Academic Emotions in Programming Learning: Women’s Impact on the Software Sector

  • Beatriz Eugenia GrassEmail author
  • Mayela CotoEmail author
  • César CollazosEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 847)


This document presents an analysis based on a systematic review carried out on the most recognized topics related to academic emotions in the different mechanisms of research and emotional evaluation, trying to focus attention on the initial programming courses, based on the basic programming concepts, independently of the tool in which these concepts are applied, taking into account that the programming courses are considered relevant courses for the training of computer engineers; mechanisms for the evaluation of emotions are also identified. The main emotions in academic contexts are identified and the aim is to identify elements and analysis through the gender variable. Analyses are done focusing on academic emotions. Subsequently, the factors by which women are not linked to the area of software engineering are analyzed, from the perspective of the high drop-out rates due to the programming courses and the impact of the low participation of women in the software sector in the world order, taking into account the roles in which women perform satisfactorily in the software industry.


Emotions Affective states Learning of programming Teaching process of programming Academic emotions 


  1. 1.
    Astrolabio, E.: Emociones académicas: El Eslabón Perdido del Plan de Estudios, 94–107 (2015)Google Scholar
  2. 2.
    Fisher, A., Margolis, J., Miller, F.: Undergraduate women in computer science: experience motivation and culture. ACM SIGCSE Bull. 29(1), 29 (1997)CrossRefGoogle Scholar
  3. 3.
    Bosch, N., D’Mello, S., Mills, C.: What emotions do novices experience during their first computer programming learning session? In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS (LNAI), vol. 7926, pp. 11–20. Springer, Heidelberg (2013). Scholar
  4. 4.
    Burton, L.J.: Higher education in a changing world (2005) Google Scholar
  5. 5.
    Won, J., Kang, M.: Computers & Education. The role of academic emotions in the relationship between perceived academic control and self-regulated learning in online learning. Comput. Educ. 77, 125–133 (2014)CrossRefGoogle Scholar
  6. 6.
    Lehman, K.J., Sax, L.J., Zimmerman, H.B.: Women planning to major in computer science: who are they and what makes them unique? Comput. Sci. Educ. 26, 277–298 (2017)CrossRefGoogle Scholar
  7. 7.
    Pekrun, R., Goetz, T., Titz, W., Perry, R.P.: Academic emotions in students’ self-regulated learning and achievement: a program of qualitative and quantitative research. Educ. Psychol. 37, 91–105 (2002)CrossRefGoogle Scholar
  8. 8.
    Wilson, B.C.: Gender differences in types of assignments preferred: implications for computer science instruction. J. Educ. Comput. Res. 34, 245–255 (2006)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Eccles, J.S., Wang, M.T.: What motivates females and males to pursue careers in mathematics and science? Int. J. Behav. Dev. 40, 100–106 (2016)CrossRefGoogle Scholar
  10. 10.
    Tiempo, P.: El Preocupante déficit de ingenieros en Colombia (2015).
  11. 11.
    Pérez-Bustos, T., Marquez Gutiérrez, S.: La industria del software y los servicios informáticos (SSI): un sector de oportunidad para el empoderamiento económico de las mujeres latinoamericanas. Capítulo Colombia – Informe de sistematización, 42 (2013)Google Scholar
  12. 12.
    Gabbert, P., et al.: ACM-W’s New Programs for Recruiting and Retaining Women in Computing. ACM SIGCSE Bull. 39(1), 247–248 (2007)CrossRefGoogle Scholar
  13. 13.
    Ramírez, B.E.G., Collazos, C.A., González, C.S.: Gender differences in computing programs: Colombian case study. ACM Int. Conf. Proceeding Ser. pp. 4–6 (2016).
  14. 14.
    Blum, L.: Transforming the Culture of Computing at Carnegie Mellon Why (and How) the Increase? 1–6 (2002)Google Scholar
  15. 15.
    Byrne, P., Lyons, G.: The effect of student attributes on success in programming. ACM SIGCSE Bull. 33(33), 49–52 (2001)CrossRefGoogle Scholar
  16. 16.
    Murphy, L., Westbrook, S., Richards, B., Morrison, B.B., Fossum, T.: Women Catch Up: gender differences in learning programming concepts. ACM SIGCSE Bull. 38(1), 17–21 (2006)CrossRefGoogle Scholar
  17. 17.
    Cohoon, J.M.: Recruiting and retaining women in undergraduate computing majors. ACM SIGCSE Bull. 34(2), 48–52 (2002)CrossRefGoogle Scholar
  18. 18.
    Collazos, C., Guerrero, L., Pino, J., Ochoa, S.: Evaluating collaborative learning processes. Groupw. Des. Implement. Use 2440, 173–194 (2002)zbMATHGoogle Scholar
