DocumentCode :
2914409
Title :
Nontraditional student withdrawal: a grounded Bayesian Vector Auto Regression framework
Author :
Laing, Chris ; Robinson, Alan
Author_Institution :
Technol. Fac., Southampton Inst., UK
Volume :
3
fYear :
2002
fDate :
6-9 Nov. 2002
Abstract :
Previously it has been proposed that explanations of nontraditional withdrawal might be defined by the underlying characteristics of the teaching and learning environment, especially on how a student´s perceptions and expectations of that environment impact on their decision to withdraw. An ethnographic study using grounded theory was used to capture these underlying characteristics. The results of that study provided an explanation of the teaching and learning environment as a function of student beliefs, staff-student actions, and institutional intentions. A follow-up longitudinal study is now being undertaken. The aim of this study is, (a) refine the grounded analysis, and (b) model the grounded teaching and learning environment within a Bayesian vector auto regression (BVAR) framework.
Keywords :
Bayes methods; autoregressive processes; education; teaching; Bayesian vector auto regression framework; ethnographic study; follow-up longitudinal study; grounded analysis; grounded theory; institutional intentions; learning environment; nontraditional student withdrawal; staff-student actions; student beliefs; student´s expectations; student´s perceptions; teaching environment; Bayesian methods; Continuing education; Educational technology; Humans; Paper technology; Predictive models; Reactive power; Resource management; Stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Education, 2002. FIE 2002. 32nd Annual
ISSN :
0190-5848
Print_ISBN :
0-7803-7444-4
Type :
conf
DOI :
10.1109/FIE.2002.1158652
Filename :
1158652
Link To Document :
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