458.Google Scholar
Lave, J., & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. New York: Cambridge University Press.Google Scholar
Lee, C. B. (2013). Experience report: CS1 in MATLAB for non-majors, with media computation and peer instruction. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education (pp. 3540). New York: ACM.Google Scholar
Maloney, J. H., Peppler, K., Kafai, Y., Resnick, M., & Rusk, N. (2008a). Programming by choice: Urban youth learning programming with Scratch. In SIGCSE ‘08: Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (pp. 367371). New York: ACM.Google Scholar
Maloney, J., Resnick, M., Rusk, N., Peppler, K. A., & Kafai, Y. B. (2008b). Media designs with Scratch: What urban youth can learn about programming in a computer clubhouse. In ICLS’08: Proceedings of the 8th International Conference for the Learning Sciences (pp. 8182). Utrecht, The Netherlands: International Society of the Learning Sciences.Google Scholar
Maloney, J., Resnick, M., Rusk, N., Silverman, B., & Eastmond, E. (2010). The Scratch programming language and environment. Transactions on Computing Education, 10, 16:1–16:15.Google Scholar
Miller, L. A. (1974). Programming by non-programmers. International Journal of Man–Machine Studies, 6, 237260.Google Scholar
Miller, L. A. (1981). Natural language programming: Styles, strategies, and contrasts. IBM Systems Journal, 29, 184215.Google Scholar
Myers, B. A., Pane, J. F., & Ko, A. (2004). Natural programming languages and environments. Communications of the ACM, 47, 4752.Google Scholar
Ni, L. (2009). What makes CS teachers change?: Factors influencing CS teachers’ adoption of curriculum innovations. In SIGCSE ‘09: Proceedings of the 40th ACM Technical Symposium on Computer Science Education (pp. 544548). New York: ACM.CrossRefGoogle Scholar
Ni, L. (2011). Building Professional Identity as Computer Science Teachers: Supporting High School Computer Science Teachers Through Reflection and Community Building (PhD thesis). Georgia Institute of Technology.Google Scholar
Ni, L., & Guzdial, M. (2011). Prepare and support computer science (CS) teachers: Understanding CS teachers’ professional identity. In American Educational Research Association (AERA) Annual Meeting. New Orleans, LA: AERA.Google Scholar
Noss, R., & Hoyles, C. (1996). Windows on Mathematical Meanings: Learning Cultures and Computers. Rotterdam, The Netherlands: Springer Science & Business Media.Google Scholar
Olson, G. M., Catrambone, R., & Soloway, E. (1987). Programming and algebra word problems: a failure to transfer. In Empirical Studies of Programmers Workshop (pp. 113). Norwood, NJ: Ablex Publishing Corp.Google Scholar
Palumbo, D. J. (1990). Programming language/problem-solving research: A review of relevant issues. Review of Educational Research, 60(1), 6589.Google Scholar
Pane, J. F., Ratanamahatana, C., & Myers, B. (2001). Studying the language and structure in non-programmers’ solutions to programming problems. International Journal of Human–Computer Studies, 54(2), 237264.Google Scholar
Papert, S. (1972). Teaching children to be mathematicians versus teaching about mathematics. International Journal of Mathematical Education in Science and Technology, 3(3), 249262.Google Scholar
Papert, S. (1980). Mindstorms: Children, Computers, and Powerful Ideas. New York: Basic Books.Google Scholar
Papert, S. (1987). Information technology and education: Computer criticism vs. technocentric thinking. Educational Researcher, 16, 2230.Google Scholar
Papert, S. (1991). Situating constructionism. In Harel, I. & Papert, S. (Eds.), Constructionism (pp. 111). Norwood, NJ: Ablex Publishing Corp.Google Scholar
Papert, S. (1997). Why school reform is impossible. Journal of the Learning Sciences, 6(4), 417427.Google Scholar
Papert, S. A., & Solomon, C. (1971). Twenty Things to Do with a Computer. Retrieved from https://dspace.mit.edu/handle/1721.1/5836Google Scholar
Pasternak, A., & Vahrenhold, J. (2010). Braided teaching in secondary CS education: Contexts, continuity, and the role of programming. In Proceedings of the 41st ACM Technical Symposium on Computer Science Education (pp. 204208). New York: ACM.Google Scholar
Pea, R. D. (1987). The aims of software criticism: Reply to Professor Papert. Educational Researcher, 16, 48.Google Scholar
Pea, R. D., & Kurland, D. M. (1984). On the cognitive effects of learning computer programming. New Ideas in Psychology, 2(2), 137168.Google Scholar
Pea, R. D., Kurland, D. M., & Hawkins, J. (1985). Logo programming and the development of thinking skills. Technical Report 16. Retrieved from https://eric.ed.gov/?id=ED249930Google Scholar
Perlis, A. J. (1962). The computer in the iniversity. In Greenberger, M. (Ed.), Computers and the World of the Future (pp. 180217). Cambridge, MA: MIT Press.Google Scholar
Pirolli, P., & Recker, M. (1994). Learning strategies and transfer in the domain of programming. Cognition and Instruction, 12, 235275.CrossRefGoogle Scholar
Resnick, M. (1994). Turtles, Termites, and Traffic Jams: Explorations in Massively Parallel Microworlds. Cambridge, MA: MIT Press.Google Scholar
Resnick, M., Maloney, J., Monroy-Herández, A., Rusk, , Eastmond, N., Brennan, E., Millner, K., Rosenbaum, A., Silver, E., Silverman, J., , B., & Kafai, Y. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 6067.Google Scholar
Resnick, M., Martin, F., Berg, R., Borovoy, R., Colella, V., Kramer, K., & Silverman, B. (1998). Digital manipulatives: new toys to think with. In CHI ‘98: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 281287). Los Angeles, CA: ACM Press/Addison-Wesley Publishing Co.Google Scholar
