Shamsuddin, Shukri and Ismail, Noor Izah and Wan Hussin, Wan Haslina
(2007)
Predicting students' performance through techniques in study skills : a multivariate discriminant analysis approach / Shukri Shamsuddin, Noor Izah Ismail and Wan Haslina Wan Hussin.
Social and Management Research Journal (SMRJ), 4 (1).
pp. 109-118.
ISSN 1675-7017
Official URL: https://smrj.uitm.edu.my/
Abstract
This paper investigates some of the study skills techniques practised by students in UiTM Johor campus. The multivariate discriminant analysis approach was used to analyse the data. The discussion focuses on to what extent these study skills techniques could be used to predict the academic performance ofstudents. This paper also examines whether there is a significant difference in study
skills techniques practised by male and female students, by students of different secondary school backgrounds, and by students of different academic performances. It is hoped that this paper would shed some light on the effectiveness of the study skills program introduced to part one students upon entry into UiTM Johor.
Metadata
Item Type: | Article |
---|---|
Creators: | Creators Email / ID Num. Shamsuddin, Shukri shuk927@johor.uitm.edu.my Ismail, Noor Izah UNSPECIFIED Wan Hussin, Wan Haslina UNSPECIFIED |
Subjects: | H Social Sciences > HF Commerce > Personnel management. Employment management > Performance standards L Education > LB Theory and practice of education > Higher Education > Graduate education > Graduate students > Malaysia L Education > LG Individual institutions > Asia > Malaysia > Universiti Teknologi MARA > Johor |
Divisions: | |
Journal or Publication Title: | Social and Management Research Journal (SMRJ) |
UiTM Journal Collections: | UiTM Journal > Social and Management Research Journal (SMRJ) |
ISSN: | 1675-7017 |
Volume: | 4 |
Number: | 1 |
Page Range: | pp. 109-118 |
Keywords: | Skills techniques, student academic performance, Universiti Teknologi MARA, UiTM Johor, |
Date: | 2007 |
URI: | https://ir.uitm.edu.my/id/eprint/13024 |
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