%0 Journal Article
%T Assistance of diagnostic assessment of practical work in electronic with machine learning
%A Mariam Tanana
%A Nicolas Delestre
%J STICEF
%D 2010
%I 
%X In some domain, the know-how is essential for a good learning. But its assessment is often difficult especially with a great number of students. In this paper, we show that machine learning can help teachers to evaluate students' practical works in the domain of electronic. First of all, we will introduce our application domain and the methodological way the students follow to solve their problems. Then, we will present experimental data used to evaluate our methods. After some reminders about machine learning algorithms, and how to choose one in our context, we will propose a similarity measure used as summative assessment. Finally, we will show that the k-nn algorithm with learning database can be used to make diagnostic assessment.
%K Diagnostic assessment
%K similarity measure between graphs
%K machine learning
%K electronic schema
%U http://sticef.univ-lemans.fr/num/vol2010/05-tanana/sticef_2010_tanana_05p.html