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Persoonlikheid as voorspeller van akademiese prestasie / Mechaela ScottScott, Mechaela January 1984 (has links)
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
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Persoonlikheid as voorspeller van akademiese prestasie / Mechaela ScottScott, Mechaela January 1984 (has links)
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
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Enkele kognitiewe faktore en akademiese prestasie van studente in Afrikaans-Nederlands / Paul Machiel BesterBester, Paul Machiel January 1988 (has links)
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
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Enkele kognitiewe faktore en akademiese prestasie van studente in Afrikaans-Nederlands / Paul Machiel BesterBester, Paul Machiel January 1988 (has links)
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
|
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Die realisering van verstandspotensiaal by die kind in die junior sekondêre skoolfase / Cornelius Petrus SchutteSchutte, Cornelius Petrus January 1989 (has links)
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
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Die realisering van verstandspotensiaal by die kind in die junior sekondêre skoolfase / Cornelius Petrus SchutteSchutte, Cornelius Petrus January 1989 (has links)
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
|
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Die verband tussen studiegewoontes en -houdings en akademiese prestasie / Eunice EngelbrechtEngelbrecht, Eunice January 1986 (has links)
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
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Die voorspelbaarheid van akademiese prestasie deur die verskille tussen nie-verbale toetsintelligensieprestasies / Hendrik Barnardus KrugerKruger, Hendrik Barnardus January 1972 (has links)
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
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Die verband tussen enkele nie-kognitiewe faktore en akademiese prestasie van studente in Bybelkunde / Antonie Gysbert WeidemanWeideman, Antonie Gysbert January 1989 (has links)
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
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Die verband tussen studiegewoontes en -houdings en akademiese prestasie / Eunice EngelbrechtEngelbrecht, Eunice January 1986 (has links)
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
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