Quantitative Techniques is traditionally a subject with a poor pass rate at Walter Sisulu University. In search of a turnaround strategy, the purpose of this study was to determine the level of problem-solving proficiency of Quantitative Techniques students, which is suspected to influence achievement in this subject. A descriptive survey design was used in this research. Second-year ND (Marketing) students (128) took part in the study. A questionnaire and a written test were used to collect data. A profile of participants’ problem-solving was determined. Their weaknesses and strengths in problem-solving were investigated. The problem-solving proficiency of participants with regards to the biographical variables of Gender, Age, Mathematics background and whether they took Data Handling training at school or not were explored. A model, based on Polya’s four stages of problem-solving, was used to measure the students’ level of problem-solving proficiency, which was 59,16%. Findings suggest that the students achieved highest in understanding a problem (72,29%) and making a plan to solve the problem (73,77%). They are weakest at interpreting their results (29,38%). MANOVA results showed no statistical significance for the biographical variables. The univariate results suggest that age, Data Handling training at school and Gender could affect problem-solving proficiency. Since the findings of this study indicate a strong relationship between participants’ problem-solving proficiency and their actual achievement, some intervention is recommended. An intervention could be in the form of a section on problem-solving in the course, supplemental instruction or an introductory course. Course and curriculum content should be revised to address students’ proficiency in problem-solving. / Mathematical Sciences / M. A. (Statistics Education)

Quantitative Techniques is traditionally a subject with a poor pass rate at Walter Sisulu University. In search of a turnaround strategy, the purpose of this study was to determine the level of problem-solving proficiency of Quantitative Techniques students, which is suspected to influence achievement in this subject. A descriptive survey design was used in this research. Second-year ND (Marketing) students (128) took part in the study. A questionnaire and a written test were used to collect data. A profile of participants’ problem-solving was determined. Their weaknesses and strengths in problem-solving were investigated. The problem-solving proficiency of participants with regards to the biographical variables of Gender, Age, Mathematics background and whether they took Data Handling training at school or not were explored. A model, based on Polya’s four stages of problem-solving, was used to measure the students’ level of problem-solving proficiency, which was 59,16%. Findings suggest that the students achieved highest in understanding a problem (72,29%) and making a plan to solve the problem (73,77%). They are weakest at interpreting their results (29,38%). MANOVA results showed no statistical significance for the biographical variables. The univariate results suggest that age, Data Handling training at school and Gender could affect problem-solving proficiency. Since the findings of this study indicate a strong relationship between participants’ problem-solving proficiency and their actual achievement, some intervention is recommended. An intervention could be in the form of a section on problem-solving in the course, supplemental instruction or an introductory course. Course and curriculum content should be revised to address students’ proficiency in problem-solving. / Mathematical Sciences / M. A. (Statistics Education)