Research in Science Education

, Volume 30, Issue 4, pp 403–416 | Cite as

Cognitive development in a secondary science setting

  • Lorna C. Endler
  • Trevor Bond


Observations were made of the progressive change in the cognitive development of 141 students over the course of their secondary education in an Australian private school. Cognitive development was measured in years 8, 10 and 12 usingBond's Logical Orerations Test. Rasch analysis of each of the data sets provided ability estimates for students in the year groups of 1993 (year 8), 1995 (year 10) and 1997 (year 12). Twenty-nine students from the year group of 1993 were tested on all three occasions. We analysed data from these 29 students in order to investigate the children's cognitive development across years 8, 10 and 12. We also examined the influence of the Cognitive Acceleration through Science Education (CASE)Thinking Science program on the cognitive development and scholastic achievement of these students. We found increased mental growth between years 8 and 10 for most students in theThinking Science cohort, which could not be predicted from their starting levels. There was a significant correlation between cognitive development and the scholastic achievement of these students. Although boys as a group were more advanced in cognitive development than girls in years 8 and 10, no difference was found in the rate of cognitive change based on sex up to year 10. However girls showed cognitive gains across years 10–12 which were not found in boys. The students who were new to the school also showed increased cognitive development in years 11 and 12. Students who had experienced theThinking Science course were more cognitively developed than students who joined the school after the intervention had taken place. This study supports the claim of Adey and Shayer that there is a relationship between cognitive development and scholastic achievement, even though we used different measures of cognitive development and scholastic achievement.


Cognitive Development Ability Estimate Scholastic Achievement Formal Thinking Mental Growth 
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  1. Adams, R. J., & Khoo, S-T. (1993).Quest: the Interactive Test Analysis System. Hawthorn, Victoria: Australian Council for Educational Research.Google Scholar
  2. Adey, P. (1992). Gender differences in the application of intellectual processes.Studia Psychologica, 34, 225–245.Google Scholar
  3. Adey, P., & Shayer, M. (1990). Accelerating the development of formal thinking in middle and high school students.Journal of Research in Science Teaching, 27, 267–285.Google Scholar
  4. Adey, P., & Shayer, M. (1994).Really raising standards. London: Routledge.Google Scholar
  5. Adey, P., Shayer, M., & Yates, C. (1989). Cognitive acceleration: The effects of two years of intervention in science classes. In P. Adey (Ed.),Adolescent development and school science (pp. 240–248). Lewes, UK: Falmer Press.Google Scholar
  6. Adey, P. S., Shayer, M., & Yates, C. (1995).Thinking science (2nd ed). London: Nelson.Google Scholar
  7. Andrich, D. (1988).Rasch models for measurement. Newbury Park, CA: Sage.Google Scholar
  8. Bond, T. G. (1976),The development, validation and use of a test to assess Piaget'sf Formal stage of logical operations. Unpublished doctoral thesis, James Cook University of North Queensland, Townsville, Australia.Google Scholar
  9. Bond, T. G. (1989). An investigation of the scaling of Piagetian formal operations. In P. Adey (Ed.),Adolescent development and school science (pp. 334–341). Lewes, UK: Falmer Press.Google Scholar
  10. Bond, T. G. (1995a). Piaget and measurement I: The twain really do meet.Archives de Psychologie, 63, 71–87.Google Scholar
  11. Bond T. G. (1995b). Piaget and measurement II: Empirical validation of the Piagetian model.Archives de Psychologie, 63, 155–185.Google Scholar
  12. Bond, T. G., & Fox, C. M. (in press).Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah, NJ: Erlbaum.Google Scholar
  13. Christiansson, D. J. (1983).An investigation of the relationship between cognitive developmental stage and quantitative skills in college students. Unpublished doctoral dissertation, University of the South Pacific, Fiji.Google Scholar
  14. Hautamäki, J. (1989). The application of a Rasch model on Piagetian measures of stages of thinking. In P. Adey (Ed.),Adolescent development and school science (pp. 342–350). Lewes, UK: Falmer Press.Google Scholar
  15. Inhelder, B., & Piaget, J. (1955/58).The growth of logical thinking from childhood to adolescence: An essay on the construction of formal operational structures. London: Routledge & Kegan Paul.Google Scholar
  16. Jackson, S. (1965). The growth of logical thinking in normal and subnormal children.British Journal of Educational Psychology, 35, 255–258.Google Scholar
  17. King, J., & Bond, T. G. (1996). A Rasch analysis of a measure of computer anxiety.Journal of Educational Computing Research, 14, 49–65CrossRefGoogle Scholar
  18. Kuhn, D., & Angelev, J. (1976). An experimental study of the development of formal operational thought.Child Development, 47, 607–706.Google Scholar
  19. Lawson, A. E., & Blake, A. J. D. (1976). Concrete and formal thinking abilities in high school biology students as measured by three separate instruments.Journal of Research in Science Teaching, 13(3), 227–235.Google Scholar
  20. Lawson, A. E., & Snitgen, D. A. (1982). Teaching formal reasoning in a college biology course for preservice teachers.Journal of Research in Science Teaching, 19, 233–248.Google Scholar
  21. Lovell, K. (1961). A follow up of Inhelder and Piaget'sThe Growth of Logical Thinking.British Journal of Educational Psychology, 52(2), 143–153.Google Scholar
  22. Rosenthal, D. A. (1979). The acquisition of formal operations—the effect of two training procedures.Journal of Genetic Psychology, 134, 125–140.Google Scholar
  23. Shayer, M. (1998). The long term effects of cognitive acceleration on pupils' school of achievement (Online). Available (September 1, 1998)Google Scholar
  24. Shayer, M., & Adey, P. (1981).Towards a science of science teaching. London: Heinemann.Google Scholar
  25. Shayer M., Küchemann, D. E., & Wylam, H. (1976). The distribution of Piagetian stages of thinking in British middle and secondary school children.British Journal of Educational Psychology, 46, 164–173.Google Scholar
  26. Shayer, M., & Wylam, H. (1978). The distribution of Piagetian stages of thinking in British middle. and secondary school children. II 14- to 16- year olds and sex differentials.British Journal of Educational Psychology, 48, 62–70.Google Scholar
  27. Smith, L., & Knight, P. (1992). Adolescent reasoning tests with history content.Archives de Psychologie, 60, 225–242.Google Scholar

Copyright information

© Australasian Science Education Research Association 2000

Authors and Affiliations

  1. 1.Teacher Education Program, Graduate School of EducationUniversity of CaliforniaSanta BarbaraUSA
  2. 2.School of EducationJames Cook UniversityTownsvilleAustralia

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