Advertisement

Mathematics Education Research Journal

, Volume 27, Issue 3, pp 331–357 | Cite as

Adapting the academic motivation scale for use in pre-tertiary mathematics classrooms

  • Siew Yee Lim
  • Elaine Chapman
Original Article
First Online:

Abstract

The Academic Motivation Scale (ams) is a comprehensive and widely used instrument for assessing motivation based on the self-determination theory. Currently, no such comprehensive instrument exists to assess the different domains of motivation (stipulated by the self-determination theory) in mathematics education at the pre-tertiary level (grades 11 and 12) in Asia. This study adapted the ams for this use and assessed the properties of the adapted instrument with 1610 students from Singapore. Exploratory and confirmatory factor analyses indicated a five-factor structure for the modified instrument (the three original ams intrinsic subscales collapsed into a single factor). Additionally, the modified instrument exhibited good internal consistency (mean α = .88), and satisfactory test-retest reliability over a 1-month interval (mean r xx = .73). The validity of the modified ams was further demonstrated through correlational analyses among scores on its subscales, and with scores on other instruments measuring mathematics attitudes, anxiety and achievement.

Keywords

Academic motivation scale Mathematics motivation Self-determination theory Exploratory factor analysis Confirmatory factor analysis 
This is a preview of subscription content, log in to check access.

