The aim of this research project was to determine the relative contribution of cognitive and non-cognitive variables to accounting achievement and to determine which variables have the greatest influence on accounting achievement so that these variables can be used to predict accounting achievement. To reach the aim of the study, a literature study was undertaken which was followed by an empirical investigation. The literature study was divided into a study of cognitive {see chapter 2) and non-cognitive (see chapter 3) variables. It was found that cognitive variables had the greater influence on academic achievement with previous achievement and intelligence as the main contributors. Research findings indicated that cognitive variables were responsible for 25 to 50 percent of the variance in academic achievement. In search for the remaining 75 to 50 percent, researchers included non-cognitive variables in their research attempts. Most researchers came to the conclusion that academic achievement could be better predicted when both cognitive and non-cognitive variables were included in research attempts, although no one was willing to report a definite increase in percentage. The empirical investigation made use of the information gathered in 1980 in the Orange Free State {see chapter 4). All the Afrikaans speaking pupils in die Orange Free State during 1980 were included in the research program. Different measuring instruments {see par.4.4) were used to identify a large variety of independent variables (see par. 4.5.1). The dependent variable for this research was standard ten Accounting (see par. 4.52). The different statistical techniques are described in par. 4.6.2. A factor analysis was carried out to group the different variables according to their correlation coefficients with standard ten Accounting (see table 5.1). The 61 independent variables were grouped into 17 different factors. On these factors, together with average standard seven marks and six individual standard seven subjects, several multiple regression analysis were executed to find the best collection of predictors and their contribution to R2 {see tables 5.4 to 5.11). The Mallows Cp-value was used as criterium in finding the best collection of predictors. In chapter five the results of the research were reported. The main findings of this research are: 1) Cognitive variables contribute more than non-cognitive variables to the prediction of standard ten accounting achievement although non-cognitive variables contribute considerable. 2) Previous academic achievement is the single variable with the largest contribution to the prediction of standard ten accounting achievement. 3) Study habits, attitudes and affect are the non-cognitive variables with the largest contribution to the prediction of standard ten accounting achievement. 4) The standard ten accounting achievement of boys and girls are influenced by different independent variables. 5) Personality, family and school variables do not have a considerable influence on standard ten accounting achievement, although personality variables B contributes considerable to the standard ten accounting of boys and schoolfactors and family circumstances to that of girls. In chapter six certain conclusions were made, implications of the research findings were given, shortcomings of the research findings were given and certain recommendations were made. While it is true that little can be done to the intelligence of a person, the results of this research that previous academic achievement, study methods and intellectual factors were the three most important factors for standard ten accounting achievement are of great value for teachers. Teachers must make sure that every child knows each part of the work before they carry on with new work and must help or provide children with the best study methods. By doing so, the teacher can do a great deal in attaining high accounting achievement. / 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

1. AIM AND OVERVIEW The aim of the research was to determine with which variables and what measure of success the academic achievement of black pupils can be predicted in different school subjects. To achieve this aim a theoretical study was firstly made of the phenomenon, academic achievement prediction as it is manifested in the educational context. It was indicated that the action to predict is of supporting value to education, and that it assumes a central position in the teaching-learning situation. In addition it was indicated that academic achievement prediction is a difficult undertaking, that it demands exceptional knowledge of the teacher, and that it is essential that the teacher should be able to predict as accurately as possible. Secondly a study was made of the methodology of academic achievement prediction. It was indicated that there are different procedures for the initial selection of predictor variables, procedures which are mainly variations of factor analysis. Possible usages of moderating variables for the grouping of pupils in homogeneous groups were also discussed and procedures for the identification of the best predictors of academic achievement were described. In the third instance the academic achievement of black pupils was investigated together with the factors by which it is influenced. The indications are that the percentages of standard ten passes are relatively low, and that there are, inter alia, sex differences, language group differences and also urban/rural differences in the achievement of pupils. Then the causes of poor