Academic resilience, emotional intelligence, and academic performance among undergraduate students

  • Received January 20, 2022;
    Accepted March 8, 2022;
    Published March 10, 2022
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/kpm.06(1).2022.01
  • Article Info
    Volume 6 2022, Issue #1, pp. 1-10
  • TO CITE АНОТАЦІЯ
  • Cited by
    17 articles
  • 3032 Views
  • 919 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Academic resilience and emotional intelligence are considered important personal resources for furthering students’ academic performance. However, many educational organizations seem to trivialize the performance implications of these constructs in teachings and curriculum. Consequently, it can decrease not just their academic performance but also their employability, as they lack the generic competencies to adapt and survive in a stressful context. Even so, empirical evidence on integrating academic resilience, emotional intelligence, and academic performance remains unexplored in the Nigerian university context. Therefore, the study aimed to investigate the linkages between academic resilience, emotional intelligence, and academic performance in Nigeria. The partial least square (PLS) modeling method was utilized for testing the stated hypotheses with data collected from 179 final year undergraduate students in the regular B.Sc. Business Administration and B.Sc. Marketing program at Delta State University, Nigeria. From the PLS results, the study reported that academic resilience was positively related to emotional intelligence (β = 0.125, p = 0.007), academic resilience (β = 0.231, p = 0.000) and emotional intelligence (β = 0.260, p = 0.000) were positively related to academic performance, and emotional resilience mediated the positive relationship between academic resilience and academic performance (β = 0.057, p = 0.005). While academic resilience predicted academic performance, it also predicted emotional intelligence, which affected academic performance significantly and positively.

view full abstract hide full abstract
    • Table 1. Measurement model results
    • Table 2. Structural model results
    • Conceptualization
      Uzoma Ononye, Mercy Ogbeta, Francis Ndudi, Dudutari Bereprebofa, Ikechuckwu Maduemezia
    • Data curation
      Uzoma Ononye
    • Formal Analysis
      Uzoma Ononye, Francis Ndudi
    • Funding acquisition
      Uzoma Ononye, Mercy Ogbeta, Francis Ndudi, Dudutari Bereprebofa, Ikechuckwu Maduemezia
    • Investigation
      Uzoma Ononye, Mercy Ogbeta
    • Methodology
      Uzoma Ononye, Mercy Ogbeta, Dudutari Bereprebofa
    • Software
      Uzoma Ononye
    • Supervision
      Uzoma Ononye, Mercy Ogbeta
    • Writing – original draft
      Uzoma Ononye, Mercy Ogbeta, Francis Ndudi, Dudutari Bereprebofa, Ikechuckwu Maduemezia
    • Writing – review & editing
      Uzoma Ononye, Mercy Ogbeta, Francis Ndudi, Dudutari Bereprebofa, Ikechuckwu Maduemezia