Admission criteria for post graduate MBL students

Abstract

There is a great need for qualified MBL and MBA graduates in South Africa to support and maintain the current growth rate that the economy is experiencing. Diligent effort is required to ensure that the locally acquired MBA/MBL qualifications remain on par with international qualifications. As an initial step to ensure high standards, the Council for Higher Education (CHE) did accreditation evaluations and only 18 MBA courses are now accredited. Admission criteria for the MBA/MBL is one of the minimum standards being assessed as part of the accreditation process conducted by the CHE. To be effective some of the aims of the admissions process at the UNISA SBL should be to: • Determine as accurately as possible, which students are capable to complete the MBL qualification successfully; (this has two implications, not denying any students who could have completed the course, and not admitting students who will not be able to complete the course). • Ensure that a culturally diverse and representative student body is admitted. • Do the above mentioned by using a practical process that is as financially and time efficient as possible. This research study focuses on the admissions criteria for MBL students at UNISA. The objectives of the study are: • Understanding the admissions criteria in use at universities globally and locally in South Africa. • Understanding the success rate of the GMAT as admissions predictor for MBA completion (globally). • Determining the success rate of the current admissions criteria as admissions predictor for the UNISA MBL completion. • Determine what data or combinations of data on the MBL application registration form can be used as a more successful predictor. iv The data collected for this study was obtained from the UNISA SBL administration department and consisted of a list of 724 students that enrolled for their MBL in 2003. The corresponding list of students that completed their studies in 2005 was also collected, which were 151 of the 724 students, or 20.9%. The data was re-coded and tested to determine in which of the data fields on the admissions form were there a statistically significantly correlation with regards to completing the MBL in 3 years. The following data fields indicated a statistically significant correlation: Race, Nationality, Age Group and Language. In order to test the final hypothesis, a classification tree making use of CHAID algorithms was used. The classification tree selected the data fields that showed statistically significant correlations. The data fields used was nationality, race and age groups. The classification tree re-grouped the data to achieve a 38.7% and 35.8% pass rate. Indicating that the newly developed admission tool is more successful in predicting students who will complete their MBL qualification in 3 years, than the current process, with which only 20.9% of the students passed. The pass rate of 38.7% might not sound significant, but it is an improvement of 85% on the current system. The research question was whether the data fields on the MBL application registration could be used to develop admissions criteria in order to serve as a predictor of the post graduate MBL student’s ability to complete the qualification in the prescribed period of time. This question was answered in two ways, firstly by the literature review, where Cate et al (2004) created a discriminant model that predicted MBA no-shows with 94.2% accuracy. Secondly by way of hypothesis 8 where the classification tree making use of CHAID algorithms grouped the students to achieve a pass rate of 38.7% and 35.8%, by only making use of the information available on the current UNISA admissions form. All the objectives of the study were met, and the following recommendations were made: Modify the admissions form to include some fields that may prove to be better predictors. Do not show away students, who according to the model will not pass, rather give them additional tutoring or require the students to complete a preparatory programme such as the Programme in Business Leadership (PBL), prior to starting with their MBL. Refine the admissions prediction model up to a point where the model is able to predict 80% to 90% of the cases correctly, prior to it being implemented, by using more than one MBL group that will give a more representative sample, and do not limit the study to only students that finished in the minimum period, but to all students that finished within 5 years. This study therefore concludes that the data fields on the MBL application registration form can be used to develop admissions criteria in order to serve as a predictor of the post graduate MBL student’s ability to complete the qualification in the prescribed period of time.