academic achievement by black pupils in the school and family environment were considered, and also the extent of educational and cultural deprivation. It was concluded that the family environment does not always promote academic achievement at school. With regard to the variables which are specifically related to the achievement of black pupils, a limited number of research results are available. In spite of this, there are indications that the pupil and milieu variables are related in the same measure to the academic achievement of black pupils as indicated by the general tendencies in research results. This conclusion was arrived at with some reservation, because there are certain indications of differences in the relative weighting of variables pertaining to achievement. In addition it was discovered that there are non-test factors which also co-determine the achievement of black pupils in psychometric tests. It transpired too, that further research is necessary as regards the sources of the unexplained variance in the academic achievement of black pupils. In the fourth instance a study was mad0 of the relationship between a specific selection of variables and the academic achievement of black pupils. An image was obtained of the relationship between ability, previous achievement, interest and personality, and the academic achievement of black pupils, and then some problem questions based on the relevant literature, were formulated. The empirical research which followed, attempted to find some of the answers to these questions. 2. AIM, PROCEDURE AND RESULTS OF THE EMPIRICAL INVESTIGATION. The aim of the empirical investigation was to determine the extent to which the standard ten achievement of black pupils can be predicted with the aid of cognitive, non-cognitive and biographical variables. Four groups of hypotheses were drafted. The group-A hypotheses investigated the contribution of the subsets of the best predictors from all the independent variables to R2. The groups B, C, and D hypotheses studied respectively, the contributions of the cognitive, non-cognitive, and biographical variables to R2 in the dependent variables. In the research, the data was used of 871 subjects of the 19179 students who comprised the 1980 pupil population which took part in the Guidance Project of the Department of Education and Development Aid. Data was compiled of three psychometric tests, the Academic Aptitude Test, the Vocational Interest Questionnaire, and the High School Personality Questionnaire. This data was subjected to factor analysis and nine factors were identified. To test the different groups of hypotheses, 81e technique of multiple regression analysis was applied in two ways. Firstly, the all possible subsets multiple regression method was used so as to identify the subset of best predictors per dependent variable, on the basis of the Cp criterion. The group-A hypotheses were tested on this basis. Secondly, the remaining hypotheses were tested by calculating differences in R2 and testing their significance. In the case of each dependent variable R2 1 was calculated for a basic set of control variables which varied per group hypotheses. To this set of control variables the cognitive predictors were added and R2 2 calculated. The difference between R2 2 and R2 1 then gives an indication of the contribution which was made by the cognitive variables to the prediction. The same procedure was followed to calculate the contribution of the non-cognitive and of the biographical variables to the prediction. The sets of control variables varied in the different analyses. In each case the educational significance of the contributions to R2 was calculated with the aid of the formula for the calculation of effect sizes as drafted by Cohen (1977). With the formula of Cohen, a more precise indication was obtained of the educational significance of the contributions to R2. The effect sizes indicated whether contributions to R2 were of small, medium or large educational significance. On the basis of the results for multiple regression analyses, selections were made of the biographical variables, and the potential role of each as moderators of the prediction of dependent variables were then investigated. In the last instance a cross validation of results was made. The results of the statistical analyses indicate in the first instance that the subsets of best predictors of standard ten achievement, consist of cognitive, non-cognitive and biographical variables. The combinations of predictors vary from one school subject to another, although certain trends were observed, like for instance that the cognitive variables generally made the largest contribution to R2 of all the predictors. It was also found that the best subsets of predictors provide better predictions for standard ten total, English, Afrikaans and Biology, and weaker predictions for History and the Vernacular. In the second instance the results indicate that the cognitive variables, like aptitude and previous achievement separately and together, made a statistical- and educational-significant contribution to the prediction of achievement in the separate standard ten subjects. These contributions were made in addition to the non-cognitive and biographical variables which served as control measures. The contributions of the cognitive variables are larger in the case of standard ten total, Afrikaans and English, and smaller in the case of the Vernacular, History and Biology. It was also found that previous achievement always rendered a larger contribution to the