Abstract

This research aims to identify undergraduate students’ intelligence profiles using a two-stage cluster analysis based on the person’s ability of the Rasch model to examine the effect of the clusters on academic performance. A total of 1443 undergraduate students from nine academic disciplines at Universitas Padjadjaran in Bandung, Indonesia, participated in the study, completing 11 subtests of the Tes Intelligensi Kolektip Indonesia Tinggi (TIKI-T). A hierarchical cluster analysis approach using Ward’s linkage method and squared Euclidean distance was conducted, followed by a nonhierarchical k-means cluster analysis using simple Euclidean distance as the similarity measure to examine two-, three-, four-, and five-cluster solutions. An intra-class correlation (ICC) and a discriminant analysis were also conducted to validate the cluster membership results. This research identified five profiles of intelligence that had an effect on academic performance. Students with high scores in the scholastic aptitude subtests tended to have higher grade point average than those with high scores in the nonverbal ability subtests and the speed and accuracy ability subtests. The findings can be used as a recommendation for psychologists in Indonesia for university placement tests.

Highlights

  • Intelligence is related to performance in a wide range of cognitive tasks and is one of the best predictors for educational and professional success (Buschkuehl & Jaeggi, 2010; Rosander, Bäckström, & Stenberg, 2011; Schmidt & Hunter, 1998)

  • The results suggest that reliable intelligence profile patterns of the Tes Intelligensi Kolektip Indonesia Tinggi (TIKI-T) subtest scores can be derived using cluster analysis for undergraduate students

  • This study found that students from the nine academic disciplines showed variations in both level and pattern of performance across the TIKI-T subtests

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Summary

Introduction

Intelligence is related to performance in a wide range of cognitive tasks and is one of the best predictors for educational and professional success (Buschkuehl & Jaeggi, 2010; Rosander, Bäckström, & Stenberg, 2011; Schmidt & Hunter, 1998). Research in educational settings has revealed that intellectual factors obtained from psychometric tests have medium to high correlations with students’ academic performance. The relationship was higher when the latent intelligence traits (Spearman’s g of a psychometric test) and the latent traits of educational performance were correlated. It should be emphasized that the correlation between IQ and academic performance for university students was lower than that for junior and elementary school students. This trend was related to the restriction range of university students who are selected on more specific criteria (Chamorro-Premuzic & Furnham, 2005)

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