Document Type : Research Paper


1 Department of Mathematics, Aras Branch, Islamic Azad University, Jolfa, Iran.

2 Department of Mathematics, Yadegar-e-Imam Khomeini (RAH) Shahre Rey Branch, Islamic Azad University, Tehran, Iran.


Emotional Intelligence (EQ) is considered as an alternative issue in both fields of psychology and education. Studies that have been conducted in this area illustrate the role of EQ and its components in different aspects of one's life such as academic achievement, occupation, and social relationships. Turning to a view to academic performance measurement, mathematics is considered as a science which can promote the learners' ability in order to respond to the ups and downs of every individual’s life. Most of the previous papers have investigated the relationship between EQ and mathematical Performance. The main feature of those studies were focusing on statistical analysis. To deal with this issue, this study proposes an alternative procedure not only is interested in employing non parametric models, such as Data Envelopment Analysis (DEA), but also provides the statistical analysis to assess the questioned relation. The proposed procedure can serve as an evaluation tool for educational policy and students ‘promotion.  To do so, eighty-one individuals have been selected among Islamic Azad University (Yadegar-e-Imam Khomeini (RAH) branch) engineering students with simple random during the first midterm of academic year 2019-2020. Distributing a standard EQ questionnaire of Bradberry and Greaves [18] reveals EQ and its four components’ scores. The average of three completed math scores have presented mathematical performance quantity. The results of DEA point out no specific pattern between EQ and mathematical performance. The study also reveals that statistical analysis show a similar trend as efficiency analysis method did.


