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The Influence of a University-School Partnership on Pre-service Teachers’ Perceived Preparedness and Views on Teaching and Learning S.T.E.M

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Abstract

The purpose of this study is to explore how a university-school partnership in Canada supports pre-service teachers in developing positive perceptions about learning and teaching Science, Technology, Engineering, and Mathematics (STEM) in their teacher preparation programs. This initiative provided opportunities for pre-service teachers to understand STEM as a boundary-object (i.e. S.T.E.M) and work in communities of practice toward creating and implementing lesson plans with K-12 students. Using a non-random pre- and post-intervention research design, we examine the effectiveness of this initiative by analyzing survey responses from 43 pre-service teachers. The survey consisted of 37 Likert-scale responses measuring agreement on statements relating to pre-service teachers’ feelings about learning and teaching S.T.E.M. The initiative had a positive effect on pre-service teachers’ perceptions and feeling of competence in teaching mathematics and S.T.E.M as a whole, their perceptions of learning S.T.E.M, and views on teaching S.T.E.M. Also, findings revealed some differences in responses by age, undergraduate field of study, and program stream. We discuss these findings and their implications for pre-service teaching programs, emphasizing S.T.E.M as a boundary-object and building communities of practice as 2 primary factors.

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Notes

  1. In the fall, half of the group were in mathematics and the other half in science class. In the winter, these groups switched.

  2. Research ethics approval was granted by our university’s Research Ethics Committee.

  3. Notably, the survey used in this study was researcher-created. We did not consult other surveys. While other surveys may contain similar questions, we did not consult those surveys.

  4. Because the results from the Shapiro–Wilk test were mixed, we also ran paired t-tests for each subscale (results not shown). In comparing the mean in the t-tests, the subscales that were determined statistically significant matched the results from the Wilcoxon signed-rank test. Cohen’s d effect sizes (using the means of pre- and post-survey results for each subscale) also revealed similar effect sizes to the ones reported in Table 2.

  5. To account for the nonnormal distribution of some of the subscales (our dependent variables), we use robust regression techniques. Residual analysis was also performed prior to each regression and only one subscale (Feelings PreSTEM) raised concerns; robust regression accounted for this (see McKean et al., 1993).

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Funding

This research was funded by a Social Sciences and Humanities Research Council, Partnership Engage Grant.

Author information

Authors and Affiliations

  1. Crandall University, 333 Gorge Road, Moncton, NB, E1G 3H9, Canada

    Cathlene Hillier & Diandra Singh

  2. Utah State University, Logan, USA

    Tye Campbell

Authors
  1. Cathlene Hillier
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  2. Diandra Singh
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  3. Tye Campbell
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Corresponding author

Correspondence to Cathlene Hillier.

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Ethics Approval and Consent to Participate

This research is original work and received ethics approval through Crandall University’s Research Ethics Committee. All participants provided informed consent.

Appendices

Appendix 1. B.Ed. student survey (for each statement, participants could select strongly disagree, disagree, neutral, agree, or strongly agree)

1. I like science.

2. I like to use technology.

3. I like engineering.

4. I like mathematics.

5. I learn STEM (Science, Technology, Engineering, and Mathematics) by doing experiments or other hands-on activities.

6. I learn STEM (Science, Technology, Engineering, and Mathematics) when the teacher explains it to me. (Reverse coded).

7. I learn STEM (Science, Technology, Engineering, and Mathematics) by talking and listening to peers in groups.

8. I believe I am good at science.

9. I believe I am good at using technology.

10. I believe I am good at engineering.

11. I believe I am good at math.

12. I have fun doing science activities.

13. I have fun doing technology activities.

14. I have fun doing engineering activities.

15. I have fun doing math activities.

16. It is easy for me to do science.

17. It is easy for me to do technology.

18. It is easy for me to do engineering.

19. It is easy for me to do math.

20. I love to learn about science.

21. I love to learn about technology.

22. I love to learn about engineering.

23. I love to learn about math.

24. When I do STEM, I feel lost. (Reverse coded).

25. When I do STEM, I feel happy.

26. When I do STEM, I feel angry. (Reverse coded).

27. When I do STEM, I feel bored. (Reverse coded).

28. When I do STEM, I feel really into it.

29. I believe students can learn STEM from my teaching.

30. I can learn to teach STEM if I try hard.

31. I am confident in teaching science.

32. I am confident in teaching technology.

33. I am confident in teaching engineering.

34. I am confident in teaching mathematics.

35. STEM should be taught using hands-on activities.

36. STEM should be taught using direct instruction. (Reverse coded).

37. STEM should be taught by allowing students to discuss ideas in groups.

Appendix 2

Please see Table 5.

Table 5 The Shapiro–Wilk normality test
Full size table

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Hillier, C., Singh, D. & Campbell, T. The Influence of a University-School Partnership on Pre-service Teachers’ Perceived Preparedness and Views on Teaching and Learning S.T.E.M. Int J of Sci and Math Educ (2024). https://doi.org/10.1007/s10763-024-10460-8

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