Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University

Many factors have an influence on the success of undergraduate students particularly in engineering programs. Some students have to drop out as a result of obtaining very poor GPA (grade point average) and/or GPAX (accumulated grade point average) after only their first year of studying. It would be...

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Main Author: Wattanapong KURDTHONGMEE
Format: Article
Language:English
Published: Walailak University 2011-11-01
Series:Walailak Journal of Science and Technology
Subjects:
Online Access:http://wjst.wu.ac.th/index.php/wjst/article/view/117
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author Wattanapong KURDTHONGMEE
author_facet Wattanapong KURDTHONGMEE
author_sort Wattanapong KURDTHONGMEE
collection DOAJ
description Many factors have an influence on the success of undergraduate students particularly in engineering programs. Some students have to drop out as a result of obtaining very poor GPA (grade point average) and/or GPAX (accumulated grade point average) after only their first year of studying. It would be helpful for students if they know how their current GPA/GPAX could be improved in order to successfully graduate. In addition, what would be the expected outcome of their study, if their current GPAs of compulsory subjects are not fairly good? In this paper, the Self Organizing Map (SOM) neural network is utilized as a tool to cluster engineering student data into different groups by means of their study results. The results are then used to produce the weight maps. The maps reflect the correlation between GPA/GPAX of the compulsory subjects and the educational status of students. The result from the SOM with some adaptations to its matching phase is also used to create a predictor which is capable of producing a fairly high degree of correctness. The meaningful results are intended to be used as a guideline for students to prepare and improve themselves. In addition, it might be useful for student advisors and counselors to give appropriate advice to students whose GPAX are critically low. This can be accomplished by advising students to register less or withdraw some subjects in order to leverage their GPAX. In addition, some students should be advised to change their field of study if they perform fairly poorly in all compulsory subjects. The approach utilized in this paper is a novel one with respect to this application domain.
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spelling doaj.art-c03b676da3254d2d871e7aa26266bacb2022-12-22T03:29:28ZengWalailak UniversityWalailak Journal of Science and Technology1686-39332228-835X2011-11-015110.2004/wjst.v5i1.117110Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak UniversityWattanapong KURDTHONGMEE0School of Engineering and Resources Management, Walailak University, Nakhon Si Thammarat 80161Many factors have an influence on the success of undergraduate students particularly in engineering programs. Some students have to drop out as a result of obtaining very poor GPA (grade point average) and/or GPAX (accumulated grade point average) after only their first year of studying. It would be helpful for students if they know how their current GPA/GPAX could be improved in order to successfully graduate. In addition, what would be the expected outcome of their study, if their current GPAs of compulsory subjects are not fairly good? In this paper, the Self Organizing Map (SOM) neural network is utilized as a tool to cluster engineering student data into different groups by means of their study results. The results are then used to produce the weight maps. The maps reflect the correlation between GPA/GPAX of the compulsory subjects and the educational status of students. The result from the SOM with some adaptations to its matching phase is also used to create a predictor which is capable of producing a fairly high degree of correctness. The meaningful results are intended to be used as a guideline for students to prepare and improve themselves. In addition, it might be useful for student advisors and counselors to give appropriate advice to students whose GPAX are critically low. This can be accomplished by advising students to register less or withdraw some subjects in order to leverage their GPAX. In addition, some students should be advised to change their field of study if they perform fairly poorly in all compulsory subjects. The approach utilized in this paper is a novel one with respect to this application domain.http://wjst.wu.ac.th/index.php/wjst/article/view/117Self organizing mapengineering educationeducation prediction
spellingShingle Wattanapong KURDTHONGMEE
Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
Walailak Journal of Science and Technology
Self organizing map
engineering education
education prediction
title Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
title_full Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
title_fullStr Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
title_full_unstemmed Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
title_short Utilization of a Self Organizing Map as a Tool to Study and Predict the Success of Engineering Students at Walailak University
title_sort utilization of a self organizing map as a tool to study and predict the success of engineering students at walailak university
topic Self organizing map
engineering education
education prediction
url http://wjst.wu.ac.th/index.php/wjst/article/view/117
work_keys_str_mv AT wattanapongkurdthongmee utilizationofaselforganizingmapasatooltostudyandpredictthesuccessofengineeringstudentsatwalailakuniversity