Identification of learners' attitudes toward statistics based on classification of discriminant function

This study had identified the profiles of statistics learners' attitude toward statistics through the classification process of discriminant function. This multivariate technique method is used to profile the subjects' attitude into either positive or negative attitude towards statistics. The study had characterized each profile of learners by relating to his/her perceived attitudes toward statistics, types of learners, mode of study, programme structure, age, gender and learners' evaluation towards the statistics course. Learners' attitudes toward statistics were measured using the Attitudes Toward Statistics (ATS) instrument which comprised four sub-scales or dimensions, namely, Affect, Cognitive Competence, Value and Difficulty. These variables are examined as predictors that discriminate learners with positive and negative attitudes toward statistics. The results indicate that learners with positive attitudes can be reliably distinguished from learners with negative attitudes toward statistics across the four ATS sub-scales, types of learners, mode of study and learner's evaluation towards the course. The results would assist instructors to fine-tune their teaching methodologies to optimize the teaching and learning of statistics in the classroom.

[1]  Janet L. Kottke,et al.  Mathematical Proficiency, Statistics Knowledge, Attitudes toward Statistics, and Measurement Course Performance , 2000 .

[2]  Johan A. du Preez,et al.  Automatic language identification using mixed-order HMMs and untranscribed corpora , 2000, INTERSPEECH.

[3]  Cristiana Stefania Murgoci,et al.  Towards Profitability on the Financial Markets; A Discriminant Analysis Approach. , 2009 .

[4]  Jamie D. Mills.  Students' Attitudes toward Statistics: Implications for the Future , 2004 .

[5]  Ernest A. Rakow,et al.  The Relationship of Instructional Methods with Student Responses to the Survey of Attitudes Toward Statistics. , 1995 .

[6]  A. Ganapathiraju,et al.  LINEAR DISCRIMINANT ANALYSIS - A BRIEF TUTORIAL , 1995 .

[7]  Joseph J. Stevens,et al.  The Development and Validation of the Survey of Antitudes toward Statistics , 1995 .

[8]  R. Fisher.  THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[9]  José Barahona da Fonseca.  From fisher's linear discriminant analysis to NLDA or the story of the solution of a very difficult nonlinear classification problem , 2006 .

[10]  Paula M. Popovich,et al.  Attitudes toward Statistics: An Evaluation of Multiple Measures , 1988 .

[11]  Descriptors Educational.  Meeting of the American Educational Research , 1995 .

[12]  Carl J. Huberty,et al.  The Stability of Three Indices of Relative Variable Contribution in Discriminant Analysis , 1975 .

[13]  Patricia B. Elmore,et al.  The Survey of Attitudes Toward Statistics Scale: A Construct Validity Study , 2005 .

[14]  R. James Milgram,et al.  What Is Mathematical Proficiency , 2007 .

[15]  Candace Schau,et al.  STUDENTS' ATTITUDES: THE "OTHER" IMPORTANT OUTCOME IN STATISTICS EDUCATION , 2003 .

[16]  Jami A. Fullerton,et al.  An Analysis of Attitudes toward Statistics: Gender Differences among Advertising Majors. , 2001 .

[17]  R. Barcikowski,et al.  A Monte Carlo Study of the Stability of Canonical Correlations, Canonical Weights and Canonical Variate-Variable Correlations. , 1975, Multivariate behavioral research.

[18]  Ruth Ravid,et al.  The Relationship between Attitudes toward Statistics, Math Self-Concept, Test Anxiety and Graduate Students' Achievement in an Introductory Statistics Course. , 1990 .

[19]  Sterling C. Hilton,et al.  Survey of Attitudes Toward Statistics: Factor Structure Invariance by Gender and by Administration Time , 2004 .