prediction, except in the case of English and History. In the third instance it was found that the non-cognitive variables, interest and personality separately and together. produce in isolated instances, significant contributions to the prediction of the dependent variables. These contributions to the prediction of dependent variables are produced in addition to the control variables (cognitive and biographical variables), and they are small and also (in terms of effect sizes), of small educational significance. In the fourth instance it was found that, sex in four cases, living area (urban/rural) in four, language group 2 (Zulu/non-Zulu) in four, and language group 1 (Sotho/non-Sotho) in six cases, made significant contributions in addition to the cognitive and non-cognitive control variables) to the prediction of standard ten achievement. These contributions vary from a small to a large measure of educational significance. Together, the variables contribute significantly to all the dependent variables, and it was found that the contributions or the biographical variables are largest with regard to History and Biology. Finally, the results of the research on the effects of moderator variables indicate chat sex has a modifying effect only in the case of the Vernacular as regards the prediction. Living area has no modifying effect and the effect of language group 1 is limited to History. Language group 2 is the variable which, with regard to most dependent variables, has a moderating effect on the prediction, as regards all the dependent variables except the Vernacular. In the validity study it was found that the degree of validity was satisfactory, with the exception of the results relating to History. The most important conclusion made on the basis of the empirical research is that the academic achievement of black pupils and the inclusive variables can only be predicted with limited success. school subjects vary a great deal in their predictability, and in each case there is a large amount of unexplained variance of which the source probably lies outside the scope of the variables provided for in the research. A further conclusion is that the variables, which together with others (and also individually) make the greatest contribution to the prediction, are the cognitive variables. The contribution of the non-cognitive variables, interest and personality, is quite small, even smaller than the indications in present literature. As a whole this is in accordance with the results of other investigations in developing countries. In conclusion, the inference was made as a result of the moderator study that biographical variables are indeed potentially serviceable as moderating variables and that language group 2 (Zulu/non-Zulu) probably has the greatest potential. The results of this research have implications for teaching practice as well as for further research. Practical recommendations have been made with regard to the use of the results for guidance purposes, and with a view to the manipulation of variables for the improvement of academic achievement. Recommendations have also been made for further research on alternative variables as well as the non-test factors which influence the academic achievement of black pupils. / Proefskrif (DEd)--PU vir CHO, 1987

This investigation has been undertaken to determine whether a correlation exists between the cognitive factors, final standard ten examination mark and aptitude, as measured by the Senior Aptitude Test on the one hand and academic achievement in HDE-post graduate in the Humanities field of study on the other hand. For this investigation the test group was the 1981-intake of students at the PU for CHE who studied in the hutr.ani ties field of study and completed their studies at the end of 1984. The theoretical background of the investigation was obtained by the study of authoritative literature regarding the cognitive and non-cognitive factors which have an influence on academic achievement. An ex post facto-approach was used for the experimental design. The data used was obtained from the Senior Aptitude Test and the final standard ten examin8.tion marks of the students concerned as well as their final academic achievement in the HDE-post graduate course. The data has been analysed by means of a computer programme. Multiple linear regression analysis was used to determine the combined and individual influence of the independant variables (Senior Aptitude Test and final standard ten examination mark) on the dependant variable (HDE-achievement). From the results of the investigation it becomes clear that the combined and separate influence of the independant variables on the dependant variable is very low and of no significant practical value for the prediction of academic success. The conclusion can thus not be drawn that the Senior Aptitude Test and final standard ten examination mark are good predictors of academic achievement in a post graduate HDE-course in the humanities field of study. Various factors, cognitive as well as non-cognitive, should be used in combination for the best prediction of academic achievement at tertiary level. / Thesis (MEd)--PU vir CHO, 1986

