Words or Pictures: A comparison of written and pictorial explanations of physical and chemical equilibria

International Journal of Science Education

Volumn 36, Issue 5, 2014, Pages 783-807

  Akaygun, Sevil ^a   Jones, Loretta L ^b  

^a BOGAZICI UNIVERSITY   (Turkey)

^b UNIVERSITY OF NORTHERN COLORADO   (United States)

Author keywords

Chemistry; Drawings; Equilibrium; Explanations; Representations

Indexed keywords

EID: 84893770164     PISSN: 09500693     EISSN: 14645289     Source Type: Journal    
DOI: 10.1080/09500693.2013.828361     Document Type: Article

References (64)

1. Ainsworth, S. (1999). The functions of multiple representations. Computers & Education, 33, 131-152. doi: 10.1016/S0360-1315(99)00029-9
2. Akaygun, S. (2009). The effect of computer visualizations on students' mental models of the dynamic nature of physical equilibrium (Unpublished doctoral dissertation). Greeley, CO: University of Northern Colorado.
3. Akaygun, S., & Jones, L. L. (2013a). How does level of guidance affect understanding when students use a dynamic simulation of liquid-vapor equilibrium? In I. Devetak, S. A. Glazar, & L. Plut-Pregelj (Eds.), Active learning and understanding in the chemistry classroom. Springer.
4. Akaygun, S., & Jones, L. L. (2013b). Dynamic visualizations: Tools for understanding the particulate nature of matter. In G. Tsaparlis, & H. Sevian (Eds.), Concepts of matter in science education (pp. 282-300). DordrechtThe Netherlands: Springer.
5. Ardac, D., & Akaygun, S. (2004). Effectiveness of multimedia-based instruction that emphasizes molecular representations on students' understanding of chemical change. Journal of Research in Science Teaching, 40(4), 317-337. doi: 10.1002/tea.20005
6. Ardac, D., & Akaygun, S. (2005). Using static and dynamic visuals to represent chemical change at molecular level. International Journal of Science Education, 27(11), 1269-1298. doi: 10.1080/09500690500102284
7. Banerjee, A. (1995). Teaching chemical equilibrium and thermodynamics in undergraduate general chemistry classes. Journal of Chemical Education, 72(10), 879-881. doi: 10.1021/ed072p879
8. Ben-Zvi, R., Eylon, B., & Silberstein, J. (1986). Is an atom of copper malleable? Journal of Chemical Education, 63(1), 64-66. doi: 10.1021/ed063p64
9. Bergquist, W., & Heikkinen, H. (1990). Student ideas regarding chemical equilibrium. Journal of Chemical Education, 67(12), 1000-1003. doi: 10.1021/ed067p1000
10. Bodner, G. M., Gardner, D. E., & Briggs, M. W. (2005). Models and modeling. In N. Pienta, M. Cooper, & GreenboweT. (Eds.), Chemists' guide to effective teaching (pp. 67-76). Upper Saddle River, NJ: Prentice-Hall.
11. Burke, K., Greenbowe, T., & Windschitl, M. (1998). Developing and using conceptual computer animations for chemistry instruction. Journal of Chemical Education, 75(12), 1658-1661. doi: 10.1021/ed075p1658
12. Camacho, M., & Good, R. (1989). Problem solving and chemical equilibrium: Successful versus unsuccessful performance. Journal of Research in Science Teaching, 26(3), 251-272. doi: 10.1002/tea.3660260306
13. Cheng, M., & Gilbert, J. K. (2009). Towards a better utilization of diagrams in research into the use of representative levels in chemical education. In J. K. Gilbert, & D. Treagust (Eds.), Multiple representations in chemical education, Models and modeling in science education (pp. 55-73). Heidelberg: Springer.
14. Chiu, M.-H., Chou, C.-C., & Liu, C.-J. (2002). Dynamic processes of conceptual change: Analysis of constructing mental models of chemical equilibrium. Journal of Research in Science Teaching, 39(8), 688-712. doi: 10.1002/tea.10041
15. Coll, R. K., & Treagust, D. F. (2003). Investigation of secondary school, undergraduate, and graduate learners' mental models of ionic bonding. Journal of Research in Science Teaching, 40(5), 464-486. doi: 10.1002/tea.10085
16. Craik, K. (1943). The nature of explanation. Cambridge: Cambridge University Press.
17. Davidowitz, B., Chittleborough, C., & Murray, E. (2010). Student generated submicro diagrams: A useful tool for teaching and learning chemical equations and stoichiometry. Chemical Education Research and Practice, 11, 154-164. doi: 10.1039/c005464j
18. Ebenezer, J., & Gaskell, J. (1995). Relational conceptual change in solution chemistry. Science Education, 79(1), 1-17. doi: 10.1002/sce.3730790102
19. Ehrlén, K. (2009). Drawings as representations of children's conceptions. International Journal of Science Education, 31(1), 41-57. doi: 10.1080/09500690701630455
20. Gilbert, J. K. (1997). Exploring models and modeling in science education and technology education. ReadingUK: The University of Reading.