Main Subjects

  1. Gardner, H. E. (2011). Frames of mind: the theory of multiple intelligences. New York: Basic Books.
  2. Austin, E. J., Saklofske, D. H., & Egan, V. (2005). Personality, well-being and health correlates of trait emotional intelligence. Personality and individual differences38(3), 547-558.
  3. Karkiyanoush, Z. (2007). Investigating the relationship between the components of emotional intelligence and academic performance. Thought and behavior in clinical psychology, 2(5), 89-98. (In Persian).
  4. Reyna, V. F., & Brainerd, C. J. (2007). The importance of mathematics in health and human judgment: Numeracy, risk communication, and medical decision making. Learning and individual differences17(2), 147-159.
  5. Hakkarainen, A., Holopainen, L., & Savolainen, H. (2013). Mathematical and reading difficulties as predictors of school achievement and transition to secondary education. Scandinavian journal of educational research57(5), 488-506.
  6. Hembree, R. (1990). The nature, effects, and relief of mathematics anxiety. Journal for research in mathematics education21(1), 33-46.
  7. Haddadi Koohsar, A. A., Roshan Chesli, R., & Asgharnezhad Farid, A. (2007). Comparative study of relationship between emotional intelligence and mental health and academic achievement in Shahed and non-Shahed students of Tehran University. Journal of psychology and education, 37(1), 73-97. (In Persian).
  8. Lalifaz, A., & Asgari, A. A. (2008). Predicting gifted students’ academic achievement based on their emotional intelligence and demographic variables. Psychology and education studies, 9(1), 167-181. (In Persian).
  9. Brackett, M. A., & Katulak, N. A. (2007). Emotional intelligence in the classroom: skill-based training for teachers and students. In J. Ciarrochi & J. D. Mayer (Eds.), Applying emotional intelligence: a practitioner's guide(pp. 1–27). Psychology Press.
  10. Petrides, K. V., Frederickson, N., & Furnham, A. (2004). The role of trait emotional intelligence in academic performance and deviant behavior at school. Personality and individual differences36(2), 277-293.
  11. Mahasneh, A. M. (2014). Investigating the relationship between emotional intelligence and meta-cognition among Hashemite University students. Review of European studies6(4), 201.
  12. Alavinia, P., & Mollahossein, H. (2012). On the correlation between Iranian EFL learners' use of metacognitive listening strategies and their emotional intelligence. International education studies5(6), 189-203.
  13. Rahnama, A., & Abdolmaleki, J. (2009). Investigating the relationship between emotional intelligence and creativity with academic achievement of Shahed University students. Journal of new thoughts on education, 5(2), 55-78. (In Persian).
  14. Saud, W. I. (2019). Emotional intelligence and its relationship to academic performance among Saudi EFL undergraduates. International journal of higher education8(6), 222-230.
  15. Malik, S. Z., & Shahid, S. (2016). Effect of emotional intelligence on academic performance among business students in Pakistan. Bulletin of education and research38(1), 197-208.
  16. Pourbahram, R., & Hajizadeh, M. (2018). The relationship between EFL instructors' emotional intelligence and learners' academic achievement. Language teaching and educational research1(1), 42-51.
  17. Dev, S., Nair, S., & Dwivedi, A. (2016). Emotional intelligence of instructors and the quality of their instructional performance. International education studies9(5), 40-47.
  18. Bradberry, T., & Greaves, J. (2005). Emotional intelligence tests and skills. Savalan Publications.
  19. Jafari Roshan, M., & Etemad, M. (2010). The relationship between document style and source of control with students' academic achievement. Journal of psychological research, 2(6), 1-12. (In Persian).
  20. Tamannaifar, M. R., Sedighi Arfai, F., & Salami Mohammadabadi, F. (2010). Correlation between emotional intelligence, self-concept and self-esteem with academic achievement. Scientific journal of education strategies in medical science, 3(3), 121-126. (In Persian).
  21. Goleman, D. (1995). Emotional intelligence. New York: Bantam Books.
  22. Samari, A., & Tahmasbi, F. (2007). An investigation on the relationship between emotional intelligence and academic achievement of students. Journal of fundamentals of mental health, 35/36, 121-128. (In Persian).
  23. Dehshiri, G. H. (2006). An investigation on the relationship between Emotional Intelligence and students' academic achievement. Journal of counseling research, 5(18), 97-106. (In Persian).
  24. Mayer, J. D., Caruso, D. R., & Salovey, P. (2000). Selecting a measure of emotional intelligence: the case for ability scales. In R. Bar-On & J. D. A. Parker (Eds.), The handbook of emotional intelligence: theory, development, assessment, and application at home, school, and in the workplace(pp. 320–342). Jossey-Bass.
  25. Charnes, A., & Cooper, W. W. (1962). Programming with linear fractional functionals. Naval research logistics quarterly9(3‐4), 181-186.
  26. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research2(6), 429-444.
  27. Cooper, W. W., Seiford, L. M., & Tone, K. (2006). Introduction to data envelopment analysis and its uses: with DEA-solver software and references. Springer Science & Business Media.
  28. Emrouznejad, A., Parker, B. R., & Tavares, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-economic planning sciences42(3), 151-157.
  29. Kayedpour, F., Sayadmanesh, Sh., Salmani, Y., & Sadeghi, Z. (2021). Measuring the efficiency and productivity of cement companies in Tehran Stock Exchange by data envelopment analysis and Malmquist productivity index in gray environment. Innovation management and operational strategies, 1(4), 363-382. (In Persian). DOI: 22105/IMOS.2021.276467.1038
  30. Shafiee, M., Saleh, H., & Ziyari, R. (2022). Projects efficiency evaluation by means data envelopment analysis and balanced scorecard. Journal of decision and operations research, 6, 1-18. (In Persian). DOI: 22105/DMOR.2020.229828.1150
  31. Ghasemi, Sh., Aghsami, A., & Rabbani, M. (2021). Data envelopment analysis for estimate efficiency and ranking operating rooms: a case study. International journal of research in industrial engineering, 10(1), 67-86. (In Persian). DOI: 22105/RIEJ.2021.247705.1143
  32. Edalatpanah, S. A., Godarzi Karim, R., Khalilian, B., & Partouvi, S. (2020). Data envelopment analysis and efficiency of firms: a goal programing approach. Innovation management and operational strategies1(1), 1-16. (In Persian). DOI: 22105/IMOS.2021.266007.1024
  33. Amirteimoori, A., & Emrouznejad, A. (2011). Flexible measures in production process: a DEA-based approach. RAIRO-operations research45(1), 63-74.
  34. Tohidi, G., & Matroud, F. (2017). A new non-oriented model for classifying flexible measures in DEA. Journal of the operational research society68(9), 1019-1029.