Learning to program through interactive simulation;Apprendre à programmer grâce à la simulation interactive;Programmieren lernen durch interaktive Simulation;Aprender a programar a través de la simulación interactiva

Educational Media International

Volumn 43, Issue 3, 2006, Pages 251-268

  Yuen, Allan H K ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 62649122522     PISSN: 09523987     EISSN: 14695790     Source Type: Journal    
DOI: 10.1080/09523980600641452     Document Type: Article

References (54)

1. Adelson, B., 1981. Problem solving and the development of abstract categories in programming languages. Memory and Cognition, 9(4): 422–433.
2. Akpan, J. P., and Andre, T., 2000. Using a computer simulation before dissection to help students learn anatomy. Journal of Computers in Mathematics and Science Teaching, 19(3): 297–313.
3. Baillie, C., and Percoco, G., 2000. A study of present use and usefulness of computer-based learning at a technical university. European Journal of Engineering Education, 25(1): 33–43.
4. Bayman, P., and Mayer, R., 1988. Using conceptual models to teach BASIC computer programming. Journal of Educational Psychology, 80(3): 291–298.
5. Booth, S., 1992. Research into learning to program: learning to program—a phenomenographic perspective, Goteborg, Sweden: Acta Universitatis Gothoburgensis.
6. Brookshear, J. G., 1988. Computer science: an overview, (2nd edn), Reading, MA: Benjamin/Cummings Publishing Co.
7. Brophy, J., 1999. Toward a model of the value aspects of motivation in education: developing appreciation for particular learning domains and activities. Educational Psychologist, 34(2): 75–86.
8. Brown, D. W., 1990. Giving students a logical step up. Computer Science Education, 5(2): 12–17.
9. de Jong, T., and van Joolingen, W. R., 1998. Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2): 179–201.
10. Dean, A. M., and Webster, L., 2000. Simulations in distance education: progress towards an evaluation instrument. Distance Education, 21(2): 344–360.
11. Deek, F. P., and McHugh, J. A., 1998. A survey and critical analysis of tools for learning programming. Computer Science Education, 8(2): 130–178.
12. Edison, S., and Simons, P. E., 1998. Microcomputer simulation graphic and alphanumeric modes: examining students’ process skills and conceptual understanding. Journal of Computers in Mathematics and Science Teaching, 17(1): 21–61.
13. Flyvbjerg, B., 2001. Making social science matter, Cambridge, UK: Cambridge University Press.
14. Guimaraes, M. A. M., and de Lucena, C. J. P., 1995. A system environment for teaching introductory algorithms. SIGCUE Outlook, 23(3): 2–11.
15. Hamming, R. H., 1962. Numerical methods for scientists and engineers, New York, NY: McGraw-Hill.
16. Hargrave, C. P., and Kenton, J. M., 2000. Preinstructional simulation: implications for science classroomteaching. Journal of Computers in Mathematics and Science Teaching, 19(1): 47–58.
17. Huppert, J., Yaahobi, J., and Lazarowitz, R., 1998. Learning microbiology with computer simulations: students’ academic achievement by method and gender. Research in Science and Technology Education, 16(2): 231–245.
18. Jehng, J.-C. J., Tung, S.-H. S., and Chang, C.-T., 1999. A visualization approach to learning the concept of recursion. Journal of Computer Assisted Learning, 15: 279–290.
19. Jonassen, D. H., 1996. Computers in the classroom, Upper Saddle River, NJ: Prentice-Hall.
20. Kann, C., Lindeman, R. W., and Heller, R., 1997. Integrating algorithm animation into a learning environment. Computers Education, 28(4): 223–228.
21. Keegan, M., 1995. Scenario educational software: design and development of discovery learning, 67–75. Englewood Cliffs, NJ: Educational Technology Publishing.
22. Lee, J., 1999. Effectiveness of computer-based instructional simulation: a meta analysis. International Journal of Instructional Media, 26(1): 71–85.
23. Linn, M., 1985. The cognitive consequences of programming instruction in the classroom. Educational Researcher, 14(5): 14–29.
24. Linn, M. C., and Clancy, M. J., 1992. The case for case studies of programming problems. Communications of the ACM, 35(3): 121–133.
25. Mackenzie, J. G., Earl, W. B., Allen, R. M., and Gilmour, I. A., 2001. Amoco computer simulation in chemical engineering education. Journal of Engineering Education, 90(3): 331–345.
26. Mayer, R. E., 1981. The psychology of how novices learn computer programming. ACM Computing Survey, 13(1): 121–141.
