2,582
Views
6
CrossRef citations to date
0
Altmetric
Articles

Improving preservice chemistry teachers’ content knowledge through intervention activities

Pages 1238-1261 | Received 18 Jul 2016, Accepted 18 May 2017, Published online: 16 Jun 2017

References

  • Abell, S. K. (2007). Research on science teacher knowledge. In S. K. Abell, & N. G. Lederman (Eds.), Handbook of research on science education (pp. 1105–1150). Mahwah, NJ: Lawrence Erlbaum.
  • Arzi, H. J., & White, R. T. (2007). Change in teachers’ knowledge of subject matter: A 17-year longitudinal study. Science Education, 92(2), 221–251. doi: 10.1002/sce.20239
  • Barber, M., & Mourshed, M. (2007). How the world’s best performing school systems came out on top. London: McKinsey and Company.
  • Chi, M. T. H. (1992). ‘Conceptual change within and across ontological categories: Examples from learning and discovery in science’. In R. N. Giere (Ed.), Cognitive models in science (vol. XV, pp. 129–186). Minneapolis: University of Minnesota Press.
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Hillsdale, NJ: L. Erlbaum Associates.
  • Coll, R., & Treagust, D. (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
  • Crown. (2011). Teachers’ Standards. Guidance for school leaders, school staff and governing bodies. Retrieved June 3, 2015, from https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/301107/Teachers__Standards.pdf
  • Deng, Z. (2007). Knowing the subject matter of a secondary school science subject. Journal of Curriculum Studies, 39(5), 503–535. doi: 10.1080/00220270701305362
  • Dole, J. A. (2000). ‘Readers, texts and conceptual change learning’. Reading & Writing Quarterly, 16, 99–118. doi: 10.1080/105735600277980
  • Driver, R., & Erickson, G. (1983). ‘Theories-in-action: Some theoretical and empirical issues in the study of students’ conceptual frameworks in science’. Studies in Science Education, 10, 37–60. doi: 10.1080/03057268308559904
  • Driver, R., Squires, A., Rushworth, P., & Wood-Robinson, V. (1994). Making sense of secondary science: Research into children’s ideas. London: Routledge.
  • Druva, C. A., & Anderson, R. D. (1983). Science teacher characteristics by teacher behavior and by student outcome: A meta-analysis of research. Journal of Research in Science Teaching, 20, 467–479. doi: 10.1002/tea.3660200509
  • Duit, R. H., & Treagust, D. F. (2012). Conceptual change: Still a powerful framework for improving the practice of science instruction. In K. C. D. Tan, & K. Mijung (Eds.), Issues and challenges in science education research (pp. 43–54). New York: Springer.
  • Evagorou, M., Dillon, J., Viiri, J., & Albe, V. (2015). Preservice science teacher preparation in Europe: Comparing preservice teacher preparation programs in England, France, Finland and Cyprus. Journal of Science Teacher Education, 26, 99–115. doi: 10.1007/s10972-015-9421-8
  • Fan, X. (2001). Statistical significance and effect size in education research: Two sides of a coin. The Journal of Educational Research, 94(5), 275–282. doi: 10.1080/00220670109598763
  • Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7(2), 155–170. doi: 10.1207/s15516709cog0702_3
  • Gilbert, J. K., & Watts, D. M. (1983). ‘Concepts, misconceptions and alternative conceptions: Changing perspectives in science education’. Studies in Science Education, 10, 61–98. doi: 10.1080/03057268308559905
  • Goodwin, A. L. (2012). Teaching as a profession: Are we there yet? In C. Day (Ed.), The Routledge international handbook of teacher and school development (pp. 44–56). Abingdon: Taylor & Francis.
