About this paper

Appears in:
Pages: 1231-1238
Publication year: 2011
ISBN: 978-84-615-3324-4
ISSN: 2340-1095

Conference name: 4th International Conference of Education, Research and Innovation
Dates: 14-16 November, 2011
Location: Madrid, Spain

NEW METHODS FOR STUDENT LEARNING ASSESSMENT

M. El Alami1, M. Romero2, F. de Arriaga3

1Université Abdelmalek Essaadi (MOROCCO)
2Universidad Nacional de Educación a Distancia (UNED) (SPAIN)
3Polytechnic University of Madrid (SPAIN)
The precise determination of student learning has always been an important point for several purposes such as the final student evaluation, the selection of remedial tactics for correcting learning errors and for the efficiency of learning systems. The automatic obtainment of errors has usually relied on the difference between the student’s and the human expert behaviour, which is not always apparent.

The difficulty starts when the system tries to assess that difference of behaviour, mostly in the case of complex behaviours. The paper presents new methods developed not only for error determination but also for error classification between shallow and deep errors and for obtaining the most probable reasons of the error, providing that way the most suitable remedial tactics.
The methods are assembled into a cycle with the phases: error determination, initial evaluation of the error, shallow analysis, deep analysis and final evaluation, all of them carried out by means of simple graph operations, mostly by comparing the human expert model with the student’s model. The methods can be applied automatically provided the learning system can manage the student learning model (usually a genetic graph) and the human expert model or the learning domain model.
Some results of the comparison between shallow and deep analysis carried out automatically by the system and a similar analysis made by instructors using traditional methods, are given in the paper.

The results of these methods can be used to design automatically remedial tactics especially suitable for the obtained errors. Several examples of this are included.
@InProceedings{ELALAMI2011NEW,
author = {El Alami, M. and Romero, M. and de Arriaga, F.},
title = {NEW METHODS FOR STUDENT LEARNING ASSESSMENT},
series = {4th International Conference of Education, Research and Innovation},
booktitle = {ICERI2011 Proceedings},
isbn = {978-84-615-3324-4},
issn = {2340-1095},
publisher = {IATED},
location = {Madrid, Spain},
month = {14-16 November, 2011},
year = {2011},
pages = {1231-1238}}
TY - CONF
AU - M. El Alami AU - M. Romero AU - F. de Arriaga
TI - NEW METHODS FOR STUDENT LEARNING ASSESSMENT
SN - 978-84-615-3324-4/2340-1095
PY - 2011
Y1 - 14-16 November, 2011
CI - Madrid, Spain
JO - 4th International Conference of Education, Research and Innovation
JA - ICERI2011 Proceedings
SP - 1231
EP - 1238
ER -
M. El Alami, M. Romero, F. de Arriaga (2011) NEW METHODS FOR STUDENT LEARNING ASSESSMENT, ICERI2011 Proceedings, pp. 1231-1238.
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