Students’ Attitudes, Engagement and Confidence in Mathematics and Statistics Learning: ICT, Gender, and Equity Dimensions

  • Anastasios N. Barkatsas
Part of the Advances in Mathematics Education book series (AME)


In this chapter the findings of five studies are reported. Two research instruments were used: the Mathematics and Technology Attitudes Scale (MTAS), and the Survey of Attitudes Toward Statistics Scale (SATS). The aims, methods, data analyses, selected findings and conclusions are presented, as well as implications for the teaching and learning of mathematics and statistics. The studies involved samples from Australia and Greece. Findings from the three MTAS studies revealed that there is a complex nexus of relationships between secondary mathematics students’ mathematics confidence, confidence with technology, attitude to learning mathematics with technology, affective engagement and behavioural engagement, achievement, and gender. Findings from the SATS studies indicated that male Greek tertiary students had more positive attitudes toward statistics than female students; there was no gender gap for the Australian tertiary students. Secondary students’ attitudes towards ICT use for mathematics learning require further scrutiny in order to bring about gender equity and to facilitate improved outcomes for all students. Gender and cultural sensitivity are paramount in the instructional planning, decision making, and implementation of secondary mathematics and tertiary statistics.


Positive Attitude Female Student Mathematics Achievement Secondary Student Behavioural Engagement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Araki, L. T., & Shultz, K. S. (1995, April). Student attitudes toward statistics and their retention of statistical concepts. Paper presented at the annual meeting of the Western Psychological Association, Los Angeles. Google Scholar
  2. Artigue, M. (2002). Learning mathematics in a CAS environment: The genesis of a reflection about instrumentation and the dialectics between technical and conceptual work. International Journal of Computers for Mathematical Learning, 7, 245–274. CrossRefGoogle Scholar
  3. Buck, J. L. (1985). A failure to find gender differences in statistics achievement. Teaching of Psychology, 12, 100. CrossRefGoogle Scholar
  4. Barkatsas, A. N. (2005). A new scale for monitoring students’ attitudes to learning mathematics with technology (MTAS). In P. Clarkson, A. Downton, D. Gronn, M. Horne, A. McDonough, R. Pierce & A. Roche (Eds.), Building connections: Theory, research and practice (Vol. 1, pp. 129–137). Proceedings of the 28th Annual Conference of the Mathematics Education Group of Australasia. Melbourne: MERGA. Google Scholar
  5. Barkatsas, A., Forgasz, H., & Leder, G. C. (2001). The gender stereotyping of mathematics: Cultural dimensions. In J. Bobis, B. Perry & M. Mitchelmore (Eds.), Numeracy and beyond. Sydney: Mathematics Education Research Group of Australasia. Google Scholar
  6. Barkatsas, A. N., Kasimatis, K., & Gialamas, V. (2009). Learning secondary mathematics with technology: Exploring the complex interrelationship between students’ attitudes, engagement, gender and achievement. Computers & Education, 52, 562–570. CrossRefGoogle Scholar
  7. Bechrakis, T., Gialamas, V., & Barkatsas, A. N. (2011). Survey of attitudes toward statistics (SATS): An investigation of its construct validity and its factor invariance by gender. International Journal of Theoretical Educational Practice, 1, 1–15. Google Scholar
  8. Bennison, A., & Goos, M. (2010). Learning to teach mathematics with technology: A survey of professional development needs, experiences and impacts. Mathematics Education Research Journal, 2(1), 31–56. CrossRefGoogle Scholar
  9. Bradley, D. R., & Wygant, C. R. (1998). Male and female differences in anxiety about statistics are not reflected in performance. Psychological Reports, 80, 245–246. CrossRefGoogle Scholar
  10. Cashin, S. E., & Elmore, P. B. (2005). The survey of attitudes toward statistics scale: A construct validity study. Educational and Psychological Measurement, 65, 509–524. CrossRefGoogle Scholar
