Predicting the Success rate of Engineering Students Anlia Pretorius, University of Johannesburg, South Africa Philippus P Pretorius, North West University, South Africa

2 Background Academic tuition places great demands on students. Many students experience numerous problems that can adversely affect their studies The cost in terms of the negative impact on their self-concepts, feeling of failure and frustration are difficult to ascertain “Drop outs” cost the South African tax payer R1.3bn per year, an amount that could be used to build approximately low cost houses 25% of students who register at tertiary institutions in South Africa drop out before completion of studies

3 Background Engineering is traditionally regarded as a “difficult” study direction. This is evident in the high drop out and failure rates for engineering students world-wide USA Today (19/2/2001) reports that four out of ten professors in engineering, affiliated to American Universities, believe that students are not well prepared to obtain a degree in engineering 43% believe that students drop out because they cannot master the mathematics 34% ascribe the high drop out rate to incorrect study methods and other social factors. (These results were evident in a study where 5000 USA professors in engineering participated in an investigation instituted by “MathSoft Engineering and Education Inc.)

4 The importance of training Engineers The SA government of the day has placed such a high premium on training in scientific fields that Universities are compelled to train more students in the “Science, Engineering and Technology” (SET) program Universities are pressured by the government to train more students, despite the fact that fewer students obtain university exemption A further concern is that in general, fewer candidates appear to be educated at matric level

5 Cognitive characteristics of engineering students High average intelligence High scholastic achievement in Mathematics and Science High mathematical ability Spatial ability (form perception: three-dimensional reasoning, perceptual accuracy: memory for form and spatial imagination) Mechanical insight

6 Selection of students All tertiary institutions make use of a selection mechanism in an attempt to determine which students have the best chance of successfully completing their studies Traditionally, students are selected on the basis of a score which is determined by the candidates matric symbols The use of a selection criteria by tertiary institutions is aimed at attempting to predict which students possess the ability to successfully complete a specific study direction If a selection battery were to attain its goal, it would not only turn students away, but also identify candidates and prepare them for studies

7 Investigation To compare the profiles of students who were successful in engineering during their first year (2001,2002 and 2003) with the profiles, of students who were unsuccessful during their first year, in terms of ability, study habits in mathematics and school achievement The study also takes into account the student’s progress in the second and third year (2001 and 2002) of study, where the successful and unsuccessful groups are again compared

8 Measuring Instruments SOM (Study Orientation Questionnaire in Mathematics) SAT (L) (Senior Aptitude Test) Matric Performance / Achievement 1.Study Attitude in Mathematics 2.Mathematics Anxiety 3.Study Habits in Mathematics 4.Problem-solving Behaviour in Mathematics 5.Study Environment 6.Information processing 1.Vocabulary (SAT L 1) 2.Verbal Reasoning (SAT L 2) 3.Non-Verbal Reasoning (SAT L 3) 4.Calculations (SAT L 4) 5. Reading Comprehension (SAT L 5) 6.Comparisons (SAT L 6) 7.Spatial Visualization 3-D (SAT L 8) 8.Mechanical Insight (SAT L 9) 9.Memory (Paragraph) (SAT L 10)

9 Sample/ Participants Group 1: 2001 intake; Group 2: 2002 intake; Group 3: 2003 intake Group 4: Combined (2001, 2002 and 2003, first semester of studies) 325 (Successful) and 187(Unsuccessful) Group 5: Combined (2001 and 2002, senior year of studies) 111(Successful) and 143(Unsuccessful)

10 Statistical significant Five stars (*****) indicate statistical significant differences at the 0.1% level Four stars (****) indicate statistical significant differences at the 1% level Three stars (***) indicate statistical significant differences at the 5% level Two stars (**) indicate statistical significant differences at the 10% level One star (*) indicates statistical significant differences at the 20% level No stars ( ) indicate statistical insignificant differences, meaning that no differences were detected

11

12

13 SOM 1 to 6 SOM1 – Study attitude towards mathematics SOM2 – Mathematics anxiety SOM3 – Study habits in mathematics SOM4 – Problem-solving behaviour in mathematics SOM5 – Study environment: SOM6 – Information processing Student 1(s) Math A+ Science A+ Student 2(o) Math C Science C

14

15 SOM 1 to 6 and Calculations ( 7 fields) The risk can now be calculated by combining more scores. The SOM (6 sub-fields) and SAT L (Calculatios) can be combined to determine the risk (5 stars). Given this, work has begun on a new score (S-score) which is a combination of the SOM (six subfields) and SAT L (Calculations). This S-score provides the number of dimension on the basis of which students are included in the successful group.

16 Conclusion If higher education wants to implement the proposals of the National Plan, then it is critical that a useful and well founded admission- / selection and placement battery be implemented This battery should not only be used for exclusion purposes but also to point out deficiencies which can be addressed in foundation courses Further, it aims to predict possible rate of success to prospective students before commencement of studies If the prospective student appears to be at risk, then preventative measures can be implemented beforehand Thank You