Assigning Level in Data-Mining Exercises

There is currently much interest in ascribing outcomes to Masters (M) level programmes. It is particularly difficult to define M level outcomes in bioinformatics for students on non-specialist programmes. An approach is described that attempts to discriminate undergraduate from M level in a data-min...

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Bibliographic Details
Published in:	Bioscience education e-journal Vol. 9
Main Authors:	Hooley, Paul, Chilton, Ian J, Fincham, Daron A, Burns, Alan T, Whitehead, Michael P
Format:	Journal Article
Language:	English
Published:	Centre for Bioscience, The Higher Education Academy 01-06-2007
Subjects:	Biology Classification College Science Data Evaluation Criteria Evaluation Methods Foreign Countries Genetics Graduate Students Information Retrieval Internet Masters Programs Outcomes of Education Science Education Science Instruction Student Evaluation United Kingdom United Kingdom
Online Access:	Get more information
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Summary:	There is currently much interest in ascribing outcomes to Masters (M) level programmes. It is particularly difficult to define M level outcomes in bioinformatics for students on non-specialist programmes. An approach is described that attempts to discriminate undergraduate from M level in a data-mining exercise. Differentiation of level is based upon the taxonomic origin of a DNA sequence, the relative increase in gene complexity from lower to higher eukaryote and the initiative required to use a wider range of databases and analytical tools. (Contains 5 tables.)
ISSN:	1479-7860 1479-7860
DOI:	10.3108/beej.9.4