References

  1. Amabile, T. M., Hill, K. G., Hennessey, B. A., & Tighe, E. M. (1994). The work preference inventory: assessing intrinsic and extrinsic motivational orientations. Journal of Personality and Social Psychology, 66, 950–967.CrossRefGoogle Scholar
  2. Barkoukis, V., Tsorbatzoudis, H., Grouios, G., & Sideridis, G. (2008). The assessment of intrinsic and extrinsic motivation and amotivation: validity and reliability of the Greek version of the academic motivation scale. Assessment in Education: Principles, Policy & Practice, 15(1), 39–55.CrossRefGoogle Scholar
  3. Bell, J. (1987). Doing your research project. Philadelphia: Open University Press.Google Scholar
  4. Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York: The Guildford Press.Google Scholar
  5. Browne, M. W., & Cudeck, R. (1993). Alernative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–161). Newbury Park: Stage Publications.Google Scholar
  6. Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows. Thousand Oaks: Sage Publications.Google Scholar
  7. Baker, S. R. (2004). Intrinsic, extrinsic, and amotivational orientations: Their role in university adjustment, stress, well-being, and subsequent academic performance. Current Psychology, 23(3), 189–202.Google Scholar
  8. Chamberlin, S. A. (2010). A review of instruments created to assess affect in mathematics. Journal of Mathematics Education, 3(1), 167–182.Google Scholar
  9. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Erlbaum.Google Scholar
  10. Cokley, K. O. (2000). Examining the validity of the academic motivation scale by comparing scale construction to self-determination theory. Psychological Reports, 86, 560–564.CrossRefGoogle Scholar
  11. Cokley, K. O., Bernard, N., Cunningham, D., & Motoike, J. (2001). A psychometric investigation of the academic motivation scale using a United States sample. Measurement and Evaluation in Counseling and Development, 34(2), 109–119.Google Scholar
  12. Connell, J. P., & Wellborn, J. G. (1990). Competence, automomy and relatedness: A motivational analysis of self-esteem processes. In M. R. Gunnar & L. A. Sroufe (Eds.), The Minnesota symposium on child psychology (Vol. 22) (pp. 43–77). Hillsdale: Erlbaum.Google Scholar
  13. Conway, J. M., & Huffcutt, A. I. (2003). A review and evaluation of exploratory factor analysis practices in organizational research. Organizational Research Methods, 6, 147–168.CrossRefGoogle Scholar
  14. Dawes, J. (2008). Do data characteristics change according to the number of scale points used? An experiment using 5-point, 7-point and 10-point scales. International Journal of Market Research, 50(1), 61–77.Google Scholar
  15. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum Press.CrossRefGoogle Scholar
  16. Deci, E. L., Vallerand, R. J., Pelletier, L. G., & Ryan, R. M. (1991). Motivation and education: the self-determination perspective. Educational Psychologist, 26(3), 325–346.CrossRefGoogle Scholar
  17. Deci, E. L., & Ryan, R. M. (1980). The empirical exploration of intrinsic motivational processes. In L. Berkowitz (Ed.), Advances in experimental social psychology (pp. 39–80). New York, NY: Academic.Google Scholar
  18. Evans, J. (2001). Adults' mathematical thinking and emotions: A study of numerate practices. New York, NY: Routledge.Google Scholar
  19. Fairchild, A. J., Horst, S. J., Finney, S. J., & Barron, K. E. (2005). Evaluating existing and new validity evidence for the academic motivation scale. Contemporary Educational Psychology, 30, 331–358.CrossRefGoogle Scholar
  20. Fennema, E., & Sherman, J. A. (1976). Fennema-sherman mathematics attitudes scales: instruments designed to measure attitudes toward the learning of mathematics by males and females. Journal for Research in Mathematics Education, 7(5), 324–326.CrossRefGoogle Scholar
  21. Gatignon, H. (2010). Confirmatory factor analysis in statistical analysis of management data. doi: 10.1007/978-1-4419-1270-1_4.Google Scholar
  22. Gottfried, A. E. (1985). Academic intrinsic motivation in elementary and junior high school students. Journal of Educational Psychology, 77(6), 631–645.CrossRefGoogle Scholar
  23. Gottfried, A. E. (1986). Children’s academic intrinsic motivation survey. Odessa: Psychological Assessment Resources.Google Scholar
  24. Gottfried, A. E., Marcoulides, G. A., Gottfried, A. W., Oliver, P. H., & Guerin, D. (2007). Multivariate latent change modeling of developmental decline in academic intrinsic mathematics motivation and achievement: childhood through adolescence. International Journal of Behavioral Development, 31(4), 317–327.CrossRefGoogle Scholar
  25. Grouzet, M. E., Otis, N., & Pelletier, L. G. (2006). Longitudinal cross-gender factorial invariance of the academic motivation scale. Structural Equation Modeling, 13(1), 73–98.CrossRefGoogle Scholar