27. Mayer, R. E., 1988. “ Introduction to research on teaching and learning computer programming ”. In Teaching and learning computer programming, Edited by: Mayer, R. E., 1–12. Hillsdale, NJ: LEA.
28. Mayer, R. E., 1992. Thinking, problem solving, cognition, New York: W. H. Freeman.
29. McDougall, A., and Boyle, M., 2004. Student strategies for learning computer programming: implications for pedagogy in informatics. Education and Information Technologies, 9(2): 109–116.
30. McGill, T. J., and Volet, S. E., 1997. A conceptual framework for analyzing students’ knowledge of programming. Journal of Research on Computing in Education, 29: 276–297.
31. Milbrandt, G., 1999. Computer problem-solving and programming: some number theory examples. Journal of Computer Science Education, 13(3&4): 18–26.
32. Norman, D. A., and Spohrer, J. C., 1996. Learner-centred education. Communications of the ACM, 39(4): 24–27.
33. Perkins, D. N., Schwartz, S., and Simmons, R., 1988. “ Instructional strategies for the problems of novice programmers ”. In Teaching and Learning Computing Programming, Edited by: E. Mayer, R., 153–178. Hillsdale, NJ: Lawrence Erlbaum Associates.
34. Rieber, P. L., 1991. Animation, incidental learning and continuing motivation. Journal of Educational Psychology, 83: 318–328.
35. Ramadhan, H. A., 2000. Programming by discovery. Journal of Computer Assisted Learning, 16: 83–93.
36. Ronen, M., and Eliahu, M., 2000. Simulation—a bridge between theory and reality: the case of electric circuits. Journal of Computer Assisted Learning, 16: 14–26.
37. Ruben, D. B., 1999. Simulation, games, and experience-based learning: the quest for a new paradigm for teaching and learning. Simulation and Gaming, 30(4): 498–505.
38. Schank, R. C., and Kass, A., 1996. Goal-based scenario for higher school students. Communications of the ACM, 39(4): 28–29.
39. Slavin, R. E., 2000. Educational psychology: theory and practice, (6th edn), Needham Heights, MA: Allyn and Bacon.
40. Smith, L. M., 1978. “ An evolving logic of participant observation, educational ethnography and other case studies ”. In Review of research in education, Edited by: Shuman, L., Vol. 6, 316–377. Itasca, IL: Peacock.
41. Smith, P. A., and Webb, G. I., 2000. The efficacy of a low-level program visualization tool for teaching programming concepts to novice programmers. Journal of Educational Computing Research, 22(2): 187–215.
42. Soloway, E., 1986. Learning to program = learning to construct mechanisms and explanations. Communications of the ACM, 29: 850–858.
43. Soloway, E., 1993. Should we teach students to program?. Communications of the ACM, 36(10): 21–24.
44. Soloway, E., Guzdial, M., and Hay, K. E., 1994. Learner-centred design: the challenge for HCI in the 21st century. Interactions, 1(2): 36–48.
45. Stake, R. E., 1994. “ Case studies ”. In Handbook of qualitative research, Edited by: Denzin, N. K., and Lincoln, Y. S., 236–247. Thousand Oaks, CA: Sage.
46. Stevenson, D. E., 1994. Science, computational science, and computer science: at a crossroads. Communications of the ACM, 37(12): 85–96.
47. Strauss, A., 1987. Qualitative analysis for social scientists, Cambridge, UK: Cambridge University Press.
48. Swaak, J., and de Jong, T., 2001. Discovery simulations and the assessment of intuitive knowledge. Journal of Computer Assisted Learning, 17: 284–294.
49. Thomas, R. A., and Upah, S. C., Jr. 1996. Give programming instruction a chance. Journal of Research on Computing in Education, 29(1): 96–107.
50. van Merrienboer, J., 1990. Instructional strategies for teaching computer programming: interaction with the cognitive style reflection-impulsivity. Journal of Research on Computing in Education, 23(1): 45–53.
51. Woolf, B., 1996. Intelligent multimedia tutoring systems. Communications of the ACM, 39(4): 30–31.
52. Wu, C., Lin, J., and Lin, K., 1999. A content analysis of programming examples in high school computer textbooks in Taiwan. Journal of Computers in Mathematics and Science Teaching, 18(3): 225–244.
53. Yin, R. K., 1998. “ The abridged version of case study research: design and method ”. In Handbook of applied social research methods, Edited by: Bickman, L., and Rog, D. J., 229–259. Thousand Oaks, CA: Sage.
54. Yuen, H. K., 2000. Teaching computer programming: a connectionist view of pedagogical change. Australian Journal of Education, 44(3): 239–253.