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Type :article
Subject :L Education
Main Author :Ahmad Zamzuri Mohamad Ali
Additional Authors :Anuar Hassan
Title :Segmented animation, user-control strategy and cognition
Place of Production :Tanjong Malim
Publisher :Fakulti Seni, Komputeran dan Industri Kreatif
Year of Publication :2019
Corporate Name :Universiti Pendidikan Sultan Idris
PDF Full Text :The author has requested the full text of this item to be restricted.

Abstract : Universiti Pendidikan Sultan Idris
The aim of this study was to investigate the effects of various user-control strategies of segmented animation in learning abstract contents or processes that are not naturally visual on the cognition of students. In particular, the study examined the effects of five different user-control strategies: linear user-control, random user-control, free user-control, program-control, and continuous user-control. The research design was quasi-experimental and the data obtained were statistically analysed using ANCOVA and ANOVA. The instruments involved were pre-test, post-test, and NASA-TLX cognitive load test. The sample size consisted of 265 semester-two students enrolled in the Diploma in Networking System. The results indicated significant differences in the post-test and cognitive load test outcomes. In conclusion, this study suggests that the use of user-control, either linear user-control or random user-control, were sufficient strategies for learning abstract contents in segmented animation form.  

References

1. Ahmad Zamzuri, M. A. (2013). Effects of segmented-animation in projected presentation condition. Journal of Educational Technology and Society, 16(3), 234–245.

2. Ainsworth, S. (2008). How do animations influence learning?. In D. H. Robinson & G. Schraw (Eds.), Current perspectives on cognition, learning, and instruction: Recent innovations in educational technology that facilitate student learning (pp. 37–67). North Carolina, NC: Information Age Publishing.

3. Aldalalah, O. M., Fong, S. F., & Ababneh, Z. W. (2010). Effects of multimedia-base instructional designs for Arabic language learning among pupils of different achievement levels. International Journal of Human and Social Sciences, 5(5), 960–967.

4. Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence & J. T. Spence (Eds.), The psychology of learning and motivation (Vol. 2, pp. 89–195). New York, NY: Academic Press.

3. Atkinson, R. C., & Shiffrin, R. M. (1971). The control of short memory. Scientific American, 224, 82–90. doi:10.1038/scientificamerican0871-82

4. Awan, R. N., & Stevens, B. (2006). Static/animated diagrams and their effect on student’s perceptions of conceptual understandings in computer aided learning (CAL) environments. In T. McEwan, J. Gulliksen, & D. Benyen (Eds.), People and computer XIX – The bigger picture (pp. 381–389). London, UK: Springer-Verlag.

5. Ayres, P., Marcus, N., Chan, C., & Qian, N. (2009). Learning hand manipulative tasks: When instructional animations are superior to equivalent static representations. Computers in Human Behavior, 25 (2), 348–353. doi:10.1016/j.chb.2008.12.013

6. Ayres, P., & Paas, F. (2007). Can the cognitive load approach make instructional animations more effective?. Applied Cognitive Psychology, 21(6), 811–820. doi:10.1002/acp.1351

7. Betrancourt, M. (2005). The animation and interactivity principles in multimedia learning. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 287–296). New York, NY: Cambridge University Press.

8. Bloom, B. S. (1956). Taxonomy of educational objectives: Book 1 cognitive domain. White Plains, NY: Longman.

9. Boucheix, J. M., & Guignard, H. (2005). What animated illustrations conditions can improve technical document comprehension in young students? Format, signaling and control of the presentation. European Journal of Psychology of Education, 20(4), 369–388. doi:10.1007/BF03173563

10. Boucheix, J. M., & Schneider, E. (2009). Static and animated presentations in learning dynamic mechanical systems. Learning and Instruction, 19(2), 112–127. doi:10.1016/j.learninstruc.2008.03.004

11. Chandler, P. (2009). Dynamic visualizations and hypermedia: Beyond the “Wow” factor. Computers in Human Behavior, 25(2), 389–392. doi:10.1016/j.chb.2008.12.018

12. Chandler, P., & Sweller, J. (1991). Cognitive load theory and the format of instruction. Cognition and Instruction, 8(4), 293–332. doi:10.1207/ s1532690xci0804_2

13. Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of instruction. British Journal of Educational Psychology, 62(2), 233–246. doi:10.1111/j.2044-8279.1992.tb01017.x

14. Clark, R. C., Nguyen, F., & Sweller, J. (2011). Efficiency in learning: Evidencebased guidelines to manage cognitive load. New York, NY: Wiley.

15. Fong, S. F., & Lily, L. P. L. (2010). Effects of segmented animation among students of different anxiety levels: A cognitive load perspective. Malaysian Journal Of Education Technology, 10(2), 91–100.

