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Informatics Education in School: A Multi-Year Large-Scale Study on Female Participation and Teachers’ Beliefs

  • Enrico NardelliEmail author
  • Isabella Corradini
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11913)

Abstract

This paper describes the outcomes of a multi-year large-scale study on Informatics education in school, involving an average of 3,600 teachers per school year of all school levels. The study has been conducted in Italy, where - generally speaking - there is no compulsory informatics education in school. Teachers have voluntarily enrolled in the “Programma il Futuro” project, running since 2014, and have taught short introductory courses in Informatics. Answering - anonymously - to monitoring questionnaires, they have indicated whether girls or boys were more interested in Informatics activities and whether girls or boys were more effective.

Answers show that the difference between the number of teachers thinking boys are more interested (or more effective) and the number of those judging girls more interested (or more effective) has constantly decreased over school years during the project. This variation in teachers’ beliefs over school years - that we attribute to their involvement in project activities - is important, since teachers’ beliefs are known to influence students’ motivations, hence their future choices. Our opinion is reinforced by the results of a differential analysis, in each school year, between teachers repeating activities and those executing them for the first time.

Moreover, the analysis of disaggregated data shows that the difference between boys and girls relative to interest or effectiveness increases going up in school level. Our results provide an empirical support to the belief that it is important to start Informatics education early in school, before gender stereotypes consolidate.

Keywords

Informatics education in school Broadening participation Gender and diversity 

Notes

Acknowledgements

We greatly thank teachers and students involved in “Programma il Futuro” (coordinated by EN) and Code.org for their cooperation.

We acknowledge the financial support for school year 2018–19 of: Eni; Engineering; SeeWeb; TIM. Other companies have financially supported PiF in previous school years, see https://programmailfuturo.it/partner.

Rai Cultura, the culture department of Italian national public broadcasting company, is a media partner of the project since February 2017.

