The aim of this study was to determine the influence of personality variables on academic achievement. Apart from the personality variables, many other variables influence the academic achievement of secondary school pupils. A literature study was undertaken to examine the nature and extent of the influence of personality variables and these other variables which include the family environment, school variables and pupil characteristics, on academic achievement. The family environment includes such variables as the socio-economic status of the family, family size, birth order and family relationships. It was found that these variables have a significant influence on academic achievement. School variables were divided into macro-level variables which include school size and -location, and micro-level variables which encompass those variables concerned with the actual classroom situation. From the literature study could be deduced that the micro-level variables, such as class size, furniture arrangement, seating position, body image boundaries and teacher characteristics have a greater influence on academic achievement than the macro-level variables. Pupil characteristics were found to have a significant influence on academic achievement. Cognitive variables such as intelligence and prior knowledge affect academic achievement the most. Although the effect of the non-cognitive variables which include cognitive style, pupil affect, locus of control, motivation, role expectations and study orientation, is not as great as that of the cognitive variables, non-cognitive variables nevertheless add significantly to the explanation of the variance in academic achievement. As the influence of the family environment, school variables and pupil characteristics seemed to be significant, these variables were included in the empirical investigation as control variables. The personality variables which were discussed in the literature study are introversion-extraversion, neuroticism and some personality factors of the High School Personality Questionnaire. Finally, the relationship between various personality variables and academic achievement in general and in specific school subjects, was discussed. From the literature study could be deduced that, although personality variables per se do not explain such a large percentage of the variance in academic achievement, they nevertheless increase the percentage of variance in academic achievement explained by the other variables significantly. Personality variables were included in the empirical study as experimental variables. All the standard ten pupils who followed the regular standard ten courses (excluding the practical course) and were taught by medium of Afrikaans in the OFS in 1980, were included as the population for this investigation. The dependent variables of the study were the average mark in standard ten and achievement in Afrikaans and Mathematics. A large number of variables with regard to each pupil was measured. By means of a factor analysis these variables were reduced to 15 control variables to which factor B (less intelligent-more intelligent) of the HSPQ was added. The remaining 13 personality variables of the HSPQ served as the experimental variables. The multiple regression analysis technique was used to determine the influence of: 1. the control variables; 2. the control plus the experimental variables; 3. the experimental (personality) variables and 4. the personality variables of boys and girls separately on each of the three dependent variables. The most important results of the empirical investigation can be stated as follows: The control variables influence academic achievement. The cognitive variable is the single control variable with the greatest influence on all three the dependent variables. Sex of the pupil and school variables influence achievement in Afrikaans meaningfully, whilst faculty of comprehension has a meaningful influence on achievement in Mathematics. A multivariate model which includes personality variables is more effective than a multivariate model excluding personality variables. Personality variables in a multivariate model are, however, more effective as predictors of achievement in Afrikaans than in Mathematics or in average mark in standard ten. Personality as a construct, thus in a multivariate model which includes only personality variables, also influences achievement in Afrikaans more than it influences achievement in Mathematics or average mark in standard ten. Learning tasks in Afrikaans are more perceptual whilst those in Mathematics are more conceptual. It was therefore deduced that personality variables have a greater influence on perceptual tasks than on conceptual tasks. All personality variables influence achievement in Afrikaans whereas only factor I (self-confidence) has a meaningful influence on Mathematics achievement. No difference was found in the influence of personality variables of boys and those of girls on achievement in Afrikaans. Achievement in Mathematics of girls is however influenced more by personality variables than that of boys. Whereas factor 0 (calm) has an influence on Mathematics achievement of boys, factor I (emotionality) has an influence on the mathematics achievement of girls. The conclusion of the study, therefore, is that personality variables influence academic achievement differently, depending on the school subjects investigated, the prediction model used and the sex of the pupils. The inclusion of personality variables in a multivariate model makes the model more effective for the prediction of academic achievement. The results of tests undertaken with such a model ought to enable teachers to gain more insight into the capabilities and interests of pupils and thus to provide better vocational guidance as concerns courses to be taken at secondary school level. / Thesis (MEd)--PU vir CHO, 1985