16. Garhart, C., & Hannafin, M. (1986). The accuracy of cognitive monitoring during computer based instruction. Journal of Computer Based Instruction, 13(3), 88–93. Retrieved from http://0-files.eric.ed.gov. opac.msmc.edu/fulltext/ED267768.pdf

17. Gerjets, P., Scheiter, K., & Schorr, T. (2003). Modeling processes of volitional action control in multiple-task performance: How to explain effects of goal competition and task difficulty on processing strategies and performance within ACT-R. Cognitive Science Quarterly, 3(1), 355–400.

18. Hart, S. G. (2006). NASA-task load index (NASA-TLX); 20 years later. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 50(9), 904–908. doi:10.1177/154193120605000909

19. Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (Task Load Index): Result of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139–183). Amsterdam, The Netherlands: Elsevier Science Publishers.

20. Hasler, B. S., Kersten, B., & Sweller, J. (2007). Learner control, cognitive load and instructional animation. Applied Cognitive Psychology, 21(1), 713–729. doi:10.1002/acp.1345

21. Hegarty, M. (2004). Dynamic visualization and learning: Getting to the difficult questions. Learning and Instruction, 14(3), 343–351. doi:10.1016/j.learninstruc.2004.06.007

22. Hegarty, M., Kriz, S., & Cate, C. (2003). The roles of mental animation and external animation in understanding mechanical systems. Cognition and Instruction, 21(4), 325–360. doi:10.1207/s1532690xci2104_1

23. Janssen, J., Erkens, G., Kirschner, P. A., & Kanselaar, G. (2010). Effects of representational guidance during computer-supported collaborative learning. Instructional Science, 38(1), 59–88. doi:10.1007/s11251-008-9078-1

24. Jeroen, J., Enboer, V., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147–177. doi:10.1007/s10648-005-3951-0

25. Jun-Xia, G. (2007). Action research: The application of cognitive load theory to reading teaching. Sino-US English Teaching, 4(4), 19–23. Retrieved from https://www.researchgate.net/publication/237584679_ Action_Research_The_Application_of_Cognitive_Load_Theory_to_Reading_Teaching

26. Kalyuga, S., Ayres, P., Chandler, P., & Sweller, J. (2003). The expertise reversal effect. Educational Psychologist, 38(1), 23–31. doi:10.1207/ S15326985EP3801_4

27. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry based teaching. Educational Psychologist, 41(2), 75–86. doi:10.1207/s15326985ep4102_1

28. Kolloffel, B., Eysink, T., De Jong, T., & Wilhelm, P. (2009). The effects of representation format on learning combinatories from an interactive computer. Instructional Science, 37(1), 503–515. doi:10.1007/s11251-008-9056-7

29. Lewalter, D. (2003). Cognitive strategies for learning from static and dynamic visuals. Learning and Instruction, 13(2), 177–189. doi:10.1016/S0959-4752(02)00019-1

30. Lightner, N. J. (2001). Model testing of users’ comprehension in graphical animation: The effect of speed and focus area. International Journal of Human-Computer Interaction, 13(1), 53–73. doi:10.1207/S15327590IJHC1301_4

31. Lin, C. L., & Dwyer, F. M. (2004). Effect of varied animated enhancement strategies in facilitating achievement of different educational objectives. International Journal of Instructional Media, 31(2), 185–199.

32. Lin, H., & Dwyer, F. M. (2010). The effect of static and animated visualization: A perspective of instructional effectiveness and efficiency. Educational Technology Research and Development, 58(2), 155–174. doi:10.1007/s11423-009-9133-x

33. Lowe, R. K. (1999). Extracting information from an animation during complex visual learning. European Journal of the Psychology of Education, 14(2), 225–244. doi:10.1007/BF03172967

34. Lowe, R. K. (2004). Interrogation of a dynamic visualization during learning. Learning and Instruction, 14(3), 257–274. doi:10.1016/j. learninstruc.2004.06.003

35. Lowe, R. K., & Boucheix, J. M. (2010). Manipulable models for investigating processing of dynamic diagrams. In A. K. Goel, M. Jamnik, &

36. N. H. Narayanan (Eds.), The 6th International Conference on the Theory and Application of Diagrams (pp. 319–321). Portland, USA: Springer.

37. Mayer, R. E. (2001). Multimedia learning. Cambridge, UK: Cambridge University Press.

38. Mayer, R. E. (2002). Cognitive theory and the design of multimedia instruction: An example of the two-way street between cognition and instruction. New Directions for Teaching and Learning, 2002(89), 55–71. doi:10.1002/tl.47

39. Mayer, R. E. (2005). Principles for managing essential processing in multimedia learning: Segmenting, pertaining, and modality principles. In R. E. Mayer (Ed.), The Cambridge handbook of multimedia learning (pp. 169–182). New York, NY: Cambridge University Press.

