DocumentCode :
3637662
Title :
Evaluating Student Response Driven Feedback in a Programming Course
Author :
José Luis Fernández Alemán;Dominic Palmer-Brown;Chrisina Draganova
Author_Institution :
Fac. of Comput. Sci., Univ. of Murcia, Murcia, Spain
fYear :
2010
Firstpage :
279
Lastpage :
283
Abstract :
This paper presents an experience of generating diagnostic feedback for guided learning in an introductory programming course. An on-line Multiple Choice Questions (MCQs) system is integrated with a neural network based data analysis. Some empirical results about how students use the system in a CS1 course are presented. Research with an experimental group of 61 students suggests that the feedback addresses the level of knowledge of the individual and guides them towards a greater understanding of particular concepts. Moreover the approach proposed promotes the students´ interest and produces statistically significant differences in the scores between the experimental group and control group.
Keywords :
"Artificial neural networks","Electronic learning","Training","Programming profession","Instruments"
Publisher :
ieee
Conference_Titel :
Advanced Learning Technologies (ICALT), 2010 IEEE 10th International Conference on
Print_ISBN :
978-1-4244-7144-7
Type :
conf
DOI :
10.1109/ICALT.2010.82
Filename :
5571312
Link To Document :
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