Publication: A Forecasting model to evaluate a freshman's ability to succeed by using particular full-scaled class association rules (PFSCARs)
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Issued Date
2009
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-70449602414
Rights Holder(s)
Scopus
Bibliographic Citation
2009 International Association of Computer Science and Information Technology - Spring Conference, IACSIT-SC 2009. (2009), p.40-44
Suggested Citation
Laokietkul J., Utakrit N., Meesad P. A Forecasting model to evaluate a freshman's ability to succeed by using particular full-scaled class association rules (PFSCARs). 2009 International Association of Computer Science and Information Technology - Spring Conference, IACSIT-SC 2009. (2009), p.40-44. doi:10.1109/IACSIT-SC.2009.129 Retrieved from: https://hdl.handle.net/20.500.14740/3717
Author(s)
Abstract
This study was to create a forecasting model for evaluate freshmen's ability to succeed with using the longest rules from CARs technique as called a particular full-scaled class association rules (PFSCARs). The purposed of this study was to create a classifier tool to evaluate freshmen's ability. This study used demographic data of students in Information Technology program Chandrakasem Rajabhat University and current grade levels of students as equalized levels. The equalized levels consist of 3 classes: good, fair and poor. The result of this study that proposed that the forecasting model to evaluate freshmen quality with PFSCARs performed at a good level of performance with an accuracy rate of 79% of the students equalized model. Finally, the research discovered that the forecasting model to evaluate freshmen quality can be a guideline for academic advisors or other relevant persons to help new students, to manage an appropriated study plan and could help them to improve course or curriculum in the future as well. © 2009 IEEE.