Marian Petre
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Abstract
Many believe that visual programming techniques are quite close to developers. This article reports on some fascinating research focusing on understanding how textual and visual representations for software differ in effectiveness. Among other things, it is determined that the differences lie not so much in the textual-visual distinction as in the degree to which specific representations support the conventions experts expect.
- 1 Anzai, Y. Learning diagram-drawing and graphical reading skills: analysis and design. Presented to: Workshop on Graphical Representations, Reasoning, and Communication, AI-ED '93 (Edinburgh, August, 1993).Google Scholar
- 2 Bouwhuis, D. G. Reading as goal-driven behaviour. In B. A. G. Elsendoorn and H. Bouma, Eds., Working Models of Human Perception. Academic Press, 1988, pp. 341-362.Google Scholar
- 3 Chi, M.T.H., Glaser, R., and Farr, MJ., Eds. The Nature of Expertise. Erlbaum, Hillsdale, NJ, 1988.Google Scholar
- 4 Cleveland, W.S., and McGill, R. Graphical perception: theory, experimentation and application to the development of graphi cal methods.J. Amer. Statistical Assoc. 79, (1984), 531-554.Google ScholarCross Ref
- 5 Davies, S. P. Skill levels and strategic differences in plan comprehension and implementation in programming. In A. Sutcliffe and L. Macaulay, Eds., People and Computers V. Cambridge niversity Press, Cambridge, UK, 1989. Google ScholarDigital Library
- 6 Gibson, EJ., and Levin, H. The Psychology ofReading. MIT Press, Cambridge, Mass., 1975.Google Scholar
- 7 Gilmore, D.J., and Green, T. R. G. Programming plans and programming expertise. Quarterly j. of Experimental Psych. 40A (1988), 423-442.Google Scholar
- 8 Green, T.R.G., and Petre, M. When visual programs are harder to read than textual programs. In Proceedings of the Sixth European Conference on Cognitive Ergonomics (ECCE-6), Budapest, Hungary, September 1992.Google Scholar
- 9 Green, T. R. G., Petre, M., and Bellamy, R. K. E. Comprehensibility of visual and textual programs: A test of Superlativism against the "match-mismatch" conjecture. In Empirical Studies of Programmers Fourth Workshop. Ablex, 1991.Google Scholar
- 10 Horowitz, P., and Hill, W. The Art of Electronics. 2d ed. Cambridge University Press, Cambridge, UK, 1989. Google ScholarDigital Library
- 11 Koga, K., and Groner, R. Intercultural experiments as a research tool in the study of cognitive skill acquisition: Japanese character recognition and eye movements in non-Japanese subjects. In H. Mandl and J.R. Levin Eds., Knowledge Acquisition from Text and Pictures. North-Holland, 1989, 279-291.Google Scholar
- 12 Kosslyn, S.M. Imagery and internal representation. In E. Rosch and B.B. Lloyd, Eds., Cognition and Categorization. Erlbaum, Hillsdale, NJ, 1978, 227-286.Google Scholar
- 13 Mackinlay, J. Automating the design of graphical presentations of relational information. ACM TOGS5, 2 (1986), 110-141. Google ScholarDigital Library
- 14 Moher, T.G., Mak, D.C., Blumenthal, B., and Leventhal, L.M. Comparing the comprehensibility of textual and graphical programs: The case of Petri nets. In C.R. Cook, J.C. Scholtz, and J.C. Spohrer, Eds., Empirical Studies of Programmers: Fifth Workshop. Ablex, 1993, 137-161.Google Scholar
- 15 Myers, B.A. Taxonomies of visual programming and program visualization. JVLC 1, 1 (1990), 97123.Google ScholarDigital Library
- 16 Pennington, N. Stimulus structures and mental representations in expert comprehension of computer programs. Cognitive Psychology 19, (1987), 295-341.Google ScholarCross Ref
- 17 Petre, M., and Green, T. R. G. Where to draw the line with text: Some claims by logic designers about graphics in notation. In INTERACT'90 Conference on Computer-Human Interaction, 1990. Google ScholarDigital Library
- 18 Petre, M., and Green, T. R. G. Requirements of graphical notations for professional users: Electronics CAD systems as a case study. Le Travail Humain 55, 1 (1992), 47-70.Google Scholar
- 19 Petre, M., and Green, T.R.G. Learning to read graphics: some evidence that 'seeing' an information display is an acquired skill. Journal of Visual Languages and Computing 4 (1993), 55-70.Google ScholarCross Ref
- 20 Raymond, D. Characterizing visual languages. In The 1991 1EEE Workshop on Visual Languages, (1991) IEEE Computer Society Press.Google Scholar
- 21 Rohr, G. Using visual concepts. In S-K. Chang, T. Ichikawa and P.A. Ligomenides, Eds., Visual Languages. Plenum Press, 1986.Google Scholar
- 22 Shu, N.C. Visual Programming. Van Nostrand Reinhold, 1988. Google ScholarDigital Library
- 23 Sime, M.E., Green, T.R.G., and Guest, D.J. Scope marking in computer conditionals--A psychological evaluation. IJMMS 9, (1977) 107-118.Google Scholar
- 24 Swigger, K.M., and Brazile, R.P. An empirical study of the effects of design/documentation formats on expert system modifiability. In J. Joenemann-Belliveau, T. Moher, and S. Robertson, Eds., Empirical Studies of Programmers: Fourth Workshop, Ablex, 1991.Google Scholar
- 25 Treisman, A. Features and objects in visual processing. Scientific American (1986), 106-115. Google ScholarDigital Library
Index Terms
- Why looking isn't always seeing: readership skills and graphical programming
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