Visualizing roles of variables in program animation

Information Visualization

Volumn 3, Issue 3, 1997, Pages 137-153

  Sajaniemi, Jorma ^a   Kuittinen, Marja ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

classroom experiment; Program animation; roles of variables

Indexed keywords

EID: 84993736251     PISSN: 14738716     EISSN: 14738724     Source Type: Journal    
DOI: 10.1057/palgrave.ivs.9500075     Document Type: Article

References (44)

1. Ben-Ari M. Constructivism in computer science education. Journal of Computers in Mathematics and Science Teaching, 2001; 20: 45–73.
2. Samurçay R. The concept of variable in programming: Its meaning and use in problem-solving by novice programmers. In: SolowayE, SpohrerJC,(Eds.). Studying the Novice Programmer. Lawrence Erlbaum Associates: Hillsdale, NJ, 1989; 161–178.
3. Sleeman D, Putnam RT, Baxter JA, Kuspa L. A summary of misconceptions of high school Basic programmers. In: SolowayE, SpohrerJC,(Eds.). Studying the Novice Programmer. Lawrence Erlbaum Associates: Hillsdale, NJ, 1989; 301–314.
4. Madison S, Gifford J. Modular programming: Novice misconceptions. Journal of Research on Technology in Education, 2002; 34: 217–229.
5. Fleury AE. Parameter passing: The rules the students construct. ACM SIGCSE Bulletin, 1991; 23: 283–286.
6. Holland S, Griffiths R, Woodman M. Avoiding object misconceptions. SIGCSE Bulletin, 1997; 29: 131–134.
7. Hundhausen CD, Douglas SA, Stasko JT. A meta-study of algorithm visualization effectiveness. Journal of Visual Languages and Computing, 2002; 13: 259–290.
8. Mulholland P. A principled approach to the evaluation of SV: A case study in Prolog. In: StaskoJT, DomingueJ, BrownMH, PriceBA,(Eds.). Software Visualization - Programming as a Multimedia Experience. The MIT Press: Cambridge, MA, 1998; 439–451.
9. Birch MR, Boroni CM, Goosey FW, Patton SD, Poole DK, Pratt CM, Ross RJ. DYNALAB A dynamic computer science laboratory infrastructure featuring program animation. ACM SIGCSE Bulletin, 1995; 27: 29–33.
10. Haajanen J, Pesonius M, Sutinen E, Tarhio J, Teräsvirta T, Vanninen P. Animation of user algorithms on the Web. In: VL’ 97, IEEE Symposium on Visual Languages. IEEE Computer Society Press; Chicago, 1997; 360–367.
11. Lahtinen SP, Sutinen E, Tarhio J. Automated animation of algorithms with Eliot. Journal of Visual Languages and Computing, 1998; 9: 337–349.
12. Ramadhan HA. Programming by discovery. Journal of Computer Assisted Learning, 2000; 16: 83–93.
13. Mayer R. Multimedia learning. Cambridge University Press: UK, 2001.
14. Carroll JM, Mack RL. Metaphor, computing systems, and active learning. International Journal of Human-Computer Studies, 1999; 51: 385–403.
15. Petre M, Blackwell AF. Mental imagery in program design and visual programming. International Journal of Human-Computer Studies, 1999; 51: 7–30.
16. Sajaniemi J. An empirical analysis of roles of variables in novice-level procedural programs. In: IEEE Symposia on Human Centric Computing Languages and Environments (HCC1902). IEEE Computer Society Press: Chicago, 2002; 37–39.
17. Brown MH. Exploring algorithms using Balsa-II. IEEE Computer, 1988; 21: 14–36.
18. Brown MH. ZEUS: a system for algorithm animation and multi-view editing. In: Proceedings of the IEEE Workshop on Visual Languages. IEEE Computer Society Press: Chicago, 1991; 4–9.
19. DiGiano CJ, Baecker RM, Owen RN. LogoMedia: A sound-enhanced programming environment for monitoring program behaviour. In: INTERCHI1993. ACM, Addison-Wesley: New York, 1993; 301–302.
20. Hansen S, Narayanan NH, Hegarty M. Designing educationally effective algorithm visualizations. Journal of Visual Languages and Computing, 2002; 13: 291–317.
