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Higgins, Colin

Colin Higgins
Associate Professor - School of Computer Science
Address: 
Room C10b Computer Science Jubilee Campus Wollaton Road Nottingham NG8 1BB UK
Email: 
cah@cs.nott.ac.uk
Research interests: 

The Development of Courseware for Teaching

Dr Higgins is head of the Learning Technology Research Group which has been concerned with the development of the CourseMarker (formerly CEILIDH) system.

Metrics for Object-Oriented Designs and Programs

The main aim of this project is to design, implement and empirically evaluate a metric suite capable of differentiating levels of quality amongst object-oriented designs. The building of a quality model would encourage metric development and permit the comparative analysis of different object-oriented designs. Metrics for Java Programs This project is similar to the metrics for object-oriented designs; in this case however the aim is to measure the quality of logic programs written in the Java language. The results would be used, amongst other things, for the automatic assessment of student projects under the University of Nottingham CourseMarker system.

Metrics for Logic Programs

This project is similar to the metrics for object-oriented designs; in this case however the aim is to measure the quality of logic programs written in the Prolog language. The results would be used, amongst other things, for the automatic assessment of student projects under the University of Nottingham CourseMarker system.

Handwriting Recognition based on Human Reading Models

Historically, cursive script recognition systems have been modelled on the human writing process. A new system is under development based on human reading models. The paradigm used to realise the model is an object-oriented blackboard system written in C++. Off-Line Cursive Script Recognition Work is in progress on the recognition of handwriting from scanned images. There are many application areas where this is appropriate, from bank cheques recognition to forms filling. Methods invented during the on-line handwriting recognition project, that are appropriate to off-line recognition, will be used. These include feature moment vectors whose parameters are determined from a large data set using genetic algorithms.

Publications: 
HIGGINS, C.A., GRAY, G., SYMEONIDIS, P. and TSINTSIFAS, A., 2005. Automated assessment and experiences of teaching programming Journal on Educational Resources in Computing (JERIC). 5(3), Article 5

ALMA'ADEED, S., HIGGINS, C. and ELLIMAN, D., 2004. Off-line recognition of handwritten Arabic words using multiple hidden Markov models Knowledge-Based Systems. 17(2-4), 75-79

HIGGINS, C., HEGAZY, T., SYMEONIDIS, P. and TSINTSIFAS, A., 2003. The CourseMarker CBA system: improvements over Ceilidh Education and Information Technologies. 8(3), 287-304

AL-MA’ADEED, S., ELLIMAN, D. and HIGGINS, C., 2004. A data-base for Arabic handwritten text recognition research International Arab Journal of Information Technology. 1(1), 118-123