AIM OF THE STUDY - The general aim of the study is to design a selection test battery that can be used to screen students for the diploma courses in Management practice and Personnel management before the enrolment at the Witwatersrand Technikon. The specific aims are twofold: namely theoretical and empirical. The theoretical aim is firstly to give some perspective as far as the use of psychometric tests in the selection procedure, and secondly to give an overview of those factors that affect academic performance. The empirical aim consists of three objectives: To determine which factors are significantly related to academic performance of first year students for the Management practice and the Personnel management courses, respectively. To determine those factors that reflect a significant difference between the successful and unsuccessful students in both diploma courses. To develop a profile of the successful and unsuccessful groups' test performances for selection purposes. METHOD OF INVESTIGATION - A study of the relevant literature was undertaken concerning the role of psychometric tests in the selection procedure, as well as the effect of different cognitive and non-cognitive factors on academic performance. As a result of the limited number of first year students in these two courses, the total first year student group was involved in this study. The psychometric tests used in this study are the 19 Field Interest Inventory, the Structured Objective Rorschach test (SORT), The Survey of Study Habits and Attitudes (SSHA), the 16 Personality factor questionnaire {16PF), the subtest Mental Alertness of the Intermediate Battery and the Academic Achievement Battery. RESULTS OF THE MULTIPLE REGRESSION ANALYSIS - The test that shows the highest correlation with academic performance for both groups is the 16PF. In the case of the Management practice group, the correlation is 0,62 and for the Personnel management group, the correlation is 0,77. The Management practice group also reflected correlations between academic performance and previous performance (r=0,48) and between academic performance and interest (r=0,63). On the other hand, correlations were also found between academic performance and the SSHA ( r=O, 5 9) and between academic performance and mental alertness (r=0,42) concerning the Personnel management group. The 16PF therefore showed the highest correlation with academic performance for both groups. As a result of these findings and the relatively small population group used in this study it was decided, for the remainder of the investigation to combine the two groups. The new combined group was then subdivided into a successful and an unsuccessful group. RESULTS OF THE PROFILE ANALYSIS - The successful group obtained average scores which were higher than those of the unsuccessful group on eight factors of the 16PF. These eight factors are: A(Sociality), B (Intelligence), E(Dominance), F(Carefreeness), H (Social venturesomeness), L(Suspiciousness), N(Astuteness) and Ql(Radicalism). Of these eight factors, the differences for the last three are very insignificant. The unsuccessful group obtained higher average scores on the remaining eight factors but once again these differences are insignificant. RESULTS OF THE t-TEST - Significant differences were found between the successful and unsuccessful groups with regard to factors A(Sociality), B(Intelligence) and F(Carefreeness) on the 0,01-level while significant differences on the 0,05-level were obtained on factors E(Dominance) and Q3(Self-control). These results can be summarised as follows: * The successful group• is definitely more social, in other words more outgoing, carefree and more participative than the unsuccessful group. * The successful group has a greater mental ability than the unsuccessful group, is more independent and shows more enthusiasm. * The unsuccessful group shows a greater degree of self-control than the successful group with the result that they experience more anxiety in the process. According to this study, personality factors seem to play a more significant role than any other factors as measured in this particular case. Biographical data should also be considered in a study like this as this might possibly lead to other factors that influence academic performance. / Skripsie (MA)--PU vir CHO, 1987

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

Within the framework of comprehensive research that has been done on the mathematics achievement of first-year university students, research literature contains relatively few studies concerning the prediction of the mathematics achievement of final year students. An ex post facto empirical study was undertaken to rectify this situation to some extent. The aims of this study were: • To develop prediction models with which to predict the mathematics achievement of third-year students at the PU for CHE. • To develop a prediction analysis for continuous data by means of which the mathematics achievement of third-year students can be predicted in terms of a pass/fail dichotomy by using the fundamentals of Boolean algebra. • To determine, as a secondary aim, the differential influence of several independent variables on the mathematics achievement of male and female students in their third year. Of the set of independent variables in this study, five indicated previous achievement, 10 were aptitude variables (including an estimated IQ score) and 21 were measures of different interests, while a measure of the algebraic preparedness of prospective mathematics students on the PU for CHE was also included. The mathematics achievement of students at the end of the first semester of the first year was used in part of the investigation as an independent variable. Four criteria were defined to quantify the mathematics achievement of students at the PU for CHE. In three of these, unsuccessful attempts to obtain a pass in mathematics courses were taken into consideration. The