Impact of a pre-laboratory organic-extraction simulation on comprehension and attitudes of undergraduate chemistry students

Chemistry Education Research and Practice

Volumn 9, Issue 2, 2008, Pages 169-181

  Supasorn, Saksri ^a   Suits, Jerry P ^b   Jones, Loretta L ^b   Vibuljan, Sunanta ^a  

^a MAHIDOL UNIVERSITY   (Thailand)

^b UNIVERSITY OF NORTHERN COLORADO   (United States)

Author keywords

Animation; Extraction; Higher lower order cognitive skills; Mental models; Micro macroscopic levels; Organic chemistry; Particulate nature of matter; Simulated experiment; Simulation; Spatial ability; Visualization

Indexed keywords

EID: 45749121165     PISSN: None     EISSN: 11094028     Source Type: Journal    
DOI: 10.1039/b806234j     Document Type: Article

References (67)

1. Atkinson R. K., Mayer R. E. and Merrill M. M., (2005), Fostering social agency in multimedia learning: examining the impact of an animated agent's voice, Contemp. Educ. Psy., 30, 117-139.
2. Barke H., (1993), Chemical education and spatial ability, J. Chem. Educ., 70, 968-971.
3. Baddeley A. D., (1986), Working memory, Oxford University Press, Oxford, U.K.
4. Baddeley A., (1992), Working memory, Science, 255, 556-559.
5. Bodner G. M., (2007), The role of theoretical frameworks in chemistry, In G. M. Bodner and M. Orgill (Eds.), Theoretical frameworks for research in chemistry/science education, Prentice-Hall, Upper Saddle River, New Jersey, pp. 1-26.
6. Bodner G. M. and Domin D. S., (2000), Mental model: the role of representations in problem solving in chemistry, U. Chem. Educ., 4, 24-30.
7. Bunce D. B. and Gabel B., (2002), Differential effects on the achievement of males and females of teaching the particulate nature of chemistry, J. Res. Sci. Teach., 32, 911-927.
8. Carter C. S., LaRussa M. A. and Bodner G. M., (1987), A study of two measures of spatial ability as predictors of success in different levels of general chemistry, J. Res. Sci. Teach., 24, 645-657.
9. Clark R. E., (1983), Considering research on learning from media, Rev. Educ. Res., 53, 445-459.
10. Clark R. E., (1989), Current progress and future directions for research in instructional technology, Educ. Tech. Res. Dev., 37, 57-66.
11. Clark R. E., (2001), Media are mere vehicles: the opening argument, In R.E. Clark (Eds.), Learning from media: arguments, analysis, and evidence, Information Age Publishing, Greenwich, Connecticut, pp. 1-12.
12. Clark R. E., (2003), Research on web-based learning: a half-full glass, In R. Bruning, C. A. Horn, and L. M. Pytlik-Zillig (Eds.), Web-based learning: What do we know? Where do we go? Nebraska symposium on information technology in education, Information Age Publishing, Greenwich, Connecticut, pp. 1-22.
13. Clear S., (1978), Sex differences in spatial ability: a critique, Int. J. Behav. Dev., 1, 241-246.
14. Coleman S. L. and Gotch A. J., (1998), Spatial perception skills of chemistry students, J. Chem. Educ., 75, 206-209.
15. Dechsri P., Jones L. and Heikkinen H. W., (1997). Effect of a laboratory manual design incorporating visual information-processing aids on student learning and attitudes, J. Res. Sci. Teach., 34, 891-904.
16. Farrell J. J., Moog R. S., and Spencer J. N., (1999), A guided inquiry general chemistry course, J. Chem. Educ., 76, 570-574.
17. Ferguson R. L., (2007), Constructivism and social constructivism, In G. M. Bodner and M. Orgill (Eds.), Theoretical frameworks for research in chemistry/science education, Prentice Hall, Upper Saddle River, New Jersey, pp. 27-47.
18. Ginns P., (2005), Meta-analysis of the modality effect, Learn. Instr., 15, 313-332.
19. Halpern D. F., (1992), Sex differences in cognitive abilities, Erlbaum, Hillsdale, New Jersey, 2nd edn.
