Senior Lecturer in Psychology at Southampton Solent University, UK.
My main research interests are in cognitive psychology and neuroscience, visual short-term memory, object feature binding (the binding problem), visual perception, and research methods (experimental design in particular). My current research interests extend to understanding cognitive processes used in expert problem solving in the software engineering domain, the detection of on-line deception, cognitive aspects of the implementation and acceptance of biometrics and the psychology of art.
Analogical or case-based reasoning (CBR) is a knowledge management technology based upon problem-solving using episodic memory and retrieval by similarity. It has been used for many problems including support for software project management in areas such as prediction and lessons learned. Results from using CBR are varied, but it is unclear why this should be. Consequently we canot predict a priori when CBR will aid problem solving. Hence, the aim of this project is to empirically investigate the cognitive processes of professionals using CBR tools for problem-solving (presently almost completely unexplored) in order to develop more effective CBR support for software engineering problems. Working with EDS, UK to generate realistic problems drawn from the area of project effort prediction, we are conducting empirical studies with professional participants using our existing CBR shell, archANGEL. We are using multiple techniques including interviews and think-aloud protocols based on a Grounded Theory approach. This project will lead to (i) improved understanding and therefore utilization of analogy-based project management tools (CBR) and (ii) recommendations for more effective future CBR tools. This research is important because CBR is an increasingly used technology, yet not always effectively deployed, because we have little understanding of how professionals solve problems using analogy-based tools.
Curriculum Fellowship (SSU) 2008-2009 Using meta-reflection to enhance performance
An investigation into reflective practice using meta-reflection and software technology. Much evidence supports the use of reflective practice for personal development, yet it is not commonly used as a learning tool with students. More typically, reflective writing is assessed as a stand-alone piece of work. In such cases, the objective is frequently only grade. The proposed project would actively promote the use of reflections to improve performance by means of using technology to record, store and retrieve them. These individual reflections will be used to populate a database so that ultimately, with permission, each individual's reflections can be accessed by others via the database. Thus these reflections will become a learning tool for students. Using technology facilitates classification and retrieval and reduces the problems associated with human memory.
The Curriculum Fellowship project will be discussed at the next meeting of the HEA Health Sciences and Practice, Reflective Practice: SIG, 'Linking teaching and research through reflexive methodologies' at Kings College, London on 9th February, 2009.
Completed:Mair, C., Shepperd, M. and Stephens, M. (2008) How Cognitive Psychology Can Help Analogy-Based Project Estimation, Accepted for the 19th Annual UK Software Metrics Association (UKSMA) Conference, London, 16th October 2008.
Taylor, J. and Mair, C. (2008) Qualitative Methods for Classifying and Detecting Online Identity Deception. To be published in the Proceedings of Computer/Human Interaction, (CHI Õ08), Florence, Italy, 5th - 10th April 2008.
Song, Q., Shepperd, M., & Mair, C. (2006) Software Defect Association Mining and Defect Correction Effort Prediction. IEEE Transactions on Software Engineering, 32(2), 69-82.
Mair, C. and Shepperd, M.J. (2006) Looking at Comparisons of Regression and Analogy-based Software Project Cost Prediction, Proceedings of International Conference on Software Engineering Research and Practice (SERPÕ06), Las Vegas, 26th - 29th June 2006.
Mair, C., Shepperd, M.J. and Forselius, P. (2006) An Empirical Analysis of Software Productivity, Proceedings of 3rd Software Measurement European Forum (SMEF 2006), 10th - 12th May, Rome, 2006.
Mair, C., & Shepperd, M. (2005) The Consistency of Empirical Comparisons of Regression and Analogy-based Software Project Cost PredictioN. Paper presented at the 4th Intl. Symp. on Empirical Softw. Eng. (ISESE), Noosa Heads, Australia.
Mair, C., Shepperd, M., & Jorgensen, M. (2005) An Analysis of Data Sets Used to Train and Validate Cost Prediction Systems. Paper presented at the PROMISE 2005, St Louis, MI.
Song, Q., Shepperd, M., & Mair, C. (2005) Using Grey Relational Analysis to Predict Software Effort with Small Data Sets. Paper presented at the 11th IEEE Intl. Softw. Metrics Symp. (Metrics05), Como, Italy, September 2005.
Mair, C. & Shepperd, M. (2004) Making Software Cost Data Available for Meta-Analysis. Proceedings of the 8th International Conference on Empirical Assessment in Software Engineering (EASE, 2004), Edinburgh, Scotland, UK, 20-22 May 2004, 37-45.
Mair, C., Shepperd, M., Kirsopp, C., Premraj, R. & Heathcote, D. (2004) Understanding Object Feature Binding through Experimentation as a Precursor to Modelling. Proceedings of the 8th Neural Computation and Psychology Workshop, Connectionist Models of Cognition and Perception II. H. Bowman & C. Labiouise (Eds) Progress in Neural Processing 15. World Scientific, 295-305.
Premraj, R., Twala, B. & Mair, C . (2004) Productivity of Software Projects by Business Sector: An Empirical Analysis of Trends. Proceedings of the 10th International Software Metrics Symposium, Chicago, USA, 14-18 September 2004.
Mair, C. (2003) Towards a Further Understanding of Object Feature Binding. Proceedings of the 7th International Conference on Cognitive and Neural Systems (ICCNS), Boston, USA, May 2003.
Mair, C., Kadoda, G., Lefley, M., Phalp, K., Schofield, C., Shepperd, M. & Webster, S. (2000) An Investigation of Machine Learning Based Prediction Systems, Journal of Systems and Software, 53, 23-29.
Mair, C. & Shepperd, M. (1999) An Investigation of Rule Induction Based Prediction Systems. Proceedings of the 21st International Conference on Software Engineering (ICSE), Los Angeles, USA, May 1999.
Bennett, K., Burd, E., Kemerer, C., Lehman, M., Lee, M., Madachy, R., Mair, C., Sjoberg, D., & Slaughter, S. (1999) Empirical Studies of Evolving Systems. Empirical Software Engineering: an international journal. Vol. 4 (4), December 1999.
Contact:Last updated: 9th January 2009