aptitude variables in this study were measured with the Senior Aptitude tests (Human Sciences Research Council), the 19-Field Interests Questionnaire (Human Sciences Research Council) and the algebraic preparedness of students was measured by means of a 60-item multiplechoice test developed by this researcher and of which measures of validity and reliability were reported. The data of two groups of subjects considered as study populations, were used in the study. The group of first-year students following mathematics courses for the first time in 1982 was employed as an experimental group. Of the 154 first-year students in this group, 58 were able to advance to the third year and wrote the examination in least one mathematics course in that year. The class of first-year students registered for mathematics courses for the first time in 1983 was used as a crossvalidation group in order to validate the prediction models. This group consisted of 138 students, of which 54 advanced to the third year. Six hypotheses were examined in this study by means of several statistical techniques. By means of singular correlations it was shown that certain independent variables exerted a bigger influence on the mathematics performance of third-year students than others and that the correlations of some independent variables with mathematics achievement decreased from the first year to the third year. Regarding other variables, the opposite tendency was found. By means of factor, regression, discriminant and Boolean analysis, it was further found that the mathematics achievement of male and female students on the third year level was influenced differently by independent variables. The hypothesis that a higher percentage of the variance of mathematics performance in the case of females than that of males can be accounted for, could not be accepted for all criteria of mathematics achievement. The validity of prediction models could also not be accepted for all criteria of mathematics performance, even if the mathematics achievement of students at the end of the first semester in the first year was included as an independent variable in the regression analysis. Finally it was found that prediction models for the pass/fail dichotomy for mathematics achievement, developed by means of Boolean analysis, were on the average more successful in terms of validity than the discriminant functions developed by using discriminant analysis. This result indicated a promising future for the use of Boolean analysis in the prediction of academic achievement. / Proefskrif (DEd)--PU vir CHO, 1988

AIM OF THE STUDY - The general aim of the study is to design a selection test battery that can be used to screen students for the diploma courses in Management practice and Personnel management before the enrolment at the Witwatersrand Technikon. The specific aims are twofold: namely theoretical and empirical. The theoretical aim is firstly to give some perspective as far as the use of psychometric tests in the selection procedure, and secondly to give an overview of those factors that affect academic performance. The empirical aim consists of three objectives: To determine which factors are significantly related to academic performance of first year students for the Management practice and the Personnel management courses, respectively. To determine those factors that reflect a significant difference between the successful and unsuccessful students in both diploma courses. To develop a profile of the successful and unsuccessful groups' test performances for selection purposes. METHOD OF INVESTIGATION - A study of the relevant literature was undertaken concerning the role of psychometric tests in the selection procedure, as well as the effect of different cognitive and non-cognitive factors on academic performance. As a result of the limited number of first year students in these two courses, the total first year student group was involved in this study. The psychometric tests used in this study are the 19 Field Interest Inventory, the Structured Objective Rorschach test (SORT), The Survey of Study Habits and Attitudes (SSHA), the 16 Personality factor questionnaire {16PF), the subtest Mental Alertness of the Intermediate Battery and the Academic Achievement Battery. RESULTS OF THE MULTIPLE REGRESSION ANALYSIS - The test that shows the highest correlation with academic performance for both groups is the 16PF. In the case of the Management practice group, the correlation is 0,62 and for the Personnel management group, the correlation is 0,77. The Management practice group also reflected correlations between academic performance and previous performance (r=0,48) and between academic performance and interest (r=0,63). On the other hand, correlations were also found between academic performance and the SSHA ( r=O, 5 9) and between academic performance and mental alertness (r=0,42) concerning the Personnel management group. The 16PF therefore showed the highest correlation with academic performance for both groups. As a result of these findings and the relatively small population group used in this study it was decided, for the remainder of the investigation to combine the two groups. The new combined group was then subdivided into a successful and an unsuccessful group. RESULTS OF THE PROFILE ANALYSIS - The successful group obtained average scores which were higher than those of the unsuccessful group on eight factors of the 16PF. These eight factors are: A(Sociality), B (Intelligence), E(Dominance), F(Carefreeness), H (Social