  19. 19.
    González, C.S., Collazos, C.A., García, R.: Desafío en el diseño de MOOCs: incorporación de aspectos para la colaboración y la gamificación. RED. Rev. Educ. a Distancia (2016)Google Scholar
  20. 20.
    Mata, F.J. et al.: Gender Gap in Computer Science Programs from Costa Rican Public Universities Are Women Really Becoming Extinct? (2012)Google Scholar
  21. 21.
    Chetty, J., Westhuizen, D. Van der. “ I hate programming” and Other Oscillating Emotions Experienced by Novice Students Learning Computer Programming. In: EdMedia World Conference on Educational Media and Technology, pp. 1889–1894 (2013)Google Scholar
  22. 22.
    Vitores, A., Gil-Juárez, A.: The trouble with ‘women in computing’: a critical examination of the deployment of research on the gender gap in computer science. J. Gend. Stud. 1–15 (2015).
  23. 23.
    Linnenbrink-Garcia, L., Pekrun, R.: Students’ emotions and academic engagement: introduction to the special issue. Contemp. Educ. Psychol. 36, 1–3 (2011)CrossRefGoogle Scholar
  24. 24.
    Pekrun, R., Goetz, T., Frenzel, A.C., Barchfeld, P., Perry, R.P.: Measuring emotions in students’ learning and performance: the Achievement Emotions Questionnaire (AEQ). Contemp. Educ. Psychol. 36, 36–48 (2011)CrossRefGoogle Scholar
  25. 25.
    Robins, A., Rountree, J., Rountree, N.: Learning and teaching programming: a review and discussion. Comput. Sci. Educ. 13, 137–172 (2003)CrossRefGoogle Scholar
  26. 26.
    Martin, C., Hughes, J., Richards, J.: Learning experiences in programming: The Motivating Effect of a Physical Interface. 1, 162–172 (2017)Google Scholar
  27. 27.
    Linnenbrink, E.A.: Emotion research in education: theoretical and methodological perspectives on the integration of affect, motivation, and cognition. Educ. Psychol. Rev. 18, 307–314 (2006)CrossRefGoogle Scholar
  28. 28.
    Good, J., Rimmer, J., Harris, E., Balaam, M.: Self-reporting emotional experiences in computing lab sessions: an emotional regulation perspective. In: Proceedings of the 23rd Annual Psychology Programming Interest Group Conference (2011)Google Scholar
  29. 29.
    Davies, D., et al.: Creative learning environments in education-a systematic literature review. Think. Ski. Creat. 8, 80–91 (2013)CrossRefGoogle Scholar
  30. 30.
    Rosas, S.: The Achievement Emotions Questionnaire-Argentine (AEQ-AR): internal and external validity, reliability, gender differences and norm-referenced interpretation of test scores development and adaptation of instruments to measure test anxiety has been con. Revista Evaluar 15(1), 41–74 (2015)Google Scholar
  31. 31.
    Martin, C., Hughes, J., Richards, J.: Learning experiences in programming: The Motivating Effect of a Physical Interface 2002 (2017)Google Scholar
  32. 32.
    Connolly, T.M., Boyle, E.A., MacArthur, E., Hainey, T., Boyle, J.M.: A systematic literature review of empirical evidence on computer games and serious games. Comput. Educ. 59, 661–686 (2012)CrossRefGoogle Scholar
  33. 33.
    Talug, D.Y.: Lifelong learning through out today’s occasions namely social media and online games. Procedia - Soc. Behav. Sci. 46, 4431–4435 (2012)CrossRefGoogle Scholar
  34. 34.
    D’Mello, S., Graesser, A.: Dynamics of affective states during complex learning. Learn. Instr. 22, 145–157 (2012)CrossRefGoogle Scholar
  35. 35.
    Simões, J., Redondo, R.D., Vilas, A.F.: A social gamification framework for a K-6 learning platform. Comput. Human Behav. 29, 345–353 (2013)CrossRefGoogle Scholar
  36. 36.
    Pekrun, R.: The control-value theory of achievement emotions: assumptions, corollaries, and implications for educational research and practice. Educ. Psychol. Rev. 18, 315–341 (2006)CrossRefGoogle Scholar
  37. 37.
    Lachmann, H., Ponzer, S., Johansson, U.-B., Benson, L., Karlgren, K.: Capturing students’ learning experiences and academic emotions at an interprofessional training ward. J. Interprof. Care 27, 137–145 (2013)CrossRefGoogle Scholar
  38. 38.
    Daniels, L.M., et al.: Individual differences in achievement goals: a longitudinal study of cognitive, emotional, and achievement outcomes. Contemp. Educ. Psychol. 33, 584–608 (2008)CrossRefGoogle Scholar
  39. 39.
    Pekrun, R., Goetz, T., Daniels, L.M., Stupnisky, R.H., Perry, R.P.: Boredom in achievement settings: exploring control-value antecedents and performance outcomes of a neglected emotion. J. Educ. Psychol. 102, 531–549 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.San Buenaventura UniversityCaliColombia
  2. 2.Universidad Nacional de Costa RicaSan JoseCosta Rica
  3. 3.Cauca UniversityPopayánColombia

Personalised recommendations