The aim of this study was to determine the influence of personality variables on academic achievement. Apart from the personality variables, many other variables influence the academic achievement of secondary school pupils. A literature study was undertaken to examine the nature and extent of the influence of personality variables and these other variables which include the family environment, school variables and pupil characteristics, on academic achievement. The family environment includes such variables as the socio-economic status of the family, family size, birth order and family relationships. It was found that these variables have a significant influence on academic achievement. School variables were divided into macro-level variables which include school size and -location, and micro-level variables which encompass those variables concerned with the actual classroom situation. From the literature study could be deduced that the micro-level variables, such as class size, furniture arrangement, seating position, body image boundaries and teacher characteristics have a greater influence on academic achievement than the macro-level variables. Pupil characteristics were found to have a significant influence on academic achievement. Cognitive variables such as intelligence and prior knowledge affect academic achievement the most. Although the effect of the non-cognitive variables which include cognitive style, pupil affect, locus of control, motivation, role expectations and study orientation, is not as great as that of the cognitive variables, non-cognitive variables nevertheless add significantly to the explanation of the variance in academic achievement. As the influence of the family environment, school variables and pupil characteristics seemed to be significant, these variables were included in the empirical investigation as control variables. The personality variables which were discussed in the literature study are introversion-extraversion, neuroticism and some personality factors of the High School Personality Questionnaire. Finally, the relationship between various personality variables and academic achievement in general and in specific school subjects, was discussed. From the literature study could be deduced that, although personality variables per se do not explain such a large percentage of the variance in academic achievement, they nevertheless increase the percentage of variance in academic achievement explained by the other variables significantly. Personality variables were included in the empirical study as experimental variables. All the standard ten pupils who followed the regular standard ten courses (excluding the practical course) and were taught by medium of Afrikaans in the OFS in 1980, were included as the population for this investigation. The dependent variables of the study were the average mark in standard ten and achievement in Afrikaans and Mathematics. A large number of variables with regard to each pupil was measured. By means of a factor analysis these variables were reduced to 15 control variables to which factor B (less intelligent-more intelligent) of the HSPQ was added. The remaining 13 personality variables of the HSPQ served as the experimental variables. The multiple regression analysis technique was used to determine the influence of: 1. the control variables; 2. the control plus the experimental variables; 3. the experimental (personality) variables and 4. the personality variables of boys and girls separately on each of the three dependent variables. The most important results of the empirical investigation can be stated as follows: The control variables influence academic achievement. The cognitive variable is the single control variable with the greatest influence on all three the dependent variables. Sex of the pupil and school variables influence achievement in Afrikaans meaningfully, whilst faculty of comprehension has a meaningful influence on achievement in Mathematics. A multivariate model which includes personality variables is more effective than a multivariate model excluding personality variables. Personality variables in a multivariate model are, however, more effective as predictors of achievement in Afrikaans than in Mathematics or in average mark in standard ten. Personality as a construct, thus in a multivariate model which includes only personality variables, also influences achievement in Afrikaans more than it influences achievement in Mathematics or average mark in standard ten. Learning tasks in Afrikaans are more perceptual whilst those in Mathematics are more conceptual. It was therefore deduced that personality variables have a greater influence on perceptual tasks than on conceptual tasks. All personality variables influence achievement in Afrikaans whereas only factor I (self-confidence) has a meaningful influence on Mathematics achievement. No difference was found in the influence of personality variables of boys and