Retention Learning of Students in Machine Language: What can Culturo-Techno-Contextual Approach (CTCA) do?

Abstract

This study aimed to determine the difference between (a) the retention of information by students taught machine learning using the culturo-techno-contextual approach (CTCA) and the lecture method; (b) the retention of information by male and female students taught machine learning using CTCA; and (c) the interaction effects of gender and the teaching methods on the retention of information by students taught machine learning using CTCA and lecture. Adopted learning ideas include Vygotsky's theory of constructivism, Ausubel's philosophy of meaningful learning, and the philosophical framework of the CTCA. This study employed sequential explanatory mixed methodologies and a quasi-experimental research methodology. A total of 138 learners in senior secondary II participated in the study. The reliability of the Machine Language Achievement Test (MLAT) was determined using the split-half method, which yielded a Spearman-Brown coefficient of 0.80. There is a statistically significant difference in method of teaching [F (1, 137) = 111.61; p<0.05], which was in favour of the CTCA group (experimental). There is no statistically significant difference in the gender of the students in the experimental group [F (1, 137) = 0.08; p > 0.05]. The interaction effect of methods and gender is not statistically significant [F (1, 137) = 1.61; p = 0.21]. We therefore encouraged and suggested that secondary school computer studies teachers should utilise CTCA in order to improve student learning.