This experiment was performed to assess the interactive effect of incentive strength and task difficulty using measures of behavioral intensity. Subjects faced an easy or difficult task in order to avoid having to listen to aversive radio static. Half of the subjects were to hear a loud noise and half were to hear a soft noise. Prior to task commencement, five measures of behavioral intensity were taken—two timing measures, two counting measures, and one measure involving the amount of error in filling in scantron bubbles. Results showed that one timing measure and three mood adjectives followed the predicted pattern, but not in a statistically significant fashion. The patterns indicated the energization remained low and uniform when subjects heard soft noise, but increased as a function of task difficulty when subjects were exposed to a loud noise. Results are discussed in terms of Brehn’s energization theory of motivation. / Department of Psychological Science

There is no abstract available for this dissertation.

The purpose of the study was to examine the relationship between credit hour load and academic achievement of selected undergraduate college students. The study was designed to determine the relationship between credit hour load and grades earned by undergraduate college students in selected required courses and overall scholastic ratio during the specified quarters. Specifically, the study was designed to determine the additional contribution of the independent variable credit hour load to the overall relationship between academic achievement of the students in selected required courses, as measured by course grade, and overall scholastic ratio, and the independent variable set consisting of sex and ability as measured by SAT Verbal and SAT Quantitative scores.The population included all Ball State University undergraduate secondary education students enrolled during the academic years 1976/77, 1977/78 and 1978/79. The sample consisted of 1,007 students identified as having enrolled in and completed credit hour loads of twelve or more hours for at least one quarter. Students selected for inclusion had enrolled in either of two required secondary education courses, EDSEC 299 or EDSEC 420. The study was designed to control for sex differences and variations in ability.To accomplish specific purposes of the study, four null hypotheses were tested using multiple regression procedures. The Statistical Package for the Social Sciences (SFSS) program was used in conducting the analyses. Two regression models were used to determine the statistical significance of the addition of the independent variable, credit hour load, to a set of predictors consisting of sex, SAT Verbal and SAT Quantitative scores. In the first model only sex, SAT Verbal and SAT Quantitative scores were used as predictors of the dependent variable (reduced model). The second model involved the addition of the independent variable, credit hour lead, to the predictor set. The difference between the obtained squared multiple correlation (R2) was then computed and tested for statistical significance at the .05 level using an F statistic.The findings regarding statistical significance of the contribution provided by credit hour load to a relationship between the dependent variable and the independent variable set were:1. The level of prediction of course grades in EDSEC 299 provided by sex of student and ability data was not improved by the addition of credit hour load data.2. The level of prediction of scholastic ratio for students enrolled in EDSEC 299 provided by sex of student and ability data was improved by the addition of credit hour load data. The degree of improvement however, was so slight as to be of little importance in idiographic predictions.3. The level of prediction of course grades in EDSEC 420 provided by sex of student and ability data was improved by the addition of credit hour load data. The degree of improvement however, was so slight as to be of little practical importance in idiographic predictions.4. The level of prediction of scholastics ratio for students enrolled in EDSEC 420 provided by sex of student and ability data was not improved by the addition of credit hour load data.

The purpose of this study was to investigate the degree of concurrence between teachers' judgments of the academic achievement of students and the results of standardized,norm-referenced achievement tests. Although this issue had been addressed before, results reported in the literature lacked a sensitivity to the informational needs of educational policy makers and were obfuscated by significant differences in research design and analytical techniques. This study attempted to address the potential moderating effect of teachers' pre-established notions of students' knowledge, academic subject area, grade level, and student gender on the agreement level between teachers' judgment of student achievement and test results, while focusing on the ever increasing use of test scores to make decisions regarding student readiness for promotion/graduation and overall school accountability.Approximately 670 teachers were asked to rate their students as "not ready to succeed at the next grade level without remedial assistance" (non-masters) or "ready to succeed without additional instruction or intervention" (masters). Ratings were obtained in both English/language arts and mathematics for 15,935 students in grades 1, 2, 3, 6, and 8. The sample utilized was representative of the demographics of the state of Indiana. While appropriate statistical tests of significance were performed when appropriate, this study focused on effect size as the final determinant of "educational significance."Analyses revealed no practical reason to believe that teachers' judgments were influenced by their initial ratings of students as masters or non-masters, student gender, grade level, or subject matter. On the average, teachers' mastery/non-mastery ratings were found to agree with "cutscores" established through discriminant analysis in about 78% of the cases. These results were seen as encouraging, in that test results could be used to support teacher judgment, which seemed unaffected by moderating variables, while not offering information completely redundant with pre-existing teacher knowledge of student achievement. / Department of Educational Psychology

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

Rothbaum, Weisz, and Snyder's (1982) dual-process model of control proposed that in addition to attempts to change one's environment (primary control, PC) or psychologically adjust to one's circumstances (secondary control, SC), the higher-order capacity to alternate between these processes in congruence with performance (optimization) served to foster development in achievement settings. The present five-phase longitudinal study conducted over an academic year explored how college students (n = 568) shift between PC and SC over time in response to actual performance feedback, as well as the differential effectiveness of congruent emphasis shifts for development based on the perceived ability to shift in a strategic manner. Dependent measures included academic achievement (course test scores), motivation (achievement orientation, perceived success and value, expectations), emotions (enjoyment, anxiety, boredom), health status (global health, illness symptoms), and overall adjustment (perceived stress, self-esteem, depression). Hypotheses were evaluated using phase-specific and cross-lagged structural equation models assessing moderation effects for perceived congruence ability. Results showed that students shift toward PC after success and toward SC following failure, and suggest an elaborated theoretical model of how PC and SC contribute to beliefs and behaviour involving strategic and congruent emphasis shifts. These findings also demonstrate that some individuals better recognize when this behaviour is most effective for their performance and well-being and strategically make congruent emphasis shifts to improve their subsequent development. In sum, this study highlights the benefits of one's ability to make strategic emphasis shifts between PC and SC in an academic achievement setting, and provides empirical support for this effective yet relatively unexplored facet of Rothbaum et al.'s model.