those of girls on achievement in Afrikaans. Achievement in Mathematics of girls is however influenced more by personality variables than that of boys. Whereas factor 0 (calm) has an influence on Mathematics achievement of boys, factor I (emotionality) has an influence on the mathematics achievement of girls. The conclusion of the study, therefore, is that personality variables influence academic achievement differently, depending on the school subjects investigated, the prediction model used and the sex of the pupils. The inclusion of personality variables in a multivariate model makes the model more effective for the prediction of academic achievement. The results of tests undertaken with such a model ought to enable teachers to gain more insight into the capabilities and interests of pupils and thus to provide better vocational guidance as concerns courses to be taken at secondary school level. / Thesis (MEd)--PU vir CHO, 1985

This study is founded on the hypothesis that there is a correlation between certain cognitive factors namely the final std. 10 examination mark and aptitude as measured by the Senior Aptitude Test ( RSA) on the one hand, and academic achievement in Afrikaans- Nederlands 3 (AFN 3) on the other. The test group for the study were the 64 students who wrote the final examination in AFN 3 at the PU for CHE in 1983. These students were mainly from the 1981 enrolment; a few had enrolled in 1980. The study progressed as follows: At first a literature study was undertaken (chapter 2) in which was mainly concentrated on those cognitive factors which could influence study in general and academic achievement in tertiary study in particular. In general it appeared that authoritative researchers are of the opinion that aptitude (as measured by the different aptitude tests) is significant in the prediction of academic achievement and that the final matriculation examination is, of all cognitive factors, the best indicator of academic achievement. Secondly an empirical study was undertaken (chapter 4). Data for this study was obtained from the Statistical Consultation Service of the PU for CHE. Upon enrolment at the university a certain number of first year students are required to write psychometrical tests. Results of these tests (part of which is the Senior Aptitude Tests, tests 1-10) and the students' final examination results, as well as the ensuing academic achievements are stored on computer. Thirdly, in an ex post facto approach eleven variables, namely SAT (1-10) and the final matriculation examination were brought in connection with the achievement in AFN 3 of the said test group. By using BMDP 9 R - and SAS computer programmes intercorrelations were calculated and multiple regression analysis were done in order to calculate the contribution of individual variables and combinations of variables to the variance in AFN 3 (chapter 5) . The results are as follows: (chapters 5 and 6) A combination of the abovementioned eleven variables represent only 17,7% of the variance in AFN 3 and the best application is to be found in the case of std. 10 and SAT 1 and 7, with a contribution of 12,5% to the variance in AFN 3. It is clear that the influence of individual and combined independent variables on the dependent variables is so low that it holds no practical value for the indication of academic achievements. The role of high and low std. 10 achievement as individual independent variables combined with SAT 1-10 in the variance of AFN 3 was inquired into. In a step-by-step regression analysis was found that low std. 10 achievement and SAT 1-10 represent 53,4% of the achievement variance in AFN 3 and low std. 10 achievement combined with SAT 1, 5, 7 and 10 represent 45,6% of the variance in AFN 3. (Appendix J and K). It can be assumed that a differential application of std. 10 achievement can represent significant results in the search for predictors of academic achievement. / Skripsie (MEd)--PU vir CHO, 1988

This study is founded on the hypothesis that there is a correlation between certain cognitive factors namely the final std. 10 examination mark and aptitude as measured by the Senior Aptitude Test ( RSA) on the one hand, and academic achievement in Afrikaans- Nederlands 3 (AFN 3) on the other. The test group for the study were the 64 students who wrote the final examination in AFN 3 at the PU for CHE in 1983. These students were mainly from the 1981 enrolment; a few had enrolled in 1980. The study progressed as follows: At first a literature study was undertaken (chapter 2) in which was mainly concentrated on those cognitive factors which could influence study in general and academic achievement in tertiary study in particular. In general it appeared that authoritative researchers are of the opinion that aptitude (as measured by the different aptitude tests) is significant in the prediction of academic achievement and that the final matriculation examination is, of all cognitive factors, the best indicator of academic achievement. Secondly an empirical study was undertaken (chapter 4). Data for this study was obtained from the Statistical Consultation Service of the PU for CHE. Upon enrolment at the university a certain number of first year students are required to write psychometrical tests. Results of these tests (part of which is the Senior Aptitude Tests, tests 1-10) and the students' final examination results, as well as the ensuing academic