Suchergebnisse

The main aim of the study was (1) to identify the underlying factors related to errors due to incorrect association, and (2) to understand why learners continue to make such errors so that mechanisms to avoid such errors could be devised.The study was conducted by means of a case study guided by the positivists'paradigm where the research sample comprised of 105 Grade 10 Mathematics Literacy learners as respondents. Having used Polya's problem-solving techniques, Threshold Concept and Newman's Error Analysis as the theoretical frameworks for the study, a four-point Likert scale and a content-based structure-interview questionnaire were developed to address the research question. Four sets of structured-interview questionnaires were used for collecting data, aimed at addressing the main objective of the study. In order to test the reliability and consistency of the questionnaires for this study, Cronbach's Alpha was tested for standardised items (α = 0.705).Once the data was collected, it was analysed through content and correlation analysis. Based on the frequency table which summarises learner responses, it could be ascertained that the majority (n =63, 60%) of learners admitted to sometimes confusing addition with multiplication. The relationship between learners forgetting to write units and learners writing down an incorrect number/figure revealed a significance where p = .04 (r = +.17) illustrated a weak correlation between the afore-stated variables.

Abstract
Building on prior research related to (1) impact of information communication technology (ICT) and (2) operational risk management (ORM) in the context of medium and small enterprises (MSEs), the focus of this study was to investigate the relationship between (1) ICT operational risk management (ORM) and (2) performances of MSEs. To achieve the focus, the research investigated evaluating models for understanding the value of ICT ORM in MSEs. Multiple regression, Repeated-Measures Analysis of Variance (RM-ANOVA) and Repeated-Measures Multivariate Analysis of Variance (RM-MANOVA) were performed. The findings of the distribution revealed that only one variable made a significant percentage contribution to the level of ICT operation in MSEs, the Payback method (β = 0.410, p < .000). It may thus be inferred that the Payback method is the prominent variable, explaining the variation in level of evaluation models affecting ICT adoption within MSEs. Conclusively, in answering the two questions (1) degree of variability explained and (2) predictors, the results revealed that the variable contributed approximately 88.4% of the variations in evaluation models affecting ICT adoption within MSEs. The analysis of variance also revealed that the regression coefficients were real and did not occur by chance