21. Gilbert, J. K., & Treagust, D. (2009). Introduction: Macro, submicro and symbolic representations and the relationship between them: Key models in chemical education. In J. K. Gilbert, & D. Treagust (Eds.), Multiple representations in chemical education (pp. 1-8). DordrechtThe Netherlands: Springer.
22. Gobert, J. D. (2005). Leveraging technology and cognitive theory on visualization to promote students' science. In J. K. Gilbert (Eds.), Visualization in science education (pp. 73-90). DordrechtThe Netherlands: Springer.
23. Greca, I. M., & Moreira, M. A. (2000). Mental models, conceptual models, and modeling. International Journal of Science Education, 22, 1-11. doi: 10.1080/095006900289976
24. Gussarsky, E., & Gorodetsky, M. (1988). On the chemical equilibrium concept: Constrained word associations and conception. Journal of Research in Science Teaching, 25, 319-333. doi: 10.1002/tea.3660250502
25. Gussarsky, E., & Gorodetsky, M. (1990). On the concept "chemical equilibrium": The associative framework. Journal of Research in Science Teaching, 27, 197-204. doi: 10.1002/tea.3660270303
26. Hackling, M. W., & Garnett, P. J. (1985). Misconceptions of chemical equilibrium. European Journal of Science Education, 7(2), 205-214. doi: 10.1080/0140528850070211
27. Haidar, A. H., & Abraham, M. R. (1991). A comparison of applied and theoretical knowledge of concepts based on the particulate nature of matter. Journal of Research in Science Teaching, 28(10), 919-938.
28. Harrison, A. G., & Treagust, D. F. (2002). The particulate nature of matter: Challenges in understanding the submicroscopic world. In J. K. Gilbert (Ed.), Chemical education: Toward research-based practice (pp. 189-212). DordrechtThe Netherlands: Kluwer Academic Publishers.
29. Ingham, A. M., & Gilbert, J. K. (1991). The use of analogue models by students of chemistry at higher education level. International Journal of Science Education, 13(2), 193-202. doi: 10.1080/0950069910130206
30. Johnstone, A. H. (1993). The development of chemistry teaching: A changing response to changing demand. Journal of Chemical Education, 70(9), 701-704. doi: 10.1021/ed070p701
31. Jones, L. L., Jordan, K. D., & Stillings, N. A. (2005). Molecular visualization in chemistry education: The role of multidisciplinary collaboration. Chemistry Education Research and Practice, 6(3), 136-149. doi: 10.1039/b5rp90005k
32. Justi, R., & Gilbert, J. K. (2002). Models and modelling in chemical education. In J. K. Gilbert (Ed.), Chemical education: Toward research-based practice (pp. 47-68). DordrechtThe Netherlands: Kluwer Academic Publishers.
33. Kelly, R. M., & Jones, L. L. (2007). Exploring how different features of animations of sodium chloride dissolving affect students' explanations. Journal of Science Education and Technology, 16(5), 413-429. doi: 10.1007/s10956-007-9065-3
34. Kelly, R. M., & Jones, L. L. (2008). Investigating students' ability to transfer ideas learned from molecular animations of the dissolution process. Journal of Chemical Education, 85, 303-309. doi: 10.1021/ed085p303
35. Kern, A. L., Wood, N. B., Roehrig, G. H., & Nyachwaya, J. M. (2010). A qualitative report of the ways high school chemistry students attempt to represent a chemical reaction at the atomic/molecular level. Chemical Education Research and Practice, 11, 154-164. doi: 10.1039/c005465h
36. Kozma, R. B., & Russell, J. (1997). Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena. Journal of Research in Science Teaching, 34(9), 949-968. doi: 10.1002/(SICI)1098-2736(199711)34:9<949::AID-TEA7>3.0.CO;2-U
37. Lekhavat, P., & Jones, L. (2009). The effect of adjunct questions emphasizing the particulate nature of matter on students' understanding of chemical concepts in multimedia lessons. Educación Química, 20(3), 351-359.
38. Lesh, R., Hover, M., Hole, B., Kelly, A., & Post, T. (2000). Principles for developing thought-revealing activities for students and teachers. In A. Kelly, & R. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 591-645). Mahwah, NH: Lawrence Erlbaum.
39. Margel, H., Eylon, B. S., & Scherz, Z. (2008). A longitudinal study of junior high school students' conceptions of the structure of materials. Journal of Research in Science Teaching, 45(1), 132-152. doi: 10.1002/tea.20214
40. Mayer, R. E. (2001). Multimedia learning. Cambridge: Cambridge University Press.
41. Mayer, R. E., & Anderson, R. B. (1992). The instructive animation: Helping students build connections between words and pictures in multimedia learning. Journal of Educational Psychology, 84(4), 444-452. doi: 10.1037/0022-0663.84.4.444
42. Nakhleh, M. B. (1992). Why some students don't learn chemistry. Journal of Chemical Education, 69(3), 19-196. doi: 10.1021/ed069p191
