About this paper

Appears in:
Pages: 3069-3078
Publication year: 2014
ISBN: 978-84-617-0557-3
ISSN: 2340-1117

Conference name: 6th International Conference on Education and New Learning Technologies
Dates: 7-9 July, 2014
Location: Barcelona, Spain

APPLICATION OF NEURAL NETWORKS FOR REALISTICALLY OPTIMAL ANALYSIS AND EVALUATION OF SOFTWARE LEARNING PACKAGES' PERFORMANCE

H.M.H. Mustafa

Al-Baha University (SAUDI ARABIA) / Banha University (EGYPT)
This paper addresses a challenging problem concerned basically with realistic optimal computer-based educational simulations. More specifically, it searches for an optimally designed computational tool(s), such as software learning package(s), applied to teaching a specified curriculum in classroom. Herein, quantitative evaluation as well as statistical analysis of the learning environment nature have been considered for optimal learning systems' performance. Recently, this learning issue has gained significance due to the integration of information technology into educational/instructional practical operations [1].
Accordingly, two learning parameters -that are candidates to measure effectiveness and efficiency of such packages- are elected to support the optimal selection of a relevant software learning package SWLP. These parameters -after establishing how to measure results and performance of the learning process- are: the output learning level, which evaluates obtained educational achievement, and time response considered in fulfillment of a pre-assigned educational achievement/learning level. Artificial Neural Networks (ANNs) modeling is adopted for the simulation of a realistic practical learning processes’ performance, as well as software learning packages' evaluation and testing. Additionally, herein an Artificial Neural Network (ANN) model is presented. Which is based on guided-error correction learning (learning with a teacher). Therefore, it is used as a realistic simulating tool aiming at quantitative/statistical evaluation of the learning process under investigation. Consequently, presented ANN model considered both students' individual differences as well as SWLPs employed as virtual teacher in a computer course curriculum. Two learning parameters are considered during the running of the presented model. Namely, learning convergence (response) time, and secondly, the achievement (output) learning level (amplitude) response. It is worthy to note that obtained simulation results were well supported by the case study results published recently [1][2][3].

References:
[1] Mustafa , H.M. , Al-Hamadi ,A., and Kortam , M. H. (2010) "On Assessment of Teaching A Mathematical Topic Using Neural Networks Models ( with a case study) ", conference proceeding of Technology and its Integration into Mathematics Education Time 2010 , held in Malaga , Spain , on July 6th-10th, 2010.
[2] Edwin K. W. Cheung "A qualitative and statistical analysis of students' perceptions in Internet learning” Journal of Systemics, Cybernetics and Informatics Volume 1 - Number 2,2006, Pages: 13-21.
[3] Mustafa , H.M. , et.al “Quantified Evaluation of Virtual Learning Creativity Improvement by Using Computer Aided Learning Processes (Neural Networks Approach)".Published at ICERI2013, the 6th International Conference of Education, Research and Innovation held in Seville (Spain), on the 18th, 19th and 20th of November, 2013, pp. 3849 - 3859.
@InProceedings{MUSTAFA2014APP,
author = {Mustafa, H.M.H.},
title = {APPLICATION OF NEURAL NETWORKS FOR REALISTICALLY OPTIMAL ANALYSIS AND EVALUATION OF SOFTWARE LEARNING PACKAGES' PERFORMANCE},
series = {6th International Conference on Education and New Learning Technologies},
booktitle = {EDULEARN14 Proceedings},
isbn = {978-84-617-0557-3},
issn = {2340-1117},
publisher = {IATED},
location = {Barcelona, Spain},
month = {7-9 July, 2014},
year = {2014},
pages = {3069-3078}}
TY - CONF
AU - H.M.H. Mustafa
TI - APPLICATION OF NEURAL NETWORKS FOR REALISTICALLY OPTIMAL ANALYSIS AND EVALUATION OF SOFTWARE LEARNING PACKAGES' PERFORMANCE
SN - 978-84-617-0557-3/2340-1117
PY - 2014
Y1 - 7-9 July, 2014
CI - Barcelona, Spain
JO - 6th International Conference on Education and New Learning Technologies
JA - EDULEARN14 Proceedings
SP - 3069
EP - 3078
ER -
H.M.H. Mustafa (2014) APPLICATION OF NEURAL NETWORKS FOR REALISTICALLY OPTIMAL ANALYSIS AND EVALUATION OF SOFTWARE LEARNING PACKAGES' PERFORMANCE, EDULEARN14 Proceedings, pp. 3069-3078.
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