Resumen

MTHIMUNYE, Katlego D.T.  y  DANIELS, Felicity M.. Performance in grade 12 mathematics and science predicts student nurses' performance in first year science modules at a university in the Western Cape. Curationis [online]. 2017, vol.40, n.1, pp.1-6. ISSN 2223-6279.  http://dx.doi.org/10.4102/curationis.v40i1.1776.

BACKGROUND: The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence. AIM: The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. METHOD: A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman's rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. RESULTS: The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R² = 0.381 and adj R² = 0.371) of the variation in the first year science grade distributions. CONCLUSION: Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

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