achievements are stored on computer. Thirdly, in an ex post facto approach eleven variables, namely SAT (1-10) and the final matriculation examination were brought in connection with the achievement in AFN 3 of the said test group. By using BMDP 9 R - and SAS computer programmes intercorrelations were calculated and multiple regression analysis were done in order to calculate the contribution of individual variables and combinations of variables to the variance in AFN 3 (chapter 5) . The results are as follows: (chapters 5 and 6) A combination of the abovementioned eleven variables represent only 17,7% of the variance in AFN 3 and the best application is to be found in the case of std. 10 and SAT 1 and 7, with a contribution of 12,5% to the variance in AFN 3. It is clear that the influence of individual and combined independent variables on the dependent variables is so low that it holds no practical value for the indication of academic achievements. The role of high and low std. 10 achievement as individual independent variables combined with SAT 1-10 in the variance of AFN 3 was inquired into. In a step-by-step regression analysis was found that low std. 10 achievement and SAT 1-10 represent 53,4% of the achievement variance in AFN 3 and low std. 10 achievement combined with SAT 1, 5, 7 and 10 represent 45,6% of the variance in AFN 3. (Appendix J and K). It can be assumed that a differential application of std. 10 achievement can represent significant results in the search for predictors of academic achievement. / Skripsie (MEd)--PU vir CHO, 1988

1. THE AIM AND MOTIVATION FOR THE STUDY: The aim of the study was to determine with what measure of success pupils in the junior secondary school phase achieve to their full potential. Secondly a study was made of academic achievement prediction. Steps were taken to determine with which variables and with what measure of success the academic achievement of pupils in the junior secondary school phase can be predicted in different subjects. To achieve this aim the contribution of the cognitive, non-cognitive and biographical variables in the prediction of academic achievement in standard 5, 6 and 7 was investigated. The separate contributions of these variables in the prediction of scholastic achievement were also taken into consideration. The cognitive variables in the analyses were the IQ (non-verbal, verbal and total and the Junior Aptitude Tests. The non-cognitive variables include the KODUS Interest Questionnaire while the biographical variables include the residential area and socio-economic circumstances. According to available literature it is clear that cognitive, non-cognitive and biographical variables play a very important part in academic achievement. The pupil in the junior secondary school phase is in the period of puberty and adolescence. The early adolescence as developmental phase was viewed as described in appropriate literature. The concept early adolescence, the developmental tasks during adolescence, identification, the peer group and the cognitive development of the adolescent were discussed. The factors that affect academic achievement during adolescence were discussed. Under cognitive factors attention was given to intelligence, aptitude, ability and scholastic achievement. Personality, psychological and physical factors were discussed under non-cognitive factors while attention was also given to milieu factors. 2. THE RESULTS AND DISCUSSION OF THE EMPIRICAL INVESTIGATION: According to the correlation coefficients of Pearson there is a significant correlation between the independent variables and the dependent variables (scholastic achievement) in the junior secondary school phase. A high level of significance was identified between the IQ (non-verbal, verbal and total) and all the dependent variables. A high correlation was a I so found between the Junior Aptitude Tests and most of the dependent variables. A remarkable correlation was found between the KODUS Interest Questionnaire and Figures, Writing, Reading, Art, Handwork, Machinery and Science, while the SED Questionnaire proved high in correlation with Afrikaans, English, Mathematics, Science, Biology, History, Geography, Accountancy, Business Economics and Domestic Science in standard 6 and 7, and History, Geography, Science and Basic Techniques in standard 5. Tables were compiled to indicate the number of under-achievers and over-achievers as well as the number of pupils who achieve according to their potential. An important aim was to identify those variables that predict the academic achievements of pupils in the junior secondary school phase best. To do this the technique of multiple regression analysis was applied. The subsets which include the cognitive, non-cognitive and biographical variables were the best predictors. 3. CONCLUSION AND RECOMMENDATIONS: According to the study the cognitive variables played the most important part. In all cases these variables contributed best to R2. It is clear that the best contribution to all subjects was the verbal intelligence, except in Mathematics where the tot a IQ contributed most. The most important conclusion made on the basis of the empirical research is that the academic achievement of pupils in the junior secondary school phase can be predicted with a fair amount of success when using the inclusive variables. The realisation of intellectual potential is a very important phenomenon in any period of school life. Practical recommendations have been made with regard to the use of the research results for guidance purposes, and with a view to the manipulation of variables for the improvement of academic achievement. / Proefskrif (DEd)--PU vir CHO, 1989