  • Grosslight, L., Unger, C., Jay, E., & Smith, C. (1991). Understanding models and their use in science: Conceptions of middle and high school students and experts. Journal of Research in Science Teaching, 28, 799–822. doi: 10.1002/tea.3660280907
  • Harrison, A. G., & Treagust, D. F. (2000). A typology of school science models. International Journal of Science Education, 22(9), 1011–1026. doi: 10.1080/095006900416884
  • Hashweh, M. Z. (1987). Effects of subject matter knowledge in the teaching of biology and physics. Teaching and Teacher Education, 3, 109–120. doi: 10.1016/0742-051X(87)90012-6
  • IBM. (2013) IBM SPSS Statistics (Version 22.0.0.0) [Computer program]
  • Kapon, S. & diSessa, A. A. (2012). Reasoning through instructional analogies. Cognition and Instruction, 30(3), 261–310. doi: 10.1080/07370008.2012.689385
  • Khan, K. S., Davies, D. A., & Gupta, J. K. (2001). Formative self-assessment using multiple true-false questions on the Internet: Feedback according to confidence about correct knowledge. Medical Teacher, 23(2), 158–163. doi: 10.1080/01421590031075
  • Kind, V., & Kind, P. M. (2011). Beginning to teach chemistry: How personal and academic characteristics of preservice science teachers compare with their understandings of basic chemical ideas. International Journal of Science Education, 33(15), 2123–2158. doi: 10.1080/09500693.2010.542498
  • Kind, V. (2009). A conflict in your head: An exploration of trainee science teachers’ subject matter knowledge development and its impact on teacher self-confidence. International Journal of Science Education, 31(11), 1529–1562. doi: 10.1080/09500690802226062
  • Kind, V. (2014). A degree is not enough: A quantitative study of aspects of preservice science teachers’ chemistry content knowledge. International Journal of Science Education, 36(8), 1313–1345. doi: 10.1080/09500693.2013.860497
  • Käpylä, M., Heikkinen, J-P, & Asunta, T. (2009). Influence of content knowledge on pedagogical content knowledge: The case of teaching photosynthesis and plant growth. International Journal of Science Education, 31(10), 1395–1415. doi: 10.1080/09500690802082168
  • Millar, R. (2013). Assessing beginning teachers’ subject knowledge: How reliable is self-audit? Paper presented at the ESERA conference, Nicosia.
  • Mourshed, M., Chijioke, C., & Barber, M. (2010). How the world’s most improved school systems keep getting better. London: McKinsey and Company.
  • Muijs, D. (2011). Doing quantitative research in education with SPSS. London: SAGE.
  • Niebert, K., Marsch, S., & Treagust, D. (2012). Understanding needs embodiment: A theory-guided reanalysis of the role of metaphors and analogies in understanding science. Science Education, 96(5), 849–877. doi: 10.1002/sce.21026
  • NSTA. (2004). Position statement: Science teacher preparation. Retrieved January 15, 2016, from http://www.nsta.org/docs/PositionStatement_TeacherPrep.pdf
  • Park, E. J., & Light, G. (2009). ‘Identifying atomic structure as a threshold concept: Student mental models and troublesomeness’. International Journal of Science Education, 31(2), 233–258. doi: 10.1080/09500690701675880
  • Potvin, P. (2017). The coexistence claim and its possible implications for success in teaching for conceptual “change”. European Journal of Science and Mathematics Education, 5(1), 55–66.
  • Promethean. (2008). Promethean Activ software Expression edition (Version 1.0.4522) [Computer program].
  • Rohrer, T. (2005). Image schemata in the brain. In B. Hampe, & J. Grady (Eds.), From perception to meaning: Images schemas in cognitive linguistics (pp. 165–196). Berlin: Mouton de Gruyter.
  • Sanders, L. R., Borko, H., & Lockard, J. D. (1993). Secondary science teachers’ knowledge base when teaching science courses in and out of their area of certification. Journal of Research in Science Teaching, 30(7), 723–736. doi: 10.1002/tea.3660300710
  • Schraw, G. (2009). Measuring metacognitive judgments. In D. J. Hacker, J. Dunlosky, & A. C. Graesser (Eds.), Handbook of metacognition in education (pp. 415–429). New York, NY: Routledge, Taylor & Francis.
