Using statistical models for academic program management in tertiary educational Institutions

• Main Author: Lavilles, Rabby Q.
• Format: text
• Language: English
• Published: Animo Repository 2010
• Subjects: Universities and colleges—Administration; School enrollment—Forecasting; Computer Sciences; Databases and Information Systems
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/6060; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=13171&context=etd_masteral
• Institution: De La Salle University

Projecting the number of students expected to enroll in a certain subject in higher education involves uncertainty. This study uses statistical models to project the number of students expected to enroll in a given subject. Time series forecasting models were evaluated and integrated into academic program management (APM). APM consists of 3 major modules namely advising, program management and student projection. The advising module uses the nearest to program statistics implemented through weighted arithmetic mean to model the factor used by the adviser in advising and preparation of the program of study. Student projection uses time series statistical models while the program management module creates and manages the subjects of the curriculum. The software development methodology used in developing the APM is rational unified process to takes its advantage as an iterative approach, the detailed documentation, and its principles. The data used to formulate the models are the enrollment data of Mindanao State University-Iligan Institute of Technology (MSU-IIT). Time series models of moving average, single exponential smoothing (SES) and double exponential smoothing (DES) are the statistical models used in the study. Mean Absolute Percentage Error (MAPE) is used to evaluate the fit or accuracy of the data to the models. The advising module used the weighted arithmetic mean in ranking the subjects based on the curriculum and the program of study. The program management module includes the subjects required for each program. A total of 20 programs are included in the system with their corresponding subjects in each semester and year as an initial data of APM. These programs are programs documented on the curriculum book of the university for school year 2002-2003. The result of the projections for academic year 2009-2010 is compared to the naive model used by the university. Experimental result yields less error using MAPE with about 20 % difference in favour of the time series models. The advising module yields about 57% percent similar to the actual. Reasons for this result are also identified. On student projections about 58% of subjects generated have least average MAPE using double exponential smoothing with varying alpha and beta. The remaining subjects use SES with its most appropriate alpha based on the data. The integration of the statistical tool as part of the academic program management is implemented and course request for each college can be generated from it with a capability of viewing the history of a subject as well as showing it in a graphical form.