  26. Guimarães, S. E. R., & Bzuneck, J. A. (2008). Propiedades psicométricas de um instrument para avaliação da motivação de universitarios. Ciências & Cognição, 13(1), 101–113.Google Scholar
  27. Hair, J. F., Jr., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River: Pearson/Prentice Hall.Google Scholar
  28. Hannula, M. S. (2002). Attitude towards mathematics: emotions, expectations and values. Educational Studies in Mathematics, 49(1), 25–46.CrossRefGoogle Scholar
  29. Hayamizu, T. (1997). Between intrinsic and extrinsic motivation: examination of reasons for academic study based on the theory of internalization. Japanese Psychological Research, 39(2), 98–108.CrossRefGoogle Scholar
  30. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for Fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.CrossRefGoogle Scholar
  31. Jamieson, S. (2004). Likert scales: how to (ab) use them. Medical Education, 38, 1212–1218.CrossRefGoogle Scholar
  32. Kline, R. B. (2010). Principles and practice of structural equation modelling (3rd ed.). New York: Guilford Press.Google Scholar
  33. Lim, S. Y., & Chapman, E. (2013a). An investigation of the fennema-sherman mathematics anxiety subscale. Measurement and Evaluation in Counseling and Development, 46(1), 26–37. doi: 10.1177/0748175612459198.CrossRefGoogle Scholar
  34. Lim, S. Y., & Chapman, E. (2013b). Development of a short form of the attitudes toward mathematics inventory. Educational Studies in Mathematics: An International Journal, 82(1), 145–164. doi: 10.1007/s10649-012-9414-x.CrossRefGoogle Scholar
  35. Liu, W. C., Wang, C. K. J., Tan, O. S., Kohn, C., & Ee, J. (2009). A self-determination approach to understanding student’s motivation in project work. Learning and Individual Differences, 19(1), 139–145.CrossRefGoogle Scholar
  36. Lubke, G. H., & Muthen, B. O. (2004). Applying multigroup confirmatory factor models for continuous outcomes to likert scale data complicates meaningful group comparisons. Structural Equation Modeling, 11, 514–534.CrossRefGoogle Scholar
  37. Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal for Research in Mathematics Education, 28, 26–47.CrossRefGoogle Scholar
  38. MacCallum, R. C. (1986). Specificiation searches in covariance structure modeling. Psychological Bulletin, 100, 107–120.CrossRefGoogle Scholar
  39. Mendick, H. (2002). Why are we doing this? A case study of motivational practices in mathematics classes. In Cockburn, A.D. and Nardi, E. (eds.), Proceedings of the 26th PME, Vol.3 (pp. 329–336). Norwich, U.K.Google Scholar
  40. Miserandino, M. (1996). Children who do well in school: individual differences in perceived competence and autonomy in above-average children. Journal of Educational Psychology, 88, 203–214.CrossRefGoogle Scholar
  41. Mullis, I. V. S., Martin, M. O., Foy, P., Olson, J. F., Preuschoff, C., Erberber, E., Arora, A., & Galia, J. (2008). TIMSS 2007 international mathematics report: Findings from IEA’s trends in international mathematics and science study at the fourth and eighth grades. Chestnut Hill: TIMSS & PIRLS International Study Center/Boston College.Google Scholar
  42. Nicholls, J. G., Patashnick, M., & Nolen, S. (1985). Adolescents’ theories of education. Journal of Educational Psychology, 77, 683–692.CrossRefGoogle Scholar
  43. Norman, G. (2010). Likert scales, levels of measurement and the “laws”. Advance in Health Science Education, 15, 625–632. Retrieved from Springer: http://www.fammed.ouhsc.edu/research/FMSRE%20Orientation%20&%20Handout%20Materials/Handouts%205%20Science/Likert%20Scales.pdf.CrossRefGoogle Scholar
  44. Núñez, J. L., Martín-Albo, J., & Navarro, J. G. (2005). Validación de la versión española de la ëchelle de motivation en éducation. Psicothema, 17(2), 334–349.Google Scholar
  45. Núñez, J. L., Martín-Albo, J., Navarro, J. G., & Grijalvo, F. (2006). Validación de la Escala de Motivación Educativa (EME) en Paraguay. Revista Interamericana de Psicología, 40(2), 185–192.Google Scholar
  46. Nuñez, J. L., Martín-Albo, J., Navarro, J. G., & Suárez, Z. (2010). Adaptación y validación de la versión española de la escala de motivación educativa en estudiantes de educación secundaria postobligatoria. Estudios de Psicología, 31(1), 89–100.CrossRefGoogle Scholar
  47. Nunnally, J. C., & Bernstein, I. (1994). Psychometric theory (3rd ed.). New York: McGraw-Hill.Google Scholar
  48. O’Dwyer, L. M. (2005). Examining the variability of mathematics performance and its correlate using data from TIMSS ’95 and TIMSS ’99. Educational Research and Evaluation, 11, 155–177.CrossRefGoogle Scholar