  11. Coakes, S. J., & Steed, L. G. (1999). SPSS: Analysis without anguish. Australia: John Wiley and Sons Ltd. Google Scholar
  12. Drijvers, P. (2000). Students encountering obstacles using CAS. The International Journal of Computers for Mathematical Learning, 5(3), 189–209. CrossRefGoogle Scholar
  13. Earp, M. S. (2007). Development and validation of the statistics anxiety measure. Unpublished Doctoral Dissertation, University of Denver, USA. Google Scholar
  14. Elmore, P. B., & Lewis, E. L. (1991, April). Statistics and computer attitudes and achievement of students enrolled in applied statistics: Effect of a computer laboratory. Paper presented at the annual meeting of the American Educational Research Association, Chicago. Google Scholar
  15. Elmore, P. B., Lewis, E. L., & Bay, M. L. G. (1993, April). Statistics achievement: A function of attitudes and related experiences. Paper presented at the annual meeting of the American Educational Research Association, Atlanta, GA. Google Scholar
  16. Elmore, P. B., & Vasu, E. S. (1986). A model of statistics achievement using spatial ability, feminist attitudes, and mathematics-related variables as predictors. Educational and Psychological Measurement, 46, 215–222. CrossRefGoogle Scholar
  17. Fennema, E., & Sherman, J. (1976). Fennema–Sherman mathematics attitudes scales. Instruments designed to measure attitudes toward the learning of mathematics by females and males. Abstracted in the JSAS Catalog of Selected Documents in Psychology, 6(1), 31. (Ms No. 1225). Google Scholar
  18. Forgasz, H., Leder, G. C., & Barkatsas, A. (1998). Mathematics—For boys? For girls? Vinculum, 35(3), 15–19. Google Scholar
  19. Forgasz, H., Leder, G. C., & Barkatsas, A. N. (1999). Of course I can(’t) do mathematics: Ethnicity and the stereotyping of mathematics. In J. M. Truran & K. M. Truran (Eds.). Making the difference. Adelaide: Mathematics Education Research Group of Australasia. Google Scholar
  20. Forgasz, H. J., & Leder, G. C. (2001). A+ for girls, B for boys: Changing perspectives on gender equity and mathematics. In B. Atweh, H. Forgasz, & B. Nebres (Eds). Sociocultural research on mathematics education: An international perspective (pp. 347–366). Mahwah: Lawrence Erlbaum & Associates. Google Scholar
  21. Fredricks, J., Blumenfeld, P., & Paris, A. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. CrossRefGoogle Scholar
  22. Galbraith, P., & Haines, C. (1998). Disentangling the nexus: Attitudes to mathematics and technology in a computer learning environment. Educational Studies in Mathematics, 36, 275–290. CrossRefGoogle Scholar
  23. Guin, D., & Trouche, L. (1999). The complex process of converting tools into mathematical instruments: The case of calculators. International Journal of Computers for Mathematical Learning, 3, 195–227. CrossRefGoogle Scholar
  24. Harvey, A. L., Plake, B. S., & Wise, S. L. (1985, April). The validity of six beliefs about factors related to statistics achievement. Paper presented at the annual meeting of the American Educational Research Association, Chicago. Google Scholar
  25. Heid, M. K., & Edwards, M. T. (2001). Computer algebra systems: Revolution or retrofit for today’s mathematics classrooms? Theory and Practice, 40(2), 128–136. CrossRefGoogle Scholar
  26. Lebart, L., Morineau, A., Lambert, T., & Pleuvret, P. (2001). Manuel de référence de SPAD. Montreuil: CISIA-CERESTA. Google Scholar
  27. Marks, H. M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle and high school years. American Educational Research Journal, 39(1), 153–184. CrossRefGoogle Scholar
  28. Middleton, J. A. (1999). Motivation for achievement in mathematics: Findings, generalisations, and criticisms of the research. Journal for Research in Mathematics Education, 30(1), 65–88. CrossRefGoogle Scholar
  29. McLeod, D. B. (1992). Research on affect in mathematics education: A reconceptualisation. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 575–596). New York: MacMillan. Google Scholar
  30. Newmann, F. M. (1989). Student engagement in high school mathematics. Educational Leadership, 46(5), 34–36. Google Scholar