1. THE AIM AND MOTIVATION FOR THE STUDY: The aim of the study was to determine with what measure of success pupils in the junior secondary school phase achieve to their full potential. Secondly a study was made of academic achievement prediction. Steps were taken to determine with which variables and with what measure of success the academic achievement of pupils in the junior secondary school phase can be predicted in different subjects. To achieve this aim the contribution of the cognitive, non-cognitive and biographical variables in the prediction of academic achievement in standard 5, 6 and 7 was investigated. The separate contributions of these variables in the prediction of scholastic achievement were also taken into consideration. The cognitive variables in the analyses were the IQ (non-verbal, verbal and total and the Junior Aptitude Tests. The non-cognitive variables include the KODUS Interest Questionnaire while the biographical variables include the residential area and socio-economic circumstances. According to available literature it is clear that cognitive, non-cognitive and biographical variables play a very important part in academic achievement. The pupil in the junior secondary school phase is in the period of puberty and adolescence. The early adolescence as developmental phase was viewed as described in appropriate literature. The concept early adolescence, the developmental tasks during adolescence, identification, the peer group and the cognitive development of the adolescent were discussed. The factors that affect academic achievement during adolescence were discussed. Under cognitive factors attention was given to intelligence, aptitude, ability and scholastic achievement. Personality, psychological and physical factors were discussed under non-cognitive factors while attention was also given to milieu factors. 2. THE RESULTS AND DISCUSSION OF THE EMPIRICAL INVESTIGATION: According to the correlation coefficients of Pearson there is a significant correlation between the independent variables and the dependent variables (scholastic achievement) in the junior secondary school phase. A high level of significance was identified between the IQ (non-verbal, verbal and total) and all the dependent variables. A high correlation was a I so found between the Junior Aptitude Tests and most of the dependent variables. A remarkable correlation was found between the KODUS Interest Questionnaire and Figures, Writing, Reading, Art, Handwork, Machinery and Science, while the SED Questionnaire proved high in correlation with Afrikaans, English, Mathematics, Science, Biology, History, Geography, Accountancy, Business Economics and Domestic Science in standard 6 and 7, and History, Geography, Science and Basic Techniques in standard 5. Tables were compiled to indicate the number of under-achievers and over-achievers as well as the number of pupils who achieve according to their potential. An important aim was to identify those variables that predict the academic achievements of pupils in the junior secondary school phase best. To do this the technique of multiple regression analysis was applied. The subsets which include the cognitive, non-cognitive and biographical variables were the best predictors. 3. CONCLUSION AND RECOMMENDATIONS: According to the study the cognitive variables played the most important part. In all cases these variables contributed best to R2. It is clear that the best contribution to all subjects was the verbal intelligence, except in Mathematics where the tot a IQ contributed most. The most important conclusion made on the basis of the empirical research is that the academic achievement of pupils in the junior secondary school phase can be predicted with a fair amount of success when using the inclusive variables. The realisation of intellectual potential is a very important phenomenon in any period of school life. Practical recommendations have been made with regard to the use of the research results for guidance purposes, and with a view to the manipulation of variables for the improvement of academic achievement. / Proefskrif (DEd)--PU vir CHO, 1989

The aim of this research project is firstly to determine whether factors other than study habits and attitudes influence academic achievement and secondly whether there exists a relationship between study habits and attitudes and academic achievement, as well as between the components of study habits and attitudes and academic achievement. To reach this aim a literature study was undertaken which was followed by an empirical investigation. It emerged from the literature that various factors influence academic achievement (sec chapter two) and that most writers agreed that there existed a relationship between study habits and attitudes and academic achievement as well as between the various components of study habits and attitudes and academic achievement (see chapter three). The empirical investigation made use of the information gathered in 1980 in the Orange Free State (see chapter four ). All the Afrikaans speaking pupils in the Orange Free State during 1980 were included in the research program. Different