Validating a scale to measure engineers’ perceived self-efficacy for engineering education outreach


Autoři: Laura Fogg-Rogers aff001;  Tim Moss aff002
Působiště autorů: Science Communication Unit, University of the West of England, Bristol, England, United Kingdom aff001;  Department of Engineering Design and Mathematics, University of the West of England, Bristol, England, United Kingdom aff002;  Department of Psychology, University of the West of England, Bristol, England, United Kingdom aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0223728

Souhrn

Education outreach in schools has been identified as a critical route to influence children’s perceptions and capabilities for Science, Technology, Engineering, and Mathematics careers. Evidence suggests that providing non-teaching professionals like engineers with training programmes and structured experience can boost perceived self-efficacy to perform education outreach, which in turn means better quality and more frequent public engagement. A validated measure of the construct of perceived self-efficacy for engineering education outreach will be useful for effective science communication participation, research, and practise. This article presents the methods used to develop the Engineering Outreach Self-efficacy Scale (EOSS), along with initial reliability and validation results to support the scale’s use. The 10-item scale was found to have good internal consistency and reliability (Cronbach’s alpha α = .92) with a sample of 160 engineers. The scale had convergent validity with general self-efficacy. Engineers with more experience of education outreach had higher self-efficacy for engineering education outreach. There were no significant differences between male and female engineers. Initial test-retest results showed engineers receiving training in education outreach significantly improved their EOSS scores, indicating capability to detect change over time. It is hoped this scale will prove useful for further evaluation of engineering education outreach and public engagement with science activities.

Klíčová slova:

Careers – Engineering and technology – Engineers – Children – Personality – Personality traits – Questionnaires – Scientists


Zdroje

1. Jeffers AT, Safferman AG, Safferman SI. Understanding K–12 Engineering Outreach Programs. Vol. 130, Journal of Professional Issues in Engineering Education and Practice. 2004. p. 95–108.

2. Fogg-Rogers L, Lewis F, Edmonds J. Paired peer learning through engineering education outreach. Eur J Eng Educ. 2017;42(1).

3. Fogg-Rogers L, Wilkinson C, Weitkamp E. Royal Society Education Outreach Evaluation. 2015.

4. Archer L, Dawson E, DeWitt J, Seakins A, Wong B. “Science capital”: A conceptual, methodological, and empirical argument for extending bourdieusian notions of capital beyond the arts. J Res Sci Teach. 2015;52(7):922–48.

5. Enterprising Science. Improving Science Participation [Internet]. 2017. Available from: http://www.ucl.ac.uk/ioe/departments-centres/departments/education-practice-and-society/science-capital-research/pdfs/improving-science-participation-policy-overview.pdf

6. Stocklmayer SM, Rennie LJ, Gilbert JK. The roles of the formal and informal sectors in the provision of effective science education. Vol. 46, Studies in Science Education. 2010. p. 1–44.

7. Bandiera M, Bruno C. Active/cooperative learning in schools. Vol. 40, Journal of Biological Education. 2006. p. 130–4.

8. Wilkinson C, Sardo S. Killer Facts for Informal Learning [Internet]. 2013. Available from: http://www.wellcome.ac.uk/Education-resources/Education-and-learning/News/2013/WTP053966.htm

9. Laursen S, Liston C, Thiry H, Graf J. What good is a scientist in the classroom? Participant outcomes and program design features for a short-duration science outreach intervention in K-12 classrooms. CBE Life Sci Educ. 2007;6:49–64. doi: 10.1187/cbe.06-05-0165 17339394

10. Research Councils UK. Engaging Young People with Cutting-Edge Research: a guide for researchers and teachers. 2010.

11. STEM Ambassadors. STEM Ambassadors: Making an Impact [Internet]. 2016. Available from: https://www.stem.org.uk/sites/default/files/pages/downloads/STEM-Ambassadors-impact-report.pdf

12. TNS. Factors affecting public engagement by researchers [Internet]. 2015. Available from: https://wellcome.ac.uk/sites/default/files/wtp060033_0.pdf

13. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev. 1977;84(2):191–215. doi: 10.1037//0033-295x.84.2.191 847061

14. Perkins J. Professor John Perkins’ Review of Engineering Skills [Internet]. 2013. Available from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/254885/bis-13-1269-professor-john-perkins-review-of-engineering-skills.pdf

15. EngineeringUK. The state of engineering [Internet]. 2017. Available from: https://www.engineeringuk.com/research/

16. Office for National Statistics. Ethnicity and National Identity in England and Wales: 2011 [Internet]. 2011. Available from: https://www.ons.gov.uk/peoplepopulationandcommunity/culturalidentity/ethnicity/articles/ethnicityandnationalidentityinenglandandwales/2012-12-11

17. Callahan LS, Nadelson J. A Comparison of Two Engineering Outreach Programs for Adolescents. J STEM Educ Innov Res Jan-Mar 2011. 2011;12(1/2):43–54.

18. Molina-Gaudo P, Baldassarri S, Villarroya-Gaudo M, Cerezo E. Perception and intention in relation to engineering: A gendered study based on a one-day outreach activity. IEEE Trans Educ. 2010;53(1):61–70.

19. Martínez-Jiménez P, Salas-Morera L, Pedrós-Pérez G, Cubero-Atienza AJ, Varo-Martínez M. OPEE: An outreach project for engineering education. IEEE Trans Educ. 2010;53(1):96–104.

20. Pickering M, Ryan E, Conroy K, Gravel B, Portsmore M. The Benefit of Outreach to Engineering Students. In: Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition. 2004.

