Beyond academic tracking: Using cluster analysis and self-organizing maps to investigate secondary students' chemistry self-concept

Chemistry Education Research and Practice

Volumn 17, Issue 4, 2016, Pages 711-722

  Nielsen, Sara E ^a   Yezierski, Ellen J ^a  

^a MIAMI UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85028734766     PISSN: None     EISSN: 11094028     Source Type: Journal    
DOI: 10.1039/c6rp00058d     Document Type: Article

References (47)

1. Bandura A., (1977), Social learning theory, Englewood Cliffs, NJ: Prentice-Hall
2. Barbera J., Adams W. K., Wieman C. E. and Perkins K. K., (2008), Modifying and validating the Colorado Learning Attitudes about Science Survey for use in chemistry, J. Chem. Educ., 85 (10), 1435-1439
3. Bauer C. F., (2005), Beyond "student attitudes": chemistry self-concept inventory for assessment of the affective component of student learning, J. Chem. Educ., 82 (12), 1864-1870
4. Bauer C. F., (2008), Attitude towards chemistry: a semantic differential instrument for assessing curriculum impacts, J. Chem. Educ., 85 (10), 1440-1445
5. Bong M. and Clark R. E., (1999), Comparison between self-concept and self-efficacy in academic motivation research, J. Educ. Psychol., 34 (3), 139-153
6. Bong M. and Skaalvik E. M., (2003), Academic self-concept and self-efficacy: how different are they really? Educ. Psychol. Rev., 15 (1), 1-40
7. Byrne B. M., (1986), Self-concept/academic achievement relations: an investigation of dimensionality, stability, and causality, Can. J. Behav. Sci., 18 (2), 173-186
8. Campbell I., (2007), Chi-squared and Fisher-Irwin tests of two-by-two tables with small sample recommendations, Stat. Med., 26, 3661-3675
9. Chan J. Y. K. and Bauer C. F., (2014), Identifying at-risk students in general chemistry via cluster analysis of affective characteristics, J. Chem. Educ., 91 (9), 1417-1425
10. Clark L. A. and Watson D., (1995), Constructing validity: basic issues in objective scale development, Psychol. Assessment, 7 (3), 309-319
11. College Board, (1995), AP Chemistry Course Overview. https://apstudent.collegeboard.org/apcourse/ap-chemistry (accessed Jan, 2016)
12. Dalgety J., Coll R. K. and Jones A., (2003), Development of Chemistry Attitudes and Experiences Questionnaire (CAEQ), J. Res. Sci. Teach., 40 (7), 649-668
13. Deboeck G., (1998), Best practices in data mining using Self-Organizing Maps, in G. Deboeck and T. Kohonen (ed.) Visual explorations in finance, New York, NY: Springer, pp. 203-229
14. Deters K. M., (2006), What are we teaching in secondary chemistry? J. Chem. Educ., 83 (10), 1492-1498
15. Everitt B. S., Landau S., Leese M. and Stahl D., (2011), Cluster analysis, 5th edn, Chichester, UK: Wiley
16. Fazio R. H., (2007), Attitudes as object-evaluation associations of varying strength, Soc. Cognition, 25, 603-637
17. Ferrell B. and Barbera J., (2015), Analysis of students' self-efficacy, interest, and effort beliefs in general chemistry, Chem. Educ. Res. Pract., 16 (2), 318-337
18. Galloway K. R. and Bretz S. L., (2015), Using cluster analysis to characterize meaningful learning in a first-year university chemistry laboratory course, Chem. Educ. Res. Pract., 16 (4), 879-892
19. Grove N. and Bretz S. L., (2007), CHEMX: an instrument to assess students' cognitive expectations for learning chemistry, J. Chem. Educ., 84 (9), 1524-1529
20. Kiviluoto K. and Bergius P., (1998), Maps for analyzing failures of small and medium-sized enterprises, in G. Deboeck and T. Kohonen (ed.), Visual explorations in finance, New York, NY: Springer, pp. 59-71
21. Kohonen T., (1982), Self-organized formation of topographically correct feature maps, Biol. Cybern., 43, 59-69
22. Kohonen T., (2001), Self-Organizing Maps, 3rd edn, New York, NY: Springer
23. Lek S. and Guegan J. F., (1999), Artificial neural networks as a tool in ecological modelling, an introduction, Ecol. Model., 120, 65-73
24. Lewis S. E., Shaw J. L., Heitz J. O. and Webster G. H., (2009), Attitude counts: self-concept and success in general chemistry, J. Chem. Educ., 86 (6), 744-749
