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María Pita Carranza Ángel Centeno Ángela Corengia Laura Llull Belén Mesurado Cecilia Primogerio

Predicting Academic Performance and Attrition in Undergraduate Students. María Pita Carranza Ángel Centeno Ángela Corengia Laura Llull Belén Mesurado Cecilia Primogerio Francisco Redelico. INTRODUCTION. Improvement of EDUCATIONAL QUALITY.

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María Pita Carranza Ángel Centeno Ángela Corengia Laura Llull Belén Mesurado Cecilia Primogerio

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  1. Predicting Academic Performance and Attrition in Undergraduate Students María Pita Carranza Ángel Centeno Ángela Corengia Laura Llull Belén Mesurado Cecilia Primogerio Francisco Redelico

  2. INTRODUCTION Improvement ofEDUCATIONAL QUALITY Matter of concern to all Higher Education Institutions • DevelopTOOLSto predict to what extent students are capable to: • - Reach a good academic performance • - Finish their studies successfully

  3. PURPOSE Explore the relationship between ACADEMIC PERFORMANCE EDUCATIONAL APTITUDES (DAT) ATTRITION - Accounting / Business Economics - Social Communication - Industrial Engineering / Software Engineering - Law - Medicine - Nursing 1530 undergraduate students from8different programmes of a private university in Argentina

  4. DAT DIFFERENTIAL APTITUDE TEST Set of tests that “measure” different Educational Aptitudes • Abstract reasoning • Verbal reasoning • Speed and accurancy • Language / Spelling • Numerical ability • Space relations • Mechanical reasoning Complete set defines a cognitive profile for each student

  5. Why DAT? (Bennet, Seashore, Wesman, Justo) Ability to predict the success or future performance in certain activities. VALIDITY Tests are consistent, the results obtained are stable, free of casual failures. RELIABILITY Tests show low intercorrelation. The measured aptitudes of the different tests differ enough to justify the inclusion of all tests in the series. This is specially satisfactory if it is considered that each test was devised to have its own validity. INDEPENDENCE OF MEASURED APTITUDES DAT has a high enough reliability and a sufficiently low intercorrelation as to be considered a battery of tests with a good discriminative power.

  6. THEORETICAL FRAMEWORK Review and synthesis of published studies INTERNATIONAL ARGENTINA The results of the standardized test scores are related to students’ academic performance, among other indicators, especially during the first year of the undergraduate courses. • Although it is difficult to find studies related to results of standardized tests, institutions share the same concern about the search of indicators: • The studies surveyed are related to: • - socio-demographical variables • - school background • - performance in admission process • job situation • professional insertion expectations • - personality, problem-solving and • intelligence tests, etc.

  7. RELEVANCE • Provide information to academic advisers. • Early detection of students that are potentially • vulnerable to suffer academic failure. • Provide empiric evidence to theoretical discussion • about this subject.

  8. METHOD Relationship between EDUCATIONAL APTITUDES DAT - Abstract reasoning - Verbal reasoning - Speed and accurancy - Language / Spelling - Numerical ability - Space relations - Mechanical reasoning ACADEMIC PERFORMANCE GPA Grade Point Average of the first academic year ATTRITION Student drops out studies

  9. METHOD SAMPLE 1530first year undergraduate students from of a private university in Argentina - 8 programmes: Business -Accounting and Business Economics-, Social Communication, Engineering -Industrial Engineering, Software Engineering-, Law, Medicine and Nursing. - Age: 17 to 20 years old - Socio-economic level: medium to medium-high sectors - Enrolled in 2002, 2003, 2004 and 2005

  10. METHOD 1. Exploratory analysisof data. 2. General linear model: educational aptitudes related to students’ academic performance. 3. Multiple regressions: relationship of each educational aptitude with academic performance. 4. Generalized linear model: relationship between educational aptitudes and attrition.

  11. RESULTS Regression Model for each Course Source: Made by the authors

  12. RESULTS Odds Ratio and Grade of significance Source: Made by the authors

  13. CONCLUSION • DAT scores: • Allows estimating students’ academic performance in • the first year of undergraduate programs. • Predict moderately chances of attrition in some • programmes -Business, Engineering, Law and Social • Communication-, whereas in others -Nursing and • Medicine- its prediction capacity is not significantly, in • the statistical meaning.

  14. CONCLUSION age socio-cultural background economic background Population enrolled uniform in Measure the impact of other variables -motivation, satisfaction, stress- in order to complement this study with other factors that can influence both academic performance and retention. DATscores obtained have allowed designing personalized strategies of mentoring in order to promote good academic performance and to increase retention rates.

  15. Predicting Academic Performance and Attrition in Undergraduate Students THANK YOU!!! mpita@austral.edu.ar

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