EARLY IDENTIFICATION OF UNIVERSITY OF TECHNOLOGY

ENGINEERING STUDENTS AT RISK

Barend J van Wyk

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Tshwane University of Technology (TUT)

• One of 23 government funded institutions of higher learning

• Seven faculties, including Engineering and the Built Environment

• 55 000 students on 6 campuses

• Engineering and Built Environment: 9 000 students

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South African Throughput Problem

TUT :

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Reasons in literature

• New National Senior Certificate (NSC) and the quality of the NSC as signal for higher education admission is still

blurred (7).

• Race and ethnicity, together with family income are factors that seriously impact on the experience of a disadvantaged student at HE, especially if the student is part of a minority group.

• In other parts of the world the historically disadvantaged students are usually also a minority group (12, 13, 14 and 8), but in South Africa that is not the case.

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To investigate the early identification of students at risk in our National Diploma engineering programs using readily available pre- and post-admission variables, we formulated the following research questions:

1: What is the relationship between NSC results and academic performance during the first two years of the National Diploma for engineering students ? ; and

2: What is the relationship between academic achievement during the first two semesters and completing the National Diploma in Engineering ?

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Participants and Setting

Participants in this study were 456 first year students from the 2009 first time entering National Diploma cohort and 274 first year candidates from the 2010 first time entering National Diploma cohort.

This sample of 730 students is representative of the 2009 and 2010 first time entering cohorts.

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Independent VariablesNational Senior Certificate results: The Mathematics, Physical Science and English scores, as well as the Academic Potential Score (APS), i.e. the aggregate of all NSC subject scores excluding Life Orientation, were used. Mathematics I: The final results for Mathematics I, a first semester subject in the South African UoT National Diploma engineering curriculum, were used. Mathematics I predicate score: The final Mathematics I exam admission score, reflecting performance during the first four months of the semester, and counting 50% of a student’s final score, was used. % Subjects Passed Semester I % Subjects Passed Semester II

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Results

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-1.4603 + 0.2613*(Mathematics I predicate as a %) + 0.7387*(% Subjects Passed Semester I): 86 % accurate to predict < 50% passed

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3.58 + 0.11*(% for Mathematics I) + 0.90*(% Subjects Passed Semester II): 91% accurate to predict who will pass < 50% of subjects

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Conclusion 1:

The Mathematics I score and percentage subjects passed after one and two semesters could be used as reliable indicators to identify students at risk and could be incorporated in an early warning system for drop out. Obviously such a system could include other factors such as communication skills, financial difficulties, quality of accommodation, distance from campus, family and socio economic situation, overall academic performance, etc.

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Conclusion 2:

Nearly 50% of the students we admit to our engineering programs are at risk right from the start. Since the admission of these at risk students are driven by the national emphasis on access and by institutional financial viability reasons, our support structures and foundation programs should be strengthened.

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Conclusion 3:

Once students who performed marginally in NSC were given a chance and after one or two semesters and it becomes clear that engineering is not the best option for them, student friendly mobility mechanisms to other programs need to be investigated.