  • SCORE. (2015). Principles for routes into teaching the sciences at secondary level. Retrieved June 3, 2015, from http://www.score-education.org/media/16294/final20score20ite20position20paper20-20designed.pdf
  • Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14. doi: 10.3102/0013189X015002004
  • Taber, K. S. (1998). The sharing-out of nuclear attraction: Or I can’t think about Physics in Chemistry. International Journal of Science Education, 20(8), 101–1001. doi: 10.1080/0950069980200807
  • Taber, K. S. (2002). Chemical misconceptions—prevention, diagnosis and cure, volume II: Classroom resources. London: RSC.
  • Taber, K. S., & Tan, K. C. D. (2007). Exploring learners’ conceptual resources: Singapore A level students’ explanations in the topic of ionisation energy. International Journal of Science and Mathematics Education, 5, 375–392. doi: 10.1007/s10763-006-9044-9
  • Taber, K. S., & Tan, K. C. D. (2011). The insidious nature of ‘hard-core’ alternative conceptions: Implications for the constructivist research programme of patterns in high school students’ and pre-service teachers’ thinking about ionisation energy. International Journal of Science Education, 33(2), 259–297. doi: 10.1080/09500691003709880
  • Tan, K.-C. D., Taber, K. S., Goh, N.-K., & Chia, L.-S. (2005). The ionisation energy diagnostic instrument: A two-tier multiple choice instrument to determine high school students’ understanding of ionisation energy. Chemistry Education Research & Practice, 6(4), 180–197. doi: 10.1039/B5RP90009C
  • Tan, K.-C. D., & Taber, K. S. (2009). Ionization energy: Implications of preservice teachers’ conceptions. Journal of Chemical Education, 86(5), 623–629. doi: 10.1021/ed086p623
  • Tan, K. C. D., Taber, K. S., Liu, X., Coll, R. K., Lorenzo, M., Li, J., … Chia, L. S. (2008). Students’ conceptions of ionisation energy: A cross cultural study. International Journal of Science Education, 30(2), 263–283. doi: 10.1080/09500690701385258
  • Taylor, A. K., & Kowalski, P. (2004). Naive psychological science: The prevalence, strength and sources of misconceptions. The Psychological Record, 54, 15–25. doi: 10.1007/BF03395459
  • Trumper, R. (2001). ‘A cross-college age study of science and nonscience students’ conceptions of basic astronomy concepts in preservice training for high-school teachers’. Journal of Science Education and Technology, 10(2), 189–195. doi: 10.1023/A:1009477316035
  • TSO. (2010). The importance of teaching – The Schools White Paper 2010. Retrieved June 3, 2015, from http://webarchive.nationalarchives.gov.uk/20130401151715/https://www.education.gov.uk/publications/eOrderingDownload/CM-7980.pdf
  • Wakabayashi, T., & Guskin, K. (2010). The effect of an ‘‘unsure’’ option on early childhood professionals’ Pre- and post-training knowledge assessments. American Journal of Evaluation, 31(4), 486–498. doi: 10.1177/1098214010371818
  • Wallace, J. (2005). Reading accounts: Central themes in science teachers’ descriptions of exemplary teaching practice, Ch.8. In S. Alsop, L. Bencze, & E. Pedretti (Eds.), Analysing exemplary science teaching (pp. 171–182). Maidenhead: Open University Press.
  • Wayne, A., & Youngs, P. (2003). Teacher characteristics and student achievement gains: A review. Review of Educational Research, 73, 89–122. doi: 10.3102/00346543073001089
  • Wheeldon, R., Akinson, R., Dawes, A., & Levinson, R. (2012). Do high school chemistry examinations inhibit deeper level understanding of dynamic reversible chemical reactions? Research in Science and Technological Education, 30(2), 107–130. doi: 10.1080/02635143.2012.692362
  • Wheeldon, R. (2012). Examining preservice teachers’ Use of atomic models in explaining subsequent ionisation energy values. Journal of Science Education and Technology, 21, 403–422. doi: 10.1007/s10956-011-9333-0
  • Wilbers, J., & Duit, R. (2006). Post-festum and heuristic analogies. In P. J. Aubusson, A. G. Harrison, & S. M. Richie (Eds.), Metaphor and analogy in science education (pp. 37–49). Dordrecht, NL: Springer.