Predicting student's STEM subject performance by using the Malay version of S-STEM

Abstract

The study employed the Malay version of Student Attitude towards STEM (S-STEM) to predict STEM subject performance. The original S-STEM was translated from English to the Malay language and tested on a sample of 144 first year undergraduates. The instrument consisted of four constructs on attitudes: mathematics, science, engineering/technology, and 21st century skills. Confirmatory factor analysis confirmed the four factors contributed 53.2% to the explained variance. Structural Equation Modelling was employed to test the measurement and structural model. Item loadings below 0.6 were removed from the instrument. Results show that all constructs fulfilled most of the reliability criteria. Fit indices presented CFI = 0.925 and RMSEA= 0.069 which abide the rule of thumb with GFI = 0.836, AGFI = 0.789, NFI = 0.837 readings near the level of acceptance. When the Malay version of S-STEM was administered on 111 students in the following year, result shows that mathematics attitudes was the best factor to predict STEM subject performance followed by science attitudes, and then the 21st century skill. Impact of engineering/technology was not statistically significant at p