measuring instruments, of which the Survey of Study Habits and Attitudes, Form H, was the most important for this project, were used (see paragraph 4.5) to identify a Large variety or independent variables (respectively the experimental and control variables - see paragraph 4.6) that influence academic achievement. The dependent variable for this research was the standard ten average marks as well as marks in the !allowing subjects: Afrikaans, English, Mathematics and Science (see paragraph 4.6.3). The BMDP-computer program (Dixon and Brown, 1979; revised 1983) was used to process the results. The different statistical techniques are described in paragraph 4.7. A factor analysis was carried out to group the different variables according to their correlation coefficients with the standard ten average marks (sec table 5.1). The 67 independent variables (respectively the experimental and control variables) were grouped into different factors. The 18 factors were then used as independent variables to determine their contribution R2 (see tables 5.2 and 5.3). Next the separate and collective contribution or the components or study habits and attitudes (respectively the experimental variables) to R2 in each or the dependent variables (respectively standard ten average, Afrikaans, English, Mathematics and Science) was determined (see tables 5.4 and 5.5). The results or this study can be submitted up as follows: (1) Apart from study habits and attitudes other factors influence academic achievement. (2) Study habits and attitudes contribute a statistical significant proportion or the variance in academic achievement. (3) With a few exceptions the components or study habits and attitudes do not contribute a statistical significant proportion or the variance in academic achievement. / Thesis (MEd)--PU vir CHO, 1987

In this study the possibility of predicting academic success at first year university level by means of the discrepancy between nonverbal and verbal intelligence test scores, is investigated. Firstly the problem is stated and the purpose and programme of the research are outlined. A closer look at various points of view on intelligence is given in the next chapter. Nonverbal and verbal intelligence is discussed. The hypotheses is that nonverbal intelligence relates more closely to the concrete in the field of intellectual activity, while the verbal intelligence deals with the symbolic and abstract. It is further stated that nonverbal intelligence resembles more closely the hereditary intelligence than the verbal, which is to a greater extent the result of non- genetic factors. Academic achievement and the various influences on it are described. The relationship between factors influencing the verbal intelligence and factors influencing academic achievement is pointed out. It is reasoned that negative influences will prevent the verbal intelligence from developing to the same or a higher level than the nonverbal intelligence. The same influences will prevent the student from achieving academically as could have been expected from his I. Q. Positive environmental influences will stimulate the actualisation of genetic intelligence and will also lead to relative better academic achievement. In the empirical research first year students with a discrepancy of 10+ between nonverbal and verbal I. Q. scores are grouped. Groups with a higher nonverbal score are designated as negative groups and those with higher verbal scores as positive groups. By means of the Wilcoxon Matched- Pairs Signed Ranks Test these groups are compared with groups consisting of students with a discrepancy of less than 10 between nonverbal and verbal I.Q. scores. The results show that only the largest negative group, which is a combination of men and women groups from various degree courses, achieves academically lower than the control group. The result is reliable within the 0, 05 level of confidence. / Proefskrif (DEd)--PU vir CHO, 1973

Researchers have been trying for years to determine why such a large percentage of first-year university students fail or terminate their courses. There is a need for research about the identification of factors which have a negative influence on the academic achievement of students. With regard to the factors which influence academic achievement, one can distinguish between cognitive and non-cognitive factors. In this study intelligence was referred to as a cognitive factor, and its link with academic achievement pointed out. Research has proved that intelligence is one of the best predictor's for academic achievement. Non-cognitive factors selected for this research include the family, the school, interests, motivation and adjustment. From the literature survey which was undertaken (chapter 2) about students in general (practically all fields of study), it was deduced that there is a link between academic achievement and some non-cognitive factors. There is thus a wide spectrum of factors which can affect the individual's total existence positively or negatively. The objective with this study was to identify those variables (non-cognitive) which have the greatest influence on the academic achievement of Biblical students. All the final-year education students (N = 70) in Biblical Studies who had started their studies in 1981 and completed their courses in 1984 were used as population. The students had all completed a degree at the end of 1983 and then completed