A code-comparison of student assignments based on neural visualisation models

CSEDU 2009 - Proceedings of the 1st International Conference on Computer Supported Education

Volumn 1, Issue , 2009, Pages 47-54

  Martin, David ^a   Corchado, Emilio ^a   Marticorena, Raúl ^a  

^a UNIVERSITY OF BURGOS   (Spain)

Author keywords

Principal component analysis; Programming metrics; Project evaluation; Teaching of programming; Unsupervised learning

Indexed keywords

CODE METRICS; GAIN INSIGHT; MULTIDIMENSIONAL DATA; PROGRAMMING METRICS; PROJECT EVALUATION; REDUCTION TECHNIQUES; STUDENT ASSIGNMENTS; TEACHING OF PROGRAMMING; VISUALISATION;

COMPUTER SOFTWARE SELECTION AND EVALUATION; EDUCATION COMPUTING; PROJECT MANAGEMENT; STUDENTS; TEACHING; UNMANNED AERIAL VEHICLES (UAV); UNSUPERVISED LEARNING;

PRINCIPAL COMPONENT ANALYSIS;

EID: 67650539321     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Campwood Software. (2007). SourceMonitor Version 2.4 [Computer software]. Last accessed November 2008. Available from *http://www.campwoodsw.com
2. Corchado, E., MacDonald, D., Fyfe, C. (2004). Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit. In Data Mining and Knowledge Discovery 8(3) (pp. 203-225). (Pubitemid 39019961)
3. Corchado, E. and Fyfe, C. (2003). Connectionist Techniques for the Identification and Suppression of Interfering Underlying Factors. In International Journal of Pattern Recognition and Artificial Intelligence 17(8) (pp. 1447-1466).
4. Corchado E., Han Y., Fyfe C.,Structuring Global Responses of Local Filters Using Lateral Connections, Journal of Experimental & Theoretical Artificial Intelligence,15(4),(pp 473-487). (Pubitemid 38107845)
5. Friedman, J.H. and Tukey, J.W. (1974). A Projection Pursuit Algorithm for Exploratory Data-Analysis. In IEEE Transactions on Computers 23(9) (pp. 881-890).
6. Fyfe, C. and Corchado, E. (2002). Maximum likelihood Hebbian rules. In ESANN 2002, 10th European Symposium on Artificial Neural Networks, Proceedings (pp. 143-148).
7. Hotelling, H. (1933). Analysis of a Complex of Statistical Variables Into Principal Components. In Journal of Educational Psychology 24 (pp. 417-444).
8. Marticorena, R., Bernal, I., Rebollo, J., Lopez, C. (2008). Detection de la Copia de Practicas de Programacion con JDup. In Adas de las XIV Jornadas de Ensehanza Universitaria de Informdtica, Jenui 2008 (pp. 579- 586).
9. Oja, E. (1989). Neural networks, principal components, and subspaces. In International Journal of Neural Systems 1, (pp. 61-68).
10. Pearson K.,(1901),On lines and planes of closest fit to systems of points in space, Philosophical Magazine,2(16)(pp.559-572).