A study of 96 students at the Islamic University of Gaza was designed to determine whether there is a difference in extroversion and neuroticism between high achieving and low achieving students, and whether there is a difference in extroversion and neuroticism due to sex. The Eysenck Personality Inventory was used to measure extroversion and neuroticism; academic achievement, high or low, was determined by students' grades at the University.The results of a two-way analysis of variance indicated that there was no significant difference in extroversion due to academic achievement, nor was there any significant difference in extroversion due to sex.Another two-way analysis of variance indicated that there was no significant difference in neuroticism due to academic achievement; however, female students did measure significantly higher than male students in neuroticism.

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

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

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 purpose of the study was to examine differential effects, if any, which two types of sma.11-group continuing freshman orientation programs had on participant academic achievement and perceptions of campus environment. The initial research sample consisted of 155 students randomly selected from 328 freshmen entering Taylor University, Upland, Indiana, for the first time in the fall term, 1980. Fifty-two students were randrn1v selected to participated in three levels of continuing orientation. Level 1 involved participation in the Providing Relevant Opportunities and Building Experiences (PROSE) program at Taylor University. PROBE was a small-group continuing orientation program with a prescribed format and content. Level 2 involved participation in a small-group continuing orientation program in which neither format nor content were prescribed. Level 3 involved no participation in a continuing orientation program at Taylor University and served as the control group for the study.Following completion of the seven week orientation program, perceptions of research subjects about campus environment were measured by the college and University Environment Scales (CUES). Grade point averages of all subjects were obtained following completion of the fall term. The final sample was comprised of forty-nine students in each of the three experimental groups.Analysis of variance, with subsequent t-tests, where appropriate, were utilized to test three null hypotheses pertaining, to differences among groups on the post test criterion measure of student perceptions about the campus environment and three null hypotheses pertaining to differences on the post test criterion measure of academic achievement. All decisions with regard to significance were made at the .05 level.Findings of the study support the following conclusions regarding the effects of two types of continuing freshman orientation programs on academic achievement an perceptions of the campus environment at Taylor University:1. Students participating in a small-group continuing orientation program with a prescribed format and content do not perceive the campus environment any differently than non-participants.2. Students participating in a small-group continuing orientation program without a prescribed format and content do not perceive the campus environment any differently than non-participants.3. Students participating in a small-group continuing orientation program with a prescribed format and content do not perceive the campus environment any differently than students participating in a small-group continuing orientation program without a prescribed format and content.4. Participants in a small-group continuing orientation program achieve a higher grade point average than non-participants, regardless of whether the format: and content are prescribed b y the university.Application of the findings were extended for observations beyond the scope of the original research. One such observation involved speculation regarding the role of the small-group format in the improvement off participant academic achievement.Results of the study suggest that participation in a continuing orientation program with a small-group format contributes to academic achievement. The results further suggest that such an improvement in academic achievement occurs irrespective of the format or content of the small-group continuing orientation program. Implications which might be drawn from such results include the following:1. The small-group process as utilized in the continuing orientation program contributes to increased academic achievement.2. Format or content of small-group continuing orientation programs are not a contributing factor to increased academic achievement.Further research to determine the differential effects, if any, of the small-group process compared to alternative processes in continuing orientation is needed to empirically support or refute such statements.

Concurrent and prospective relationships between symptoms of depression, anxiety, attention deficit/hyperactivity disorder (ADHD), and conduct disorder (CD) and academic achievement were examined in a large sample of Canadian children. Students in Grade 5 (N = 715) completed the depression and anxiety subscales of the Behaviour Assessment System for Children – Second Edition. Parents reported on their child’s symptoms of ADHD and CD using the Brief Child and Family Phone Interview. Academic achievement was measured using teacher-rated learning skills and students’ grade point average (GPA) from their Ontario Student Record (OSR) in fifth grade and again in sixth grade (N = 627). Symptoms of depression, anxiety, ADHD, and CD were significantly negatively correlated with academic achievement at Time 1 and Time 2. After controlling for child’s sex, household income, maternal education, and days absent, children’s mental health problems accounted for an additional 12% and 11% of the variability in their Time 1 mean ratings of learning skills and GPA, respectively. Only symptoms of ADHD predicted Time 2 GPA (1% of the variance) after controlling for Time 1 GPA and other sociodemographic variables. Findings highlight the unique contribution of mental health problems in predicting academic achievement and point to the need to promote children’s mental health in schools.

Typescript. / Thesis (Ph. D.)--University of Hawaii, 1970. / Bibliography: leaves 166-173. / viii, 173 l graphs, tables

This study modifies Cummins' (1997) theoretical framework of minority student achievement and social power relations to account for differences in educational achievement among different identifiable subgroups of the ESL population. This framework provides the conceptual structure for a multidimensional understanding of ESL academic achievement (e.g. Gonzales, 2001) whereby the mediating influence of the broad social power relations between dominant and minority groups, students' individual characteristics, including personal abilities, experiences and socio-demographic backgrounds, interacts with ecologies, including educational structures such as curricula, curricular organization, school populations and the policy environment to influence educational trajectories. This study employs descriptive, bi-variate, and logistic and multiple regression to perform secondary analysis on data describing the academic trajectories of the ESL students (n=7 527) of British Columbia's 1997 grade eight cohort (n=48 265). It compares the results to a native English speaker (NES) baseline. ESL students are disaggregated by ethno-cultural background, English proficiency, gender, age on entry to the BC school system, and socio-economic status. School population effects are also considered. The dependent variables are five and six-year graduation rates, and participation and performance across academic subjects. Results show that identifiable ethno-cultural subgroups of ESL students navigate widely varying academic trajectories. English proficiency and gender differences also affect achievement, more so in already under-achieving ethno-cultural groups. Later ages of entry generally prove advantageous for some groups in mathematics and the sciences but predict diminished outcomes in the humanities for all groups. Socio-economic effects only partially account for differences among ethno-cultural groups. School composition also has minimal effect. Most ethno-cultural groups have higher academic participation rates but lower performance scores than NESs. ESL graduation rates are more stable across socio-economic strata than NES graduation rates. The need to disaggregate data for research and decision-making, and to target support toward under-performing student groups is discussed. While ESL students perform well in aggregate, lower outcomes of identifiable subgroups are masked. The study concludes with a call for more refined data, and for further methodologically advanced research.

Thesis (Ed.D.)--University of Tulsa, 1978. / Bibliography: l. 39-41.