the HED(P) diploma at the end of 1984. The measuring instruments which were used were the 19-Field Interest Questionnaire, the PHSF-Relationship Questionnaire and Standard 10 achievement. The 19-FIQ was compiled for the measurement of professional interests of senior secondary school pupils, students and adults in 19 broad fields of interest. The purpose of the PHSF was to measure the personal, home, social and formal relationships of high school pupils, students and adults in order to determine their measure of adjustment. As criterion of previous achievement, performance in the subjects' Standard 10 examination was taken. In the empirical study the ex post facto approach was used. The data were analysed by means of a multiple regression analysis in order to identify those non-cognitive variables which influence academic achievement. The BMDP9R computer programme was used for this purpose. Fifteen independent variables were selected because they made the biggest contribution to the R2, and because these different fields and components are very closely linked to the teaching profession. The contribution of the selected independent variables to the R2 indicated a very good correlation, viz. R2 = 0,61, or 61%. The selected independent variables which made the best contribution to the square of the multiple correlation co-efficient (R2) is Standard 10 achievement, with 0,319 or 31,9%, 19-FIQ 10 (congeniality) with 0,277 or 27% and PHSF 4 (nervousness) with 0,044 or 4,4%. The following six independent variables seem, according to the Cp criterion, to be the best predictors of academic achievement in this study: Standard 10 performance, 19-FIQ 10 (congeniality), PHSF 3 (self-control), PHSF 4 (nervousness), PHSF 6 (family influences) and PHSF 7 (personal freedom). The contribution of the six best predictors to the R2 = 0,52 or 52%. The predictors which made the best contribution to the R2 are Standard 10 performance, with 0,31 or 31% and the 10-FIQ 10 (congeniality), with 0,28 or 28%. The results indicate that the independent variables separately and in conjunction had a significant influence on the prediction of academic achievement. The independent variables (non-cognitive factors) thus had a direct influence on the academic achievement of university students. From the results of the study it emerges that the independent variables separately and in conjunction have a significant influence on academic achievement, and the hypothesis is supported that there is a link between the non-cognitive factors and academic achievement. / Skripsie (MEd)--PU vir CHO, 1990

The aim of this research project is firstly to determine whether factors other than study habits and attitudes influence academic achievement and secondly whether there exists a relationship between study habits and attitudes and academic achievement, as well as between the components of study habits and attitudes and academic achievement. To reach this aim a literature study was undertaken which was followed by an empirical investigation. It emerged from the literature that various factors influence academic achievement (sec chapter two) and that most writers agreed that there existed a relationship between study habits and attitudes and academic achievement as well as between the various components of study habits and attitudes and academic achievement (see chapter three). The empirical investigation made use of the information gathered in 1980 in the Orange Free State (see chapter four ). All the Afrikaans speaking pupils in the Orange Free State during 1980 were included in the research program. Different measuring instruments, of which the Survey of Study Habits and Attitudes, Form H, was the most important for this project, were used (see paragraph 4.5) to identify a Large variety or independent variables (respectively the experimental and control variables - see paragraph 4.6) that influence academic achievement. The dependent variable for this research was the standard ten average marks as well as marks in the !allowing subjects: Afrikaans, English, Mathematics and Science (see paragraph 4.6.3). The BMDP-computer program (Dixon and Brown, 1979; revised 1983) was used to process the results. The different statistical techniques are described in paragraph 4.7. A factor analysis was carried out to group the different variables according to their correlation coefficients with the standard ten average marks (sec table 5.1). The 67 independent variables (respectively the experimental and control variables) were grouped into different factors. The 18 factors were then used as independent variables to determine their contribution R2 (see tables 5.2 and 5.3). Next the separate and collective contribution or the components or study habits and attitudes (respectively the experimental variables) to R2 in each or the dependent variables (respectively standard ten average, Afrikaans, English, Mathematics and Science) was determined (see tables 5.4 and 5.5). The results or this study can be submitted up as follows: (1) Apart from study habits and attitudes other factors influence academic achievement. (2) Study habits and attitudes contribute a statistical significant proportion or the variance in academic achievement. (3) With a few exceptions the components or study habits and attitudes do not contribute a statistical significant proportion or the variance in academic achievement. / Thesis (MEd)--PU vir CHO, 1987