%0 Journal Article
%T Predicting performance of first year engineering students and the importance of assessment tools therein
%A Stephen Lee
%A Martin Harrison
%A Godfrey Pell
%A Carol Robinson
%J Engineering Education
%D 2008
%I 
%X In recent years, the increase in the number of people entering university has contributed to a greater variability in the background of those beginning programmes. Consequently, it has become even more important to understand a student¡¯s prior knowledge of a given subject. Two main reasons for this are to produce a suitable first year curriculum and to ascertain whether a student would benefit from additional support. Therefore, in order that any necessary steps can be taken to improve a student¡¯s performance, the ultimate goal would be the ability to predict future performance.A continuing change in students¡¯ prior mathematics (and mechanics) knowledge is being seen in engineering, a subject that requires a significant amount of mathematics knowledge. This paper describes statistical regression models used for predicting students¡¯ first year performance. Results from these models highlight that a mathematics diagnostic test is not only useful for gaining information on a student¡¯s prior knowledge but is also one of the best predictors of future performance. In the models, it was also found that students¡¯ marks could be improved by seeking help in the university¡¯s mathematics learning support centre. Tools and methodologies (e.g. surveys and diagnostic tests) suitable for obtaining data used in the regression models are also discussed.
%K engineering mathematics
%K mathematics diagnostic testing
%U http://www.engsc.ac.uk/journal/index.php/ee/article/viewFile/75/115