Discriminating Math Low-Achievement Motivation Patterns: Comparing Disadvantaged and Other Students in Elementary and Junior High School

Author: Yi-Mei Lee(Department of Psychology and Counseling, National Taipei University of Education)

Vol.&No.：Vol. 57, No. 4
Date：December 2012
Pages：39-71
DOI：10.3966/2073753X2012125704002

Abstract：

This study assesses math-avoidant motivation patterns of disadvantaged students to determine whether they require remedial education and learning guidance. The study includes 764 elementary and junior high school students (426 male and 338 female, and 428 normal and 336 disadvantaged). The students were sampled by region and school size in Taiwan. These students completed the Math Avoidance Motivation Scale, including variables measuring “self-efficiency,” “expectancy of success,” “perception of difficulty,” “intrinsic motivation,” “avoidance strategies,” “resistance,” and “self-control.” Two-stage cluster analysis, discriminant analysis, analysis of variance, and x2 (chi-square analysis) were used as statistical methods. The results of the study show that students are divided into 4 clusters: enjoyment, permissiveness, helplessness, and carefulness. Discriminant analysis of the 7 observed variables identified 2 functions: affection and conation. These 2 functions differentiate between the 4 student clusters. The results also show that differences occur between the proportion of enjoyment and permissiveness clusters in the disadvantaged and normal student groups. This study explores 4 math avoidant motivation patterns and proposes that teachers recognize student styles. Teachers can encourage permissive students to form self-governing learning habits and support helpless students psychologically with remedial education programs.

Keywords：disadvantaged students, discriminant analysis, cluster analysis, math learning motivation

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