This study attempts to construct the profiles of two types of statistics learners: namely those<br>with a positive and a negative attitude towards statistics. The contribution of this work lies in<br>its attempt to characterize each profile of learner by relating to his/her perceived attitudes<br>toward statistics, types of learners, mode of study, program structure, age, gender and<br>learners' evaluation towards the statistics course. These variables are used as predictors that<br>discriminate learners with positive and negative attitudes toward statistics. The results<br>indicate that learners with positive attitudes can be reliably distinguished from learners with<br>negative attitudes toward statistics. This then can assist instructors to optimize the teaching<br>and learning of statistics in the classroom.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education