References

  1. 1.
    Académie des Sciences: L’enseignement de l’informatique en France: Il est urgent de ne plus attendre, May 2013. http://www.academie-sciences.fr/pdf/rapport/rads_0513.pdf
  2. 2.
    Accenture: Cracking the gender code (2016). https://www.accenture.com/us-en/cracking-the-gender-code
  3. 3.
    Armoni, M., Gal-Ezer, J.: Early computing education: Why? What? When? Who? ACM Inroads 5(4), 54–59 (2014)CrossRefGoogle Scholar
  4. 4.
    Augoustinos, M., Walker, I.: The construction of stereotypes within social psychology: from social cognition to ideology. Theory Psychol. 8(5), 629–652 (1998)CrossRefGoogle Scholar
  5. 5.
    Borg, M.: Key concepts in ELT: teachers’ beliefs. ELT J. 55(2), 186–188 (2001)CrossRefGoogle Scholar
  6. 6.
    Caspersen, M.E., Gal-Ezer, J., McGettrick, A., Nardelli, E.: Informatics as a fundamental discipline for the 21st century. Commun. ACM 62(4), 58 (2019)CrossRefGoogle Scholar
  7. 7.
    Cheryan, S., Plaut, V.C., Handron, C., Hudson, L.: The stereotypical computer scientist: gendered media representations as a barrier to inclusion for women. Sex Roles 69, 58–71 (2013)CrossRefGoogle Scholar
  8. 8.
    Code.org: Computing occupations are now the #1 source of new wages in America (2016). https://blog.code.org/post/144206906013/computing-occupations-are-now-the-1-source-of-new
  9. 9.
    Code.org: Diversity in computer science (2018). https://code.org/diversity
  10. 10.
    Cohoon, J.M., Aspray, W.: Women and Information Technology: Research on Underrepresentation, vol. 1. The MIT Press, Cambridge (2006)Google Scholar
  11. 11.
    Computer Science Zone: The technology job gap (2015). https://www.computersciencezone.org/technology-job-gap/
  12. 12.
    Corradini, I., Lodi, M., Nardelli, E.: Computational thinking in Italian schools: quantitative data and teachers’ sentiment analysis after two years of “Programma il Futuro” Project. In: ITiCSE 2017. ACM (2017)Google Scholar
  13. 13.
    Corradini, I., Lodi, M., Nardelli, E.: Conceptions and misconceptions about computational thinking among Italian primary school teachers. In: ICER 2017 (2017)Google Scholar
  14. 14.
    Corradini, I., Lodi, M., Nardelli, E.: An investigation of Italian primary school teachers’ view on coding and programming. In: Pozdniakov, S.N., Dagienė, V. (eds.) ISSEP 2018. LNCS, vol. 11169, pp. 228–243. Springer, Cham (2018).  https://doi.org/10.1007/978-3-030-02750-6_18CrossRefGoogle Scholar
  15. 15.
    Duncan, C., Bell, T., Tanimoto, S.: Should your 8-year-old learn coding? In: Proceedings WiPSCE 2014, pp. 60–69. ACM (2014)Google Scholar
  16. 16.
    European Commission: The digital skills and job coalition (2014). https://ec.europa.eu/digital-single-market/en/digital-skills-jobs-coalition
  17. 17.
    Fisher, A., Margolis, J.: Unlocking the clubhouse: the Carnegie Mellon experience. SIGCSE Bull. 34(2), 79–83 (2002)CrossRefGoogle Scholar
  18. 18.
    Funke, A., Geldreich, K., Hubwieser, P.: Primary school teachers’ opinions about early computer science education. In: 16th Koli Calling International Conference on Computing Education Research, pp. 135–139 (2016)Google Scholar
  19. 19.
    Gunderson, E.A., Ramirez, G., Levine, S.C., Beilock, S.L.: The role of parents and teachers in the development of gender related math attitudes. Sex Roles 66, 153–166 (2011)CrossRefGoogle Scholar
  20. 20.
    Hardre, P.L., Sullivan, D.W.: Motivating adolescents: teachers’ beliefs, perceptions and classroom practices. Teach. Dev. 13, 1–16 (2009)CrossRefGoogle Scholar
  21. 21.
    Hill, C., Corbett, C., St. Rose, A. (eds.): Women and Information Technology: Research on Underrepresentation. AAUW (2010)Google Scholar
  22. 22.
    Hornstra, L., Mansfield, C., Van der Veen, I., Peetsma, T., Volman, M.: Motivational teacher strategies: the role of beliefs and contextual factors. Learn. Environ. Res. 18, 363–392 (2015)CrossRefGoogle Scholar
  23. 23.
    Klawe, M.: Increasing female participation in computing: the Harvey Mudd college story. Computer 46(3), 56–58 (2013)CrossRefGoogle Scholar
  24. 24.
    Lensvelt-Mulders, G.: Surveying sensitive topics. In: de Leeuw, E., Hox, J., Dillman, D. (eds.) International Handbook of Survey Methodology, pp. 461–478. Lawrence Erlbaum Associates, New York (2008)Google Scholar
  25. 25.
    Malcom-Piqueux, L.E., Malcom, S.M.: Engineering diversity: Fixing the educational system to promote equity. Bridge 43, 24–34 (2013)Google Scholar
  26. 26.
    Margolis, J., Fisher, A.: Unlocking the Clubhouse: Women in Computing. MIT Press, Cambridge (2002)Google Scholar
  27. 27.
    Master, A., Cheryan, S., Meltzoff, A.N.: Reducing adolescent girls’ concerns about stem stereotypes: when do female teachers matter? Revue internationale de psychologie sociale 27(3–4), 79–102 (2014)Google Scholar
  28. 28.
    Medium: University computer science finally surpasses its 2003 peak! (2017). https://medium.com/anybody-can-learn/university-computer-science-finally-surpasses-its-2003-peak-ecefa4c8d77d
  29. 29.
    Miyake, A., Kost-Smith, L.E., Finkelstein, N.D., Pollock, S.J., Cohen, G.L., Ito, T.A.: Reducing the gender achievement gap in college science: a classroom study of values affirmation. Science 330, 1234–1237 (2010)CrossRefGoogle Scholar
  30. 30.
    Ong, A., Weiss, D.: The impact of anonymity on responses to sensitive questions. J. Appl. Soc. Psychol. 30(8), 1691–1708 (2000)CrossRefGoogle Scholar
  31. 31.
    Pintrich, P.: A motivational science perspective on the role of student motivation in learning and teaching context. J. Educ. Psychol. 95(4), 667–686 (2003)CrossRefGoogle Scholar
  32. 32.
    Ryan, R.M., Deci, E.L.: Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp. Educ. Psychol. 25(1), 54–67 (2000)CrossRefGoogle Scholar
  33. 33.
    Sadik, O.: Encouraging women to become CS teachers. In: GenderIT, pp. 57–61 (2015)Google Scholar
  34. 34.
    Shapiro, J.R., Williams, A.M.: The role of stereotype threats in undermining girls’ and women’s performance and interest in STEM fields. Sex Roles 66, 175–183 (2011)CrossRefGoogle Scholar
  35. 35.
    Sysło, M.M., Kwiatkowska, A.B.: Introducing a new computer science curriculum for all school levels in Poland. In: Brodnik, A., Vahrenhold, J. (eds.) ISSEP 2015. LNCS, vol. 9378, pp. 141–154. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-25396-1_13CrossRefGoogle Scholar
  36. 36.
    Tajfel, G.: Human Groups and Social Categories. Studies in Social Psychology. Cambridge University Press, Cambridge (1981)Google Scholar
  37. 37.
    The Royal Society: Shut down or restart? The way forward for computing in UK schools, January 2012. https://royalsociety.org/~/media/education/computing-in-schools/2012-01-12-computing-in-schools.pdf
  38. 38.
    U.S. Equal Employment Opportunity Commission: Diversity in high tech (2016). https://www.eeoc.gov/eeoc/statistics/reports/hightech/
  39. 39.
  40. 40.
    Varma, R.: Why so few women enroll in computing? Gender and ethnic differences in students’ perception. Comput. Sci. Educ. 20(4), 301–316 (2010)CrossRefGoogle Scholar
  41. 41.
    Vuorikari, R., Punie, Y., Gomez, S.C., Van den Brande, G.: DigComp 2.0: The Digital Competence Framework for Citizens. Luxembourg Publication Office of the European Union. EUR 27948 EN (2016)Google Scholar
  42. 42.
    Webb, M., et al.: Computer science in k-12 school curricula of the 2lst century: why, what and when? Educ. Inf. Technol. 22(2), 445–468 (2017)CrossRefGoogle Scholar
  43. 43.
    Weisgram, E.S., Bigler, R.S.: The role of attitudes and intervention in high school girls’ interest in computer science. J. Women Minor. Sci. Eng. 12, 325–336 (2006) CrossRefGoogle Scholar
  44. 44.
    Zagami, J., Boden, M., Keane, T., Moreton, B., Schulz, K.: Girls and computing: female participation in computing in schools. Aust. Educ. Comput. 30(2) (2015). https://journal.acce.edu.au/index.php/AEC/article/view/79

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Università di Roma “Tor Vergata”RomeItaly
  2. 2.Themis Research CentreRomeItaly

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