25. Marco S., Ortega A., Pardo A. and Samitier J., (1998), Gas identification with Tin Oxide sensor array and Self-Organizing Maps: Adaptive correction of sensor drifts, Instrumentation and Measurement, IEEE Transactions on, 47 (1), 316-321
26. Marsh H. W., and Yeung A. S., (1997), Coursework selection: Relations to academic self-concept and achievement, Am. Educ. Res. J., 34, 691-720
27. Marsh H. W., Relich J. and Smith I. D., (1981), Self-concept: The construct validity of the Self Description Questionnaire
28. Marsh H. W., Parada R. H. and Ayotte V., (2004), A multidimensional perspective of relations between self-concept (Self Description Questionnaire II) and adolescent mental health (Youth Self-Report), Psychol. Assessment, 16 (1), 27-41
29. Nielsen S. E. and Yezierski E., (2015), Exploring the structure and function of the Chemistry Self-Concept Inventory with secondary chemistry students, J. Chem. Educ., 92 (11), 1782-1789
30. Nieswandt M., (2007), Student affect and conceptual understanding in learning chemistry, J. Res. Sci. Teach., 44 (7), 908-937
31. Novak J. D., (1993), Human constructivism: a unification of psychological and epistemological phenomena in meaning-making, International Journal of Personal Construct Psychology, 6 (2), 167-193
32. Oh K. S., Feng Y., Kaneko K., Makinouchi A. and Bae S. H., (2001), SOM-based R∗-tree for similarity retrieval, in Database Systems for Advanced Applications, 2001. Proceedings. Seventh International Conference on IEEE, pp. 182-189
33. O'Mara A. J., Marsh H. W., Craven R. G. and Debus R. L., (2006), Do self-concept interventions make a difference? a synergistic blend of construct validation and meta-analysis, J. Educ. Psychol., 41 (3), 181-206
34. Powers A. (ed.), (2011), Chemistry in the Community, American Chemical Society
35. Preckel F., Goetz T., Pekrun R. and Kleine M., (2008), Gender differences in gifted and average-ability students comparing girls' and boys' achievement, self-concept, interest, and motivation in mathematics, Gifted Child Quart., 52 (2), 146-159
36. R Core Team, (2015), R: a language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, URL http://www.R-project.org/
37. Raker J. R. and Holme T. A., (2014), Investigating faculty familiarity with assessment terminology by applying cluster analysis to survey data, J. Chem. Educ., 91 (8), 1145-1151
38. Rosenberg M., (1965), Society and the adolescent self-image, Princeton, NJ: Princeton University Press
39. Schwarz N., (1999), Self-reports: how the questions shape the answers, Am. Psychol., 54, 93-105
40. Shavelson R. J. and Bolus R., (1982), Self-concept: the interplay of theory and methods, J. Educ. Psychol., 74 (1), 3-17
41. Shavelson R. J., Hubner J. J. and Stanton G. C., (1976), Self-concept: validation of construct interpretations, Rev. Educ. Res., 46 (3), 407-441
42. Shaw A. J., Harrison T. G., Croker S. J., Medley M., Sellou L., Shallcross K. L., Williams S. J., Grayson D. J. and Shallcross D. E., (2010), University-school partnerships: on the impact on students of summer schools (for school students aged 17-18) run by Bristol ChemLabS, Acta Didactica Napocensia, 3 (4), 35-48
43. Smith P. S., (2013), 2012 National survey of science and mathematics education: status of secondary chemistry, Chapel Hill, NC: Horizon Research, Inc
44. Tamayo P., Slonim D., Mesirov J., Zhu Q., Kitareewan S., Dmitrovsky E., Lander E. S. and Golub T. R., (1999), Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation, Proc. Natl. Acad. Sci. U. S. A., 96 (6), 2907-2912
45. Tavakol M. and Dennick R., (2011), Making sense of Cronbach's alpha, Int. J. Med. Educ., 2, 53-55
46. Villafane S. M., Garcia C. A. and Lewis J. E., (2014), Exploring diverse students' trends in chemistry self-efficacy throughout a semester of college-level preparatory chemistry, Chem. Educ. Res. Pract., 15 (2), 114-127
47. Wehrens R. and Buydens L. M. C., (2007), Self- and super-organizing maps in R: the kohonen package, J. Stat. Softw., 21 (5), 1-19