  31. Onwuegbuzie, A. J. (1995). Statistics test anxiety and female students. Psychology of Women Quarterly, 19, 413–418. CrossRefGoogle Scholar
  32. Pajares, M. F. (1992). Teachers’ beliefs and educational research: cleaning up a messy construct. Review of Educational Research, 62(3), 307–322. CrossRefGoogle Scholar
  33. Pierce, R., & Stacey, K. (2004). A framework for monitoring progress and planning teaching toward the effective use of computer algebra systems. International Journal of Computers for Mathematical Learning, 9, 59–93. CrossRefGoogle Scholar
  34. Pierce, R., Stacey, K., & Barkatsas, A. N. (2007). A scale for monitoring students’ attitudes to learning mathematics with technology. Computers and Education, 48(2), 285–300. CrossRefGoogle Scholar
  35. Reed, C. R., Drijvers, P., & Kirschner, P. A. (2010). Effects of attitudes on learning mathematics with computer tools. Computers and Education, 55(1), 1–15. CrossRefGoogle Scholar
  36. Roberts, D. M., & Bilderback, E. W. (1980). Reliability and validity of a statistics attitude survey. Educational and Psychological Measurement, 40, 235–238. CrossRefGoogle Scholar
  37. Roberts, D. M., & Saxe, J. E. (1982). Validity of a statistics attitude survey: A follow-up study. Educational and Psychological Measurement, 42, 907–912. CrossRefGoogle Scholar
  38. Schau, C., Stevens, J., Dauphinee, T. L., & Del Vecchio, A. (1995). The development and validation of the survey of attitudes toward statistics. Educational and Psychological Measurement, 55, 868–875. CrossRefGoogle Scholar
  39. Schram, C. M. (1996). A meta-analysis of gender differences in applied statistics achievement. Journal of Educational and Behavioral Statistics, 21(1), 55–70. Google Scholar
  40. Tanner, H., Jones, S., Beauchamp, G., & Kennewell, S. (2010). Interactive whiteboards and all that Jazz: Analysing classroom activity with interactive technologies. In L. Sparrow, B. Kissane, & C. Hurst (Eds.), Shaping the future of mathematics education: Proceedings of the 33rd annual conference of the Mathematics Education Research Group of Australasia. Fremantle: MERGA. Google Scholar
  41. Vale, C., & Bartholomew, H. (2008). Gender and mathematics. In H. Forgasz, A. Barkatsas, A. Bishop, B. Clarke, S. Keast, W.-T. Seah, & P. Sullivan (Eds.), Research in mathematics education in Australasia 2004–7 (pp. 271–290). Rotterdam, The Netherlands: Sense Publishers. Google Scholar
  42. Vale, C., & Leder, G. (2004). Student views of computer-based mathematics in the middle years: Does gender make a difference? Educational Studies in Mathematics, 56, 287–312. CrossRefGoogle Scholar
  43. Ware, M. E., & Chastain, J. D. (1991). Developing selection skills in introductory statistics. Teaching of Psychology, 18(4), 219–222. CrossRefGoogle Scholar
  44. Waters, L. K., Martelli, T. A., Zakrajsek, T., & Popovich, P. M. (1988). Attitudes toward statistics: An evaluation of multiple measures. Educational and Psychological Measurement, 48, 513–516. CrossRefGoogle Scholar
  45. Watt, H. M. G. (2006). The role of motivation in gendered educational and occupational trajectories related to maths. Educational Research and Evaluation, 12(4), 305–322. CrossRefGoogle Scholar
  46. Weglinsky, H. (1998). Does it compute? The relationship between educational technology and student achievement in mathematics. Princeton: Educational Testing Service Policy Information Center. Google Scholar
  47. Wise, S. L. (1985). The development and validation of a scale measuring attitudes toward statistics. Educational and Psychological Measurement, 45, 401–405. Google Scholar
  48. Zimmer, J. C., & Fuller, D. K. (1996). Factors affecting undergraduate performance in statistics: A review of the literature. Paper presented at the annual meeting of the Mid-South Educational Research Association, Tuscaloosa, AL. (ERIC Document Reproduction Service No. ED406424.) Google Scholar
  49. Zyngier, D. (2007). Listening to teachers-listening to students: Substantive conversations about resistance, empowerment and engagement. Teachers and Teaching: Theory and Practice, 13(4), 327–347. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Monash UniversityMelbourneAustralia

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