20. Hampp A., (1996), The extraction of caffeine from tea: a modification of the procedure of Murray and Hansen, J. Chem. Educ., 73, 1172.
21. Hanson D., and Wolfskill T., (2000), Process workshops - a new model for instruction, J. Chem. Educ., 77, 120-130.
22. Hegarty M., Kriz S. and Cate C., (2003). The roles of mental animations and external animations in understanding mechanical systems, Cogn. Instr., 21, 209-249.
23. Heiser J. and Tversky B., (2006), Arrows in comprehending and producing mechanical diagrams, Cogn. Sci., 30, 581-592.
24. Hinde R. J. and Kovac J., (2001), Student active learning in physical chemistry, J. Chem. Educ., 78, 93-99.
25. Huk T., (2006), Who benefits from learning with 3D models? The case of spatial ability, J. Comput. Assist. Learn., 22, 392-404.
26. Johnson-Laird P. N., (1983), Mental models - towards a cognitive science of language, inference and consciousness, Harvard University Press, Cambridge, Massachusetts.
27. Kleinman R. W., Griffin H. C. and Kerner N. K., (1987), Images in chemistry, J. Chem. Educ., 64, 766-770.
28. Kozma R. B., (1991), Learning with media, Rev. Educ. Res., 61, 179-212.
29. Kozma R. B. and Russell J., (1997), Multimedia understanding: expert and novice responses to different representations of chemical phenomena, J. Res. Sci. Teach., 34, 949-968.
30. Lee H., (2007), Instructional design of web-based simulations for learners with different levels of spatial ability, Instr. Sci., 35, 467-479.
31. Lewis J. E. and Lewis, S. E., (2005), Departing from lectures: an evaluation of a peer-led guided inquiry alternative, J. Chem. Educ., 82, 135-139.
32. Mathewson J. H., (1999), Visual-spatial thinking: an aspect of science overlooked by educators, Sci. Educ., 83, 33-54.
33. Mautone D. M. and Mayer R. E., (2001), Signaling as a cognitive guide in multimedia learning, J. Educ. Psych., 93, 377-389.
34. Mayer R. E., (1999), Multimedia aids to problem-solving transfer, Int. J. Educ. Res., 31, 611-623.
35. Mayer R. E., (2001), Multimedia learning, Cambridge University Press, New York.
36. Mayer R. E. and Anderson, R. B., (1991), Animations need narrations: an experimental test of a dual-coding hypothesis, J. Educ. Psych., 83, 484-490.
37. Mayer R. E. and Moreno R., (2003), Nine ways to reduce cognitive load in multimedia learning, In R. Bruning, C. A. Horn, and L. M. Pytlik-Zillig (Eds.), Web-based learning: What do we know? Where do we go? Nebraska symposium on information technology in education, Information Age Publishing. Greenwich, Connecticut, pp. 23-44.
38. Mayer R. E. and Sims V. K., (1994), For whom is a picture worth a thousand words? Extensions of a dual-coding theory of multimedia learning, J. Educ. Psych., 86, 389-401.
39. Mayer R. E., Steinhoff K., Bower G. and Mars R., (1995), A generative theory of textbook design: using annotated illustrations to foster meaningful learning of science text, Educ. Tech. Res. Dev., 43, 31-41.
40. McRobbie C. J., Giddings G. J. and Fraser B. J., (1990), Research into the environment of science laboratory classes in Australian schools, Res. Sci. Educ., 20, 200-209.
41. Murray S. D. and Hansen P. J., (1995), The extraction of caffeine from tea: an old undergraduate experiment revisited, J. Chem. Educ., 72, 851-852.
42. Padías A., (2007), Making the connections: a how-to guide for organic chemistry lab techniques, Hayden-McNeil Publishing, Plymouth, Michigan.
43. Paivio A., (1986), Mental representations: a dual coding approach, Oxford University Press, New York.
44. Palaigeorgiou G. E., Siozos P. D., Konstantakis N. I. and Tsoukalas I. A., (2005), A computer attitude scale for computer science freshmen and its educational implications, J. Comput. Assist. Learn., 21, 330-342.