21. Direito I, Pereira A, Duarte AM de O. Engineering Undergraduates’ Perceptions of Soft Skills: Relations with Self-Efficacy and Learning Styles. Procedia—Soc Behav Sci. 2012;55:843–51.

22. Royal Academy of Engineering. Learning to be an engineer [Internet]. 2017. Available from: https://www.raeng.org.uk/ltbae

23. Besley JC, Oh SH, Nisbet M. Predicting scientists’ participation in public life. Public Underst Sci. 2013;22(8):971–87. doi: 10.1177/0963662512459315 23825262

24. France B, Cridge B, Fogg-Rogers L. Organisational Culture and Its Role in Developing a Sustainable Science Communication Platform. Int J Sci Educ Part B. 2015;1–15.

25. Poliakoff E, Webb TL. What Factors Predict Scientists’ Intentions to Participate in Public Engagement of Science Activities? Sci Commun. 2007 Dec 1;29(2):242–63.

26. Marcinkowski F, Kohring M, Fürst S, Friedrichsmeier A. Organizational Influence on Scientists’ Efforts to Go Public: An Empirical Investigation. Sci Commun. 2014 Feb 1;36(1):56–80.

27. Trench B, Miller S. Policies and practices in supporting scientists’ public communication through training. Sci Public Policy. 2012;39(6):722–31.

28. Peterman K, Robertson Evia J, Cloyd E, Besley JC. Assessing Public Engagement Outcomes by the Use of an Outcome Expectations Scale for Scientists. Sci Commun [Internet]. 2017 Nov 3;39(6):782–97. Available from: https://doi.org/10.1177/1075547017738018

29. Robertson Evia J, Peterman K, Cloyd E, Besley J. Validating a scale that measures scientists’ self-efficacy for public engagement with science. Int J Sci Educ Part B. 2017;1–13.

30. Bandura A. Self-efficacy. Harvard Ment Heal Lett. 1997;13(9):4.

31. Bandura A. Health promotion by social cognitive means. Heal Educ Behav. 2004;31(2):143–64.

32. Flores MA, Day C. Contexts which shape and reshape new teachers’ identities: A multi-perspective study. Teach Teach Educ. 2006;22(2):219–32.

33. Bandura A. Guide for constructing self-efficacy scales. In: Self-Efficacy Beliefs of Adolescents. Information Age Publishing; 2006. p. 307–37.

34. Declerck CH, Boone C, De Brabander B. On feeling in control: A biological theory for individual differences in control perception. Brain Cogn. 2006;62(2):143–76. doi: 10.1016/j.bandc.2006.04.004 16806623

35. Dudo A. Toward a Model of Scientists’ Public Communication Activity: The Case of Biomedical Researchers. Sci Commun. 2013;35(4):476–501.

36. Flake JK, Pek J, Hehman E. Construct Validation in Social and Personality Research. Soc Psychol Personal Sci. 2017;8(4):370–8.

37. Fogg-Rogers L, Sardo M, Boushel C. “Robots Vs Animals”: Establishing a Culture of Public Engagement and Female Role Modeling in Engineering Higher Education. Sci Commun. 2017;39(2).

38. Yoon Yoon S, Evans MG, Strobel J. Validation of the Teaching Engineering Self-Efficacy Scale for K-12 Teachers: A Structural Equation Modeling Approach. J Eng Educ. 2014;103(3):463–85.

39. Fogg-Rogers L, Hobbs LK. Catch 22 –improving visibility of women in science and engineering for both recruitment and retention. J Sci Commun. 2019;

40. National Institutes for Health and Northwestern University. NIH Toolbox [Internet]. 2016. Available from: http://www.healthmeasures.net/explore-measurement-systems/nih-toolbox/obtain-and-administer-measures

41. Donnellan MB, Oswald FL, Baird BM, Lucas RE. The Mini-IPIP Scales: Tiny-yet-effective measures of the Big Five Factors of Personality. Psychol Assess. 2006;18(2):192–203. doi: 10.1037/1040-3590.18.2.192 16768595

42. Johnson DR, Ecklund EH, Lincoln AE. Narratives of Science Outreach in Elite Contexts of Academic Science. Sci Commun. 2014 Feb 1;36(1):81–105.

43. Women’s Business Council. STEM Ambassadors? [Internet]. 2017. Available from: https://www.womensbusinesscouncil.co.uk/stem-ambassadors/

44. Fogg-Rogers L. Does being human influence science and technology? J Sci Commun. 2017;16(4).

45. Fogg-Rogers L, Sardo M, Boushel C. Robots vs Animals: establishing a culture of public engagement and female role modelling in a multi-disciplinary engineering laboratory. Sci Commun. 2017;39(2).

46. Archer L, DeWitt J, Osborne J, Dillon J, Willis B, Wong B. ‘Not girly, not sexy, not glamorous’: primary school girls’ and parents’ constructions of science aspirations 1. Pedagog Cult Soc [Internet]. 2013;21:171–94. Available from: http://www.tandfonline.com/doi/abs/10.1080/14681366.2012.748676

47. Kosti MV, Feldt R, Angelis L. Archetypal personalities of software engineers and their work preferences: a new perspective for empirical studies. Empir Softw Eng [Internet]. 2016;21(4):1509–32. Available from: https://doi.org/10.1007/s10664-015-9395-3

48. Feldt R, Angelis L, Torkar R, Samuelsson M. Links between the personalities, views and attitudes of software engineers. Inf Softw Technol. 2010;52(6):611–24.


Článek vyšel v časopise

PLOS One


2019 Číslo 10