The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 29-411
Full Name: Zamalia Mahmud
Position: Associate Professor
Age: ON
Sex: Female
Address: Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor
Country: MALAYSIA
Tel: +60355435367
Tel prefix:
Fax: +60355435501
E-mail address: zamal669@salam.uitm.edu.my
Other E-mails: zamalia@tmsk.uitm.edu.my
Title of the Paper: Identification of Learners' Attitudes Toward Statistics Based on Classification of Discriminant Function
Authors as they appear in the Paper: Zamalia Mahmud
Email addresses of all the authors: zamal669@salam.uitm.edu.my
Number of paper pages: 10
Abstract: 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 wi!
th 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.
Keywords: Statistics learners, attitudes toward statistics, profiles, discriminant function
EXTENSION of the file: .doc
Special (Invited) Session: A Discriminant Analysis of Perceived Attitudes Toward Statistics and Profiles Identification of Statistics Learners
Organizer of the Session: 614-154
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