venturesomeness), L(Suspiciousness), N(Astuteness) and Ql(Radicalism). Of these eight factors, the differences for the last three are very insignificant. The unsuccessful group obtained higher average scores on the remaining eight factors but once again these differences are insignificant. RESULTS OF THE t-TEST - Significant differences were found between the successful and unsuccessful groups with regard to factors A(Sociality), B(Intelligence) and F(Carefreeness) on the 0,01-level while significant differences on the 0,05-level were obtained on factors E(Dominance) and Q3(Self-control). These results can be summarised as follows: * The successful group• is definitely more social, in other words more outgoing, carefree and more participative than the unsuccessful group. * The successful group has a greater mental ability than the unsuccessful group, is more independent and shows more enthusiasm. * The unsuccessful group shows a greater degree of self-control than the successful group with the result that they experience more anxiety in the process. According to this study, personality factors seem to play a more significant role than any other factors as measured in this particular case. Biographical data should also be considered in a study like this as this might possibly lead to other factors that influence academic performance. / Skripsie (MA)--PU vir CHO, 1987

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

Within the framework of comprehensive research that has been done on the mathematics achievement of first-year university students, research literature contains relatively few studies concerning the prediction of the mathematics achievement of final year students. An ex post facto empirical study was undertaken to rectify this situation to some extent. The aims of this study were: • To develop prediction models with which to predict the mathematics achievement of third-year students at the PU for CHE. • To develop a prediction analysis for continuous data by means of which the mathematics achievement of third-year students can be predicted in terms of a pass/fail dichotomy by using the fundamentals of Boolean algebra. • To determine, as a secondary aim, the differential influence of several independent variables on the mathematics achievement of male and female students in their third year. Of the set of independent variables in this study, five indicated previous achievement, 10 were aptitude variables (including an estimated IQ score) and 21 were measures of different interests, while a measure of the algebraic preparedness of prospective mathematics students on the PU for CHE was also included. The mathematics achievement of students at the end of the first semester of the first year was used in part of the investigation as an independent variable. Four criteria were defined to quantify the mathematics achievement of students at the PU for CHE. In three of these, unsuccessful attempts to obtain a pass in mathematics courses were taken into consideration. The aptitude variables in this study were measured with the Senior Aptitude tests (Human Sciences Research Council), the 19-Field Interests Questionnaire (Human Sciences Research Council) and the algebraic preparedness of students was measured by means of a 60-item multiplechoice test developed by this researcher and of which measures of validity and reliability were reported. The data of two groups of subjects considered as study populations, were used in the study. The group of first-year students following mathematics courses for the first time in 1982 was employed as an experimental group. Of the 154 first-year students in this group, 58 were able to advance to the third year and wrote the examination in least one mathematics course in that year. The class of first-year students registered for mathematics courses for the first time in 1983 was used as a crossvalidation group in order to validate the prediction models. This group consisted of 138 students, of which 54 advanced to the third year. Six hypotheses were examined in this study by means of several statistical techniques. By means of singular correlations it was shown that certain independent variables exerted a bigger influence on the mathematics performance of third-year students than others and that the correlations of some independent variables with mathematics achievement decreased from the first year to the third year. Regarding other variables, the opposite tendency was found. By means of factor, regression, discriminant and Boolean analysis, it was further found that the mathematics achievement of male and female students on the third year level was influenced differently by independent variables. The hypothesis that a higher percentage of the variance of mathematics performance in the case of females than that of males can be accounted for, could not be accepted for all criteria of mathematics achievement. The validity of prediction models could also not be accepted for all criteria of mathematics performance, even if the mathematics achievement of students at the end of the first semester in the first year was included as an independent variable in the regression analysis. Finally it was found that prediction models for the pass/fail dichotomy for mathematics achievement, developed by means of Boolean analysis, were on the average more successful in terms of validity than the discriminant functions developed by using discriminant analysis. This result indicated a promising future for the use of Boolean analysis in the prediction of academic achievement. / Proefskrif (DEd)--PU vir CHO, 1988