45. Park O-C. and Hopkins R., (1992), Instructional conditions for using dynamic visual displays: a review, Instr. Sci., 21, 427-449.
46. Peters M., Chisholm P. and Laeng B., (1995), Spatial ability, student gender and academic performance, J. Engr. Educ., 84, 69-73.
47. Pribyl J. R. and Bodner G. M., (1987), Spatial ability and its role in organic chemistry: a study of four organic courses, J. Res. Sci. Teach., 24, 229-240.
48. Reiser R. and Dempsey J., (2002), Instructional design and technology, Merrill Prentice Hall, Upper Saddle River, New Jersey.
49. Russell J. W., Kozma R. B., Jones T., Wykoff J., Marx N. and Davis J., (1997), Use of simultaneous-synchronized macroscopic, microscopic, and symbolic representations to enhance the teaching and learning of chemical concepts, J. Chem. Educ., 74, 330-334.
50. Sanger M., Phelps A. and Fienhold J., (2000), Using a computer animation to improve students' conceptual understanding of a cancrushing demonstration, J. Chem. Educ., 77, 1517-1520.
51. Speer O. F., Wengerter B. C. and Taylor R. S., (2004), Molecular dynamics simulations of simple liquids, J. Chem. Educ., 81, 1330-1332.
52. Sweller J., (1994), Cognitive load theory, learning difficulty, and instructional design, Learn. Instr., 4, 295-312.
53. Sweller J. and Chandler P., (1994), Why some material is difficult to learn, Cogn. Instr., 12, 185-233.
54. Sweller J., van Merriënboer J. J. G. and Paas F. G. W. C., (1998), Cognitive architecture and instructional design, Educ. Psych. Rev., 10, 251-296.
55. Tversky B., (2001), Spatial schemas in depictions, In M. Gattis (Ed.), Spatial schemas and abstract thought, MIT Press, Cambridge, Massachusetts, pp. 79-111.
56. Tversky B., (2007), Prolegomenon to scientific visualization, In J.K. Gilbert, et al. (Eds.), Visualization in science education, Springer, The Netherlands, pp. 29-42.
57. Tversky B., Zacks J., Lee P. U. and Heiser J., (2000), Lines, blobs, crosses, and arrows: diagrammatic communication with schematic figures. In M. Anderson, P. Cheng, and V. Haarslev (Eds.), Theory and application of diagrams, Springer, Berlin, pp. 221-230.
58. Williamson V. M. and Abraham M. R., (1995), The effects of computer animation on the particulate mental models of college chemistry students, J. Res. Sci. Teach., 32, 521-537.
59. Wilson B. and Lowry M., (2000), Constructivist learning on the web, New Direct. for Adult Contin. Educ., 88, 79-88.
60. Wolf S. J. and Fraser B. J., (2007), Learning environment, attitudes and achievement among middle-school science students using inquiry-based laboratory activities, Res. Sci. Educ., (On Line Version; Publication Date 08/2007), DOI: 10.1007/s11165-007-9052-y
61. Wong S. K. P., (1988), The effects of different visual strategies, selected individual differences, and learner control on student word problem solving performance, Doctoral Dissertation, University of Minnesota. Twin Cities, Minnesota.
62. Woodfield B. F., Catlin H. R., Waddoups G. L., Moore M. S., Swan R., Allen R. and Bodily G., (2004), The virtual ChemLab project: a realistic and sophisticated simulation of inorganic qualitative analysis, J. Chem. Educ., 81, 1672-1678.
63. Wu H. and Shah P., (2004), Exploring visuospatial thinking in chemistry learning, Sci. Educ., 88, 465-492.
64. Yang E., Andre T. and Greenbowe T., (2003), Spatial ability and the effect of visualization/animation on learning electrochemistry, Int. J. Sci. Educ., 25, 329-349.
65. Zoller U. and Pushkin D., (2007), Matching higher-order cognitive skills (HOCS) promotion goals with problem-based laboratory practice in a freshman organic chemistry course, Chem. Educ. Res. Pract., 8, 153-171.
66. Zoller U. and Tsaparlis G., (1997), higher and lower-order cognitive skills: the case of chemistry, Res. Sci. Educ., 27, 117-130.
67. rd ed.