The Relationship Between Selected Variables and the Prediction of College Success PDF Download
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Author: George Franklin Grimm
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 190
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Book Description
Author: George Franklin Grimm
Publisher:
ISBN:
Category : Academic achievement
Languages : en
Pages : 190
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Book Description
Author: Anthony K. Kallingal
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 322
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Book Description
Author: David Herbert Fretwell
Publisher:
ISBN:
Category : Latin American students
Languages : en
Pages : 222
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Book Description
Purpose of the Study The purposes of this study were to (1) identify the educational and socioeconomic characteristics of Latin American students who have graduated from the California State College system, (2) to identify those characteristics which significantly affect academic success, utilization of training and return home to Latin America after graduation and (3) to develop mathematical models for prediction of academic success, utilization of training and return home. Procedures A total of 146 students were included in the sample for this study. These students had graduated from the California State College system in the five years prior to August 30, 1971. Socio-economic and educational characteristics were obtained through a search of college records, interviews with faculty and staff and the mailing of a questionnaire to the students included in the sample. Academic success was defined by grade point average and utilization of training was measured in percentage by the amount of college training used by a graduate in his present job. A correlation analysis was completed to determine the relationship among the three dependent variables academic success, utilization of training and return home as well as the relationship between each of the dependent variables and the independent variables included in the study, Stepwise multiple linear regression analyses identified those characteristics contributing most significantly to academic success and utilization of training. These analyses were also used to develop prediction equations for academic success and utilization of training. Discriminant analyses were completed to test the null hypothesis that there was no significant difference between the returning and non-returning group of students and to construct a prediction model for return or non-return to native country. Findings 1. The correlation analysis indicated the following: (a) There was no significant relationship among the three dependent variables: academic success, utilization of training and return home. (b) Six independent variables had a significant relationship with academic success. One, bachelor's degree, was negatively correlated while the remainder, graduate degree training, average English grade, prior college in native country, education major and scholarship financing, were positively correlated. (c) No independent variables were identified that had a significant relationship with the dependent variable utilization of training. (d) Two independent variables, contact with Latin America while training and vacations spent in Latin America were positively correlated with the dependent variable return home. It was emphasized that these were simple linear relationships that did not indicate' causality. 2. The results of the linear regression analysis related to academic success indicated: (a) Nine variables were significantly related to academic success. Four of these variables had a positive relationship: average English grade, education major, "other" major (including majors other than agriculture, business, engineering and education) and vacations spent in Latin America. Five of these variables had a negative relationship: return home, California State Polytechnic College - San Luis Obispo, California State College - Long Beach, time in the U.S. before graduation, and F visa. (b) A prediction equation was constructed for academic success, The equation constructed included the variables: San Francisco State College, California State College - Long Beach, California, State Polytechnic College - San Luis Obispo, age, education, major and "other" major. 3. The results of the linear regression analysis related to utilization of training indicated: (a) Twelve variables were significantly related to utilization of training. Six of these had a positive relationship: bachelor's degree, engineering major, father's occupation similar to student's field of study, contact with Latin America while training, Latin America high school training and present employment at a higher level. Six of these variables had a negative relationship: age, marriage during training, family financing and follow-up contact after graduation. (b) A prediction equation was constructed for utilization of training. The equation constructed included the variables: Fresno State College, prior employment in field of training, father's occupation similar and orientation program available. 4. The null hypothesis, stating that there was no significant difference between the returning and non-returning groups of students, could not be rejected on the basis of the discriminant analyses completed. Therefore a prediction model for return could not be constructed.
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 1236
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Author: Claudia Elizabeth Plog
Publisher:
ISBN:
Category : Computer programming
Languages : en
Pages : 340
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Book Description
Author: William E. Stock
Publisher:
ISBN:
Category : Prediction of scholastic success
Languages : en
Pages : 62
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Book Description
Author: Ann Morgan Zimmerer
Publisher:
ISBN:
Category :
Languages : en
Pages : 324
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Book Description
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 1560
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Book Description
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 816
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Book Description
Author: Michael G. Rumsey
Publisher: Psychology Press
ISBN: 1134788134
Category : Psychology
Languages : en
Pages : 555
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Book Description
Bringing together several key elements needed to identify the most promising themes for future research in selection and classification, this book's underlying aim is to improve job performance by selecting the right persons and matching them most effectively with the right jobs. An emphasis is placed on current, innovative research approaches which in some cases depart substantially from traditional approaches. The contributors -- consisting of professionals in measurement, personnel research, and applied and military psychology -- discuss where the quantum advances of the last decade should take us further. Comprehensive coverage of the selection and classification domain is provided, including a broad range of topics in each of the following areas: performance conceptualization and measurement, individual differences, and selection and classification decision models. The presentations in each of these areas are integrated into a set of coherent themes. This integration was the product of structured group discussions which also resulted in a further evolution of some of the ideas presented.