Rich, L., Perry, H., & Guzdial, M. (2004). A CS1 course designed to address interests of women. In Proceedings of the 35th SIGCSE Technical Symposium on Computer Science Education (pp. 190194). New York: ACM.CrossRefGoogle Scholar
Scaffidi, C. (2017). Workers who use spreadsheets and who program earn more than similar works who do neither. In VL/HCC 2017 (pp. 233237). Hoboken, NJ: IEEE.Google Scholar
Scaffidi, C., Shaw, M., & Myers, B. (2005). An approach for categorizing end user programmers to guide software engineering research. SIGSOFT Software Engineering Notes, 30, 15.Google Scholar
Schanzer, E., Fisler, K., Krishnamurthi, S., & Felleisen, M. (2015). Transferring skills at solving word problems from computing to algebra through Bootstrap. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (pp. 616621). New York: ACM.Google Scholar
Schanzer, E., Fisler, K., & Krishnamurthi, S. (2018). Assessing Bootstrap: Algebra students on scaffolded and unscaffolded word problems. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (pp. 813). New York: ACM.Google Scholar
Schon, D. A. (1987). Educating the Reflective Practitioner. Hoboken, NJ: Jossey-Bass.Google Scholar
Searle, K. A., & Kafai, Y. B. (2015). Boys’ needlework: Understanding gendered and indigenous perspectives on computing and crafting with electronic textiles. In ICER ‘15: Proceedings of the Eleventh Annual International Conference on International Computing Education Research (pp. 3139). New York: ACM.CrossRefGoogle Scholar
Shaffer, D. W., & Resnick, M. (1999). “Thick’’ authenticity: New media and authentic learning. Journal of Interactive Learning Research, 10, 195215.Google Scholar
Sherin, B. L. (2001). A comparison of programming languages and algebraic notation as expressive languages for physics. International Journal of Computers for Mathematical Learning, 6, 161.Google Scholar
Simon, B., Chen, T.-Y., Lewandowski, G., McCartney, R., & Sanders, K. (2006). Commonsense computing: What students know before we teach (Episode 1: Sorting). In Proceedings of the Second International Workshop on Computing Education Research (pp. 2940). New York: ACM.Google Scholar
Simon, B., Kinnunen, P., Porter, L., & Zazkis, D. (2010). Experience report: CS1 for majors with media computation. In Proceedings of the Fifteenth Annual Conference on Innovation and Technology in Computer Science Education (pp. 214218). New York: ACM.Google Scholar
Sloan, R. H., & Troy, P. (2008). CS 0.5: A better approach to introductory computer science for majors. In Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (pp. 271275). New York: ACM.Google Scholar
Smith, D. C., Cypher, A., & Schmucker, K. (1996). Making programming easier for children. Interactions, 3, 5867.Google Scholar
Sweller, J., Clark, R., & Kirschner, P. (2010). Teaching general problem-solving skills is not a substitute for, or a viable addition to, teaching mathematics. Notices of the AMS, 57, 13031304.Google Scholar
Taylor, R. (Ed.) (1980). The Computer in the School: Tutor, Tool, Tutee. New York: Teachers College Press.Google Scholar
Vasudevan, V., Kafai, Y., & Yang, L. (2015). Make, wear, play: Remix designs of wearable controllers for scratch games by middle school youth. In IDC ‘15: Proceedings of the 14th International Conference on Interaction Design and Children (pp. 339342). New York: ACM.Google Scholar
Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127147.Google Scholar
Weintrop, D., & Wilensky, U. (2015a). Using commutative assessments to compare conceptual understanding in blocks-based and text-based programs. In Proceedings of the Eleventh Snnual International Conference on International Computing Education Research (pp. 101110). New York: ACM.Google Scholar
Weintrop, D., & Wilensky, U. (2015b). To block or not to block, that is the question: Students’ perceptions of blocks-based programming. In Proceedings of the 14th International Conference on Interaction Design and Children (pp. 199208). New York: ACM.Google Scholar
Weintrop, D., & Wilensky, U. (2017). Comparing block-based and text-based programming in high school computer science classrooms. Transactions on Computing Education, 18(1), 125.Google Scholar
Whitehead, C., Ray, L., Khan, S., Summers, W., & Obando, R. (2011). Implementing a computer science endorsement program for secondary school teachers. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education (pp. 547552). New York: ACM.Google Scholar
Wilensky, U., Brady, C. E., & Horn, M. S. (2014). Fostering computational literacy in science classrooms. Communications of the ACM, 57, 2428.Google Scholar
Wilensky, U., & Rand, W. (2015). An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo. Cambridge, MA: MIT Press.Google Scholar
Wilkerson-Jerde, M., Wagh, A., & Wilensky, U. R. I. (2015). Balancing curricular and pedagogical needs in computational construction kits: Lessons From the DeltaTick Project. Science Education, 99(3), 465499.Google Scholar
Wilson, G. (2016). Software Carpentry: Lessons learned. F1000Research. Retrieved from www.ncbi.nlm.nih.gov/pmc/articles/PMC3976103/Google Scholar
Wing, J. (2010). Computational Thinking: What and Why. The Link. Carnegie Mellon University. Retrieved from www.cs.cmu.edu/link/research-notebook-computational-thinking-what-and-whyGoogle Scholar
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49, 3335.Google Scholar
Wolf, M. (2007). Proust and the Squid: The Story and Science of the Reading Brain. New York: Harper Collins.Google Scholar

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