DocumentCode
1852227
Title
Student noncompletion factors and targeted resource allocation: a predictive model
Author
Laing, Chris ; Robinson, Alan ; King, Graham
Author_Institution
Technol. Fac., Southampton Inst., UK
Volume
2
fYear
2001
fDate
2001
Abstract
As an increasing higher priority, United Kingdom higher education institutions are introducing strategies to reduce student noncompletion rates. However, current measures of noncompletion make no allowance for the fluid characteristics of the higher education environment. Attention must be given to the characteristics of such an environment, and how this environment influences noncompletion. It is from this perspective that a preliminary model of the teaching and learning environment has been developed. It is proposed that the underlying nature of such an environment can be captured using a grounded theory methodology and implemented as a Bayesian vector auto regression model
Keywords
Bayes methods; education; teaching; Bayesian vector auto regression model; United Kingdom; grounded theory methodology; higher education institutions; learning environment; predictive model; student noncompletion; targeted resource allocation; teaching environment; Bayesian methods; Councils; Current measurement; Econometrics; Economic forecasting; Education; Educational technology; Government; Predictive models; Resource management;
fLanguage
English
Publisher
ieee
Conference_Titel
Frontiers in Education Conference, 2001. 31st Annual
Conference_Location
Reno, NV
ISSN
0190-5848
Print_ISBN
0-7803-6669-7
Type
conf
DOI
10.1109/FIE.2001.963661
Filename
963661
Link To Document