  49. Palacios, A., Arias, V., & Arias, B. (2014). Attitudes towards mathematics: construction and validation of a measurement. Revista de Psicodidáctica, 19(1), 67–91.CrossRefGoogle Scholar
  50. Pelletier, L. G., Tuson, K. M., & Haddad, N. K. (1997). Client motivation for therapy scale: a measure of intrinsic motivation, extrinsic motivation, and amotivation for therapy. Journal of Personality Assessment in Education, 68, 414–435.CrossRefGoogle Scholar
  51. Ryan, R. M. (1982). Control and information in the intrapersonal sphere: an extension of cognitive evaluation theory. Journal of Personality and Social Psychology, 43(3), 450–461.CrossRefGoogle Scholar
  52. Ryan, R. M., & Connell, J. P. (1989). Perceived locus of causality and internalization: examining reasons for acting in two domains. Journal of Personality and Social Psychology, 57(5), 749–761.CrossRefGoogle Scholar
  53. Ryan, R. M., & Deci, E. L. (2000a). Intrinsic and extrinsic motivations: classic definitions and new directions. Contemporary Educational Psychologist, 25, 54–67.CrossRefGoogle Scholar
  54. Ryan, R. M., & Deci, E. L. (2000b). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78.CrossRefGoogle Scholar
  55. Seegers, G., & Boekaerts, M. (1993). Task motivation and mathematics achievement in actual task situations. Learning and Instruction, 3(2), 133–150.CrossRefGoogle Scholar
  56. Sheldon, K. M., & Kasser, T. (1995). Coherence and congruence: two aspects of personality integration. Journal of Personality and Social Psychology, 68, 531–543.CrossRefGoogle Scholar
  57. Shen, C. (2002). Revisiting the relationship between students’ achievement and their self-perceptions: A cross-national analysis based on TIMSS 1999 data. Assessment in Education, 9, 161–184.CrossRefGoogle Scholar
  58. Smith, K. J., Davy, J. A., & Rosenberg, D. L. (2010). An examination of the validity of the academic motivation scale with a United States business student sample. Psychological Reports, 106, 323–341.CrossRefGoogle Scholar
  59. Stover, J. B., de la Iglesia, G., Boubeta, A., & Fernández Liporace, M. (2012). Academic motivation scale (AMS): adaptation and psychometric analyses for high school and college students. Psychology Research and Behavior Management, 5, 71–83.CrossRefGoogle Scholar
  60. Tapia, M., & Marsh II, G. E. (2004). An instrument to measure mathematics attitudes. Academic Exchange Quarterly, 8(2), 16–21.Google Scholar
  61. Tourangeau, R., Rips, L. J., & Rasinski, K. (Eds.). (2000). The psychology of survey response. Cambridge: Cambridge University Press.Google Scholar
  62. Vallerand, R. J., & Bissonnette, R. (1992). Intrinsic, extrinsic and amotivational styles as predictors of behaviour: a prospective study. Journal of Personality, 60(3), 599–620.CrossRefGoogle Scholar
  63. Vallerand, R. J., Blais, M. R., Briere, N. M., & Pelletier, L. G. (1989). Construction et validation de l’Echelle de Motivation en Éducation (EME). Canadian Journal of Behavioural Science, 21, 323–349.CrossRefGoogle Scholar
  64. Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., & Vallières, E. F. (1992). The academic motivation scale: a measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52, 1003–1017.CrossRefGoogle Scholar
  65. Vallerand, R. J., Pelletier, L. G., Balis, M. R., Brière, N. M., Senécal, C., & Vallieres, E. F. (1993). On the assesment of intrinsic, extrinsic, and amotivation in education: evidence on the concurrent and construct validity of the academic motivation scale. Educational and Psychological Measurement, 53, 159–172.CrossRefGoogle Scholar
  66. Vogt, W. P., Vogt, E. R., Gardner, D. C., & Haeffele, L. M. (2014). Selecting the right analyses for your data: quantitative, qualitative, and mixed methods. New York: The Guilford Publishing.Google Scholar
  67. Wang, J., Hagger, M., & Liu, W. C. (2009). A cross-cultural validiation of perceived locus of causality scale in physical education context. Research Quarterly for Exercise and Sport, 80(2), 313–325.CrossRefGoogle Scholar
  68. Zakaria, E., & Nordin, N. M. (2008). The effects of mathematics anxiety on matriculation students as related to motivation and achievement. Eurasia Journal of Mathematics, Science & Technology Education, 4(1), 27–30.Google Scholar
  69. Zan, R., Brown, L., Evans, J., & Hannula, M. S. (2006). Affect in mathematics education: an introduction. Educational Studies in Mathematics, 63(2), 113–121.CrossRefGoogle Scholar

Copyright information

© Mathematics Education Research Group of Australasia, Inc. 2014

Authors and Affiliations

  1. 1.Department of MathematicsCrescent Girls’ SchoolSingaporeSingapore
  2. 2.Graduate School of EducationUniversity of Western AustraliaPerthAustralia

Personalised recommendations

Cite article

Buy options