40. Mayer, R. E., & Chandler, P. (2001). When learning is just a click away: Does simple user interaction foster deeper understanding of multimedia messages?. Journal of Educational Psychology, 93(2), 390–397. doi:10.1037/0022-0663.93.2.390

41. Mayer, R. E., Dow, G. T., & Mayer, S. (2003). Multimedia learning in an interactive self-explaining environment: What works in the design of agent-based microworlds?. Journal of Education & Psychology, 95(4), 806–812. doi:10.1037/0022-0663.95.4.806

42. Mayer, R. E., & Moreno, R. (2002). Animation as an aid to multimedia learning. Educational Psychology Review, 14(1), 87–99. doi:10.1023/ A:1013184611077

43. Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6

44. Moreno, R. (2007). Optimising learning from animations by minimizing cognitive load: Cognitive and affective consequences of signaling and segmentation methods. Applied Cognitive Psychology, 21(6), 765–781. doi:10.1002/acp.1348

45. Narayanan, N. H., & Hegarty, M. (2002). Multimedia design for communication of dynamic information. International Journal of HumanComputer Studies, 57(4), 279–315. doi:10.1006/ijhc.2002.1019

46. Norman, D. A. (1982). Learning and memory. New York, NY: WH Freeman & Co.

47. Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent developments. Educational Psychologist, 38(1), 1–4. doi:10.1207/S15326985EP3801_1

48. Paas, F., van Gog, T., & Sweller, J. (2010). Cognitive load theory: New conceptualizations, specifications, and integrated research perspectives. Educational Psychology Review, 22(2), 115–121. doi:10.1007/ s10648-010-9133-8

49. Paivio, A. (1986). Mental representations: A dual coding approach. Madison Avenue, New York: Oxford University Press.

50. Pallant, J. (2007). SPSS survival manual: A step-by-step guide to data analysis using SPSS for windows (version 15) (3rd ed.). Crows Nest, NSW: Allen & Unwin.

51. Slater, R. B., & Dwyer, F. (1996). The effect of varied interactive questioning strategies in complementing visualized instruction. International Journal of Instructional Media, 23(3), 273–280. Retrieved from http://eric.ed.gov/?id=EJ569022

52. Spanjers, I. A. E., van Gog, T., & van Merrienboer, J. J. G. (2010). A theoretical analysis of how segmentation of dynamic visualizations optimizes students’ learning. Educational Psychology Review, 22(4), 411–423. doi:10.1007/s10648-010-9135-6

53. Spanjers, I. A. E., Wouters, P., van Gog, T., & van Merrienboer, J. J. G. (2011). An expertise reversal effect of segmentation in learning from animated worked-out examples. Computers in Human Behavior, 27(1), 46–52. doi:10.1016/j.chb.2010.05.011

54. Sperling, R. A., Seyedmonir, M., Aleksic, M., & Meadows, G. (2003). Animations as learning tools in authentic science materials. International Journal of Instructional Media, 30(2), 213–222.

55. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. doi:10.1016/0364-0213(88)90023-7

56. Sweller, J. (1994). Cognitive load theory, learning difficulty and instructional design. Learning and Instruction, 4(4), 295–312. doi:10.1016/0959-4752(94)90003-5

57. Sweller, J. (2004). Instructional design consequences of an analogy between evolution by natural selection and human cognitive architecture. Instructional Science, 32(1–2), 9–31. doi:10.1023/B:TRUC.0000021808.72598.4d

58. Sweller, J., van Merriënboer, J., & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. doi:10.1023/A:1022193728205

59. Tindall-Ford, S. (1998). Applying cognitive psychology principles to education and training: Optimizing multimedia instruction. Retrieved from http://www.aare.edu.au/98pap/cha98030.htm

60. Torres, J., & Dwyer, F. (1991). The effect of time in instructional effectiveness of varied enhancement strategies. International Journal of Instructional Media, 8(4), 2–8.

61. Tversky, B., Morrison, J. B., & Betrancourt, M. (2002). Animation: Can it facilitate?. International Journal of Human Computer Studies, 57(4), 247–262. doi:10.1006/ijhc.2002.1017

62. van Merrienboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for e-Learning. Educational Technology, Research and Development, 53(3), 5–13. doi:10.1007/BF02504793

63. van Merrienboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147–177. doi:10.1007/s10648-005-3951-0

64. van Oostendorp, H., Beijersbergen, M. J., & Solaimani, S. (2008). Conditions for learning from animations. Proceedings of the 8th International Conference on Learning Science, 2(1), 438–445. Retrieved from http://dl.acm.org/citation.cfm?id=1599926&dl= ACM&coll=DL&CFID=614080807&CFTOKEN=95575446

65. Weir, G. R. S., & Heeps, S. (2003). Getting the message across: Ten principles for web animation. Proceedings of the 7th IASTED international conference on internet and multimedia and applications, 121–126. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/down load?doi=10.1.1.185.135&rep=rep1&type=pdf

66. Wiebe, E. N. (1991). A review of dynamic and static visual display techniques. Retrieved from http://www4.ncsu.edu/~wiebe/articles/ani1991.pdf

 

 


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