21. Hundhausen CD, Douglas SA. SALSA and ALVIS: a language and system for constructing and presenting low fidelity algorithm visualizations. In: 2000 IEEE Symposium on Visual Languages, 2000; 67–68.
22. Roman GC, Cox K, Wilcox C, Plun J. Pavane: A system for declarative visualization of concurrent computations. Journal of Visual Languages and Computing, 1992; 3: 161–193.
23. Rössling G, Freisleben B. ANIMAL: A system for supporting multiple roles in algorithm animation. Journal of Visual Languages and Computing, 2002; 13: 341–354.
24. Stasko JT. Tango: A framework and system for algorithm animation. IEEE Computer, 1990; 23: 27–39.
25. Stasko JT. Using student-built algorithm animations as learning aids. In: Proceedings of the 1997 ACM SIGCSE Conference, 1997; 25–29.
26. Stasko JT, Kraemer E. A methodology for building application-specific visualizations of parallel programs. Journal of Parallel and Distributed Computing, 1993; 18: 258–264.
27. Sajaniemi J, Kuittinen M. Program animation based on the roles of variables. In: ACM 2003 Symposium on Software Visualization (SoftVis 2003). Association for Computing Machinery Press: New York, 2003; 7–16.
28. Ben-Bassat Levy R, Ben-Ari M, Uronen PA. The Jeliot 2000 program animation system. Computers & Education, 2003; 40: 1–15.
29. Ehrlich K, Soloway E. An empirical investigation of the tacit plan knowledge in programming. In: ThomasJC, SchneiderML,(Eds.). Human Factors in Computer Systems. Norwood, NJ: Ablex Publishing Company, 1984; 113–133.
30. Rist RS. Schema creation in programming. Cognitive Science, 1989; 13: 389–414.
31. Green TRG, Cornah AJ. The programmer’s torch. Human-Computer Interaction - INTERACT1984. IFIP, Elsevier Science Publishers: North-Holland: Amsterdam, 1985; 397–402.
32. Ben-Ari M, Sajaniemi J. Roles of variables from the perspective of computer science educators. In: The 9th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2004), 2004.
33. Sajaniemi J, Karjalainen M. Suppea johdatus Pascal-ohjelmointiin (A Brief Introduction to Programming in Pascal). Epsilon ry, Joensuu, Finland, 1985.
34. Foley RW. Introduction to Programming Principles Using Turbo Pascal. Chapman & Hall; London, 1991.
35. Jones WB. Programming Concepts - A Second Course. Prentice-Hall: Englewood Cliffs, NJ, 1982.
36. Lavie N. Perceptual load as a necessary condition for selective attention. Journal of Experimental Psychology: Human Perception and Performance, 1995; 21: 451–468.
37. Kuittinen M, Sajaniemi J. Teaching roles of variables in elementary programming courses. In: The 9th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2004), 2004.
38. Mulholland P, Eisenstadt M. Using software to teach programming: Past, present and future. In: StaskoJT, DomingueJ, BrownMH, PriceBA,(Eds.). Software Visualization - Programming as a Multimedia Experience. The MIT Press: Cambridge, MA, 1998; 399–408.
39. Dillon A, Gabbard R. Hypermedia as an educational technology: A review of the quantitative research literature on learner comprehension, control and style. Review of Educational Research, 1998; 68: 322–349.
40. Good J. Programming paradigms, information types and graphical representations: empirical investigations of novice program comprehension. Ph.D. thesis University of Edinburgh, 1999.
41. Sajaniemi J, Kuittinen M. An experiment on using roles of variables in teaching introductory programming. Computer Science Education. In press.
42. Pennington N. Comprehension strategies in programming. In: Empirical Studies of Programmers: Second Workshop. Ablex Publishing Company: Norwood, NJ, 1987; 100–113.
43. Détienne F. Software Design - Cognitive Aspects. Springer-Verlag: London, 2002.
44. Clancy MJ, Linn MC. Patterns and pedagogy. In: Proceedings of the 30th SIGCSE Technical Symposium on CS Education, 1999; 37–42.