43. Niaz, M. (1995). Relationship between student performance on conceptual and computational problems of chemical equilibrium. International Journal of Science Education, 17, 343-355. doi: 10.1080/0950069950170306
44. Noh, T., & Scharmann, L. C. (1997). Instructional influence of a molecular-level pictorial presentation of matter on students' conceptions and problem-solving ability. Journal of Research in Science Teaching, 34(2), 199-217. doi: 10.1002/(SICI)1098-2736(199702)34:2<199::AID-TEA6>3.0.CO;2-O
45. Nurrenbern, S. C., & Pickering, M. (1987). Concept learning versus problem solving: Is there a difference? Journal of Chemical Education, 64(6), 508-509. doi: 10.1021/ed064p508
46. Nyachwaya, J. M., Mohamed, A.-R., Roehrig, G. H., Wood, N. B., Kern, A. L., & Schneider, J. L. (2011). The development of an open-ended drawing tool: An alternative diagnostic tool for assessing students' understanding of the particulate nature of matter. Chemistry Education Research and Practice, 12, 121-132. doi: 10.1039/c1rp90017j
47. Osborne, R. J., & Cosgrove, M. M. (1983). Children's conceptions of the changes of state of water. Journal of Research in Science Teaching, 20(9), 825-838. doi: 10.1002/tea.3660200905
48. Paivio, A. (1969). Mental imagery in associative learning and memory. Psychological Review, 76(3), 241-263. doi: 10.1037/h0027272
49. Paivio, A. (1990). Mental representations: A dual coding approach. New York: Oxford Science Publications.
50. Prain, V., & Tytler, R. (2012). Learning through constructing representations in science: A framework of representational construction affordances. International Journal of Science Education, 34(17), 2751-2773. doi: 10.1080/09500693.2011.626462
51. Sanger, M. (2000). Using particulate drawings to determine and improve students' conceptions of pure substances and mixtures. Journal of Chemical Education, 77(6), 762-766. doi: 10.1021/ed077p762
52. Sanger, M., Phelps, A., & Fienhold, J. (2000). Using a computer animation to improve students' conceptual understanding of a can-crushing demonstration. Journal of Chemical Education, 77(11), 1517-1520. doi: 10.1021/ed077p1517
53. Schnotz, W. (2001). Sign system, technologies, and the acquisition of knowledge. In J. F. Rouet, J. Levonen, & A. Biardeau (Eds.), Multimedia learning (pp. 9-29). Amsterdam: Elsevier Science.
54. Smith, K. J., & Metz, P. A. (1996). Evaluating student understanding of solution chemistry through microscopic representations. Journal of Chemical Education, 73(3), 233-237. doi: 10.1021/ed073p233
55. Treagust, D. F., Chittleborough, G., & Mamiala, T. L. (2003). The role of submicroscopic and symbolic representations in chemical explanations. International Journal of Science Education, 25, 1353-1368. doi: 10.1080/0950069032000070306
56. Tversky, B. (2001). Spatial schemas in depictions. In P. Grialou, G. Longo, & M. Okado (Eds.), Spatial schemas and abstract thought (pp. 79-112). Cambridge: MIT Press.
57. Tversky, B. (2005). Some ways images express and promote thought. In P. Grialou, G. Longo, & M. Okado (Eds.), Image and reasoning (pp. 15-29). Tokyo: Keiko University Press.
58. Tversky, B., Agrawala, M., Heiser, J., Lee, P. U., Hanrahan, P., Phan, D., Stolte, C., & Daniele, M. (2006). Cognitive design principles for automated generation of visualizations. In G. Allen (Ed.), Applied spatial cognition: From research to cognitive technology (pp. 53-73). Mahwah, NJ: Erlbaum.
59. Tyson, L., Treagust, D. F., & Bucat, R. B. (1999). The complexity of teaching and learning chemical equilibrium. Journal of Chemical Education, 76(4), 554-558. doi: 10.1021/ed076p554
60. Van Driel, J. H., & Gräber, W. (2002). The teaching and learning of chemical equilibrium. In J. K. Gilbert, O. De Jong, R. Justi, D. F. Treagust, J. H. Van Driel (Eds.), Chemical education: Towards research-based practice (pp. 271-292). DordrechtThe Netherlands: Kluwer Academic Publishers.
61. Voska, K. W., & Heikkinen, H. W. (2000). Identification and analysis of student conceptions used to solve chemical equilibrium problems. Journal of Research in Science Teaching, 37(2), 160-176. doi: 10.1002/(SICI)1098-2736(200002)37:2<160::AID-TEA5>3.0.CO;2-M
62. Wheeler, A. E., & Kass, H. (1978). Student misconceptions in chemical equilibrium. Science Education, 62(2), 223-232. doi: 10.1002/sce.3730620212
63. Williamson, V. (2008). The particulate nature of matter: An example of how theory-based research can impact the field. In D. Bunce, & R. S. Cole (Eds.), Nuts and bolts of chemical education research (pp. 67-78). Washington, DC: American Chemical Society.
64. Williamson, V. M., & Abraham, M. R. (1995). The effects of computer animation on the particulate mental models of college chemistry students. Journal of Research in Science Teaching, 32(5), 521-534. doi: 10.1002/tea.3660320508