María Pita CarranzaÁngel CentenoÁngela CorengiaLaura LlullBelén MesuradoCecilia PrimogerioFrancisco Redelico

Predicting Academic Performance and Attrition in Undergraduate Students

INTRODUCTIONINTRODUCTION

Improvement of EDUCATIONAL QUALITYEDUCATIONAL QUALITY

Matter of concern to all Higher Education Institutions

Develop TOOLSTOOLS to predict to what extent students are capable to:

- Reach a good academic performance

- Finish their studies successfully

Explore the relationship between

PURPOSEPURPOSE

EDUCATIONALAPTITUDES

(DAT)

ACADEMIC PERFORMANCE

1530 undergraduate students

from 8 different programmes of a private university in Argentina

ATTRITION

- Accounting / Business Economics - Social Communication- Industrial Engineering / Software Engineering- Law- Medicine- Nursing

DATDAT

DIFFERENTIAL APTITUDE TESTDIFFERENTIAL APTITUDE TEST

Set of tests that “measure” different

Educational AptitudesEducational Aptitudes

Complete set defines a cognitive profilefor each student

- Abstract reasoning- Verbal reasoning- Speed and accurancy- Language / Spelling- Numerical ability- Space relations- Mechanical reasoning

Ability to predict the success or future performance in certain activities.

RELIABILITY Tests are consistent, the results obtained are stable, free of casual failures.

INDEPENDENCEOF MEASURED

APTITUDES

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.

VALIDITY

Why DAT?Why DAT?(Bennet, Seashore, Wesman, Justo)

DAT has a high enough reliability and a sufficiently low intercorrelation as to be considered a battery of tests with

a good discriminative power.

THEORETICAL FRAMEWORKTHEORETICAL FRAMEWORKReview and synthesis of published studies

ARGENTINAINTERNATIONAL

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.

RELEVANCERELEVANCE

• 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.

METHODMETHOD

EDUCATIONALAPTITUDES

DAT- Abstract reasoning- Verbal reasoning- Speed and accurancy- Language / Spelling- Numerical ability- Space relations- Mechanical reasoning

ACADEMIC PERFORMANCE

GPAGrade Point Average of the first academic year

ATTRITION

Student drops out studies

Relationship between

METHODMETHOD

1530 first year undergraduate students from of a private university in Argentina

SAMPLESAMPLE

- 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

METHODMETHOD

1. Exploratory analysisExploratory analysis of data.

2. General linear modelGeneral linear model: educational aptitudes related to students’ academic performance.

3. Multiple regressionsMultiple regressions: relationship of each educational aptitude with academic performance.

4. Generalized linear modelGeneralized linear model: relationship between educational aptitudes and attrition.

Regression Model for each Course

Source: Made by the authors

Programp-value (< .05)

R2

AR VR S&A NA L S MR SR

Nursing .01 .001 .05 .001 - - - - .34

Social Communication

.01 .0001 .0001 - .0001 .0001 - .001 .25

Law .001 .000 .01 .05 .000 .000 .05 - .25

Engineering .01 .000 .01 .01 .001 .001 - - .15

Business .01 .0001 .05 .05 .01 .01 - - .14

Medicine .05 .000 - .000 .01 .001 - - .12

RESULTSRESULTS

RESULTSRESULTS

Program Odds ratioGrade of

significance

Nursing 1.14 .45

Social Communication 1.2 .10

Law 1.82 .10

Engineering 2 .10

Business 2.14 .10

Medicine 1.4 .40

Odds Ratio and Grade of significance

Source: Made by the authors

CONCLUSIONCONCLUSION

DAT scores: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.

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.

DATDAT scores obtained have allowed designing personalized strategies of mentoring in order to promote good academic

performance and to increase retention rates.

Population enrolled uniform inagesocio-cultural backgroundeconomic background

CONCLUSIONCONCLUSION

THANK YOU!!!THANK YOU!!!mpita@austral.edu.ar

Predicting Academic Performance and Attrition in Undergraduate Students