560 – Contributed Oral Poster Presentations: Section on Statistical Education
Development and Initial Testing of the Online Undergraduate Statistics Inventory
Raymond Mooring
Analysis Made Easy
As technology advances, courses that were once taught using chalkboards in classrooms (e.g. Introductory Statistics) are now being offered online by various university departments. To be successful, the students in these courses must master the statistics content and navigate the online environment. Previous efforts to predict success in statistics have not included data from students in online sections. Because of this, the predictive power of skills germane to the online environment is not taken into consideration. On the other hand, inventories have been developed to predict academic success in the online environment using data from general courses, not STEM subjects. The inventories fail to capture the self-discipline and technical competence needed to succeed in a STEM subject. This study begins to fill this void. The goal is to develop an inventory (questionnaire) that can predict success in a fully online undergraduate statistics class. The psychometric properties (calculated under the Rasch framework) of the first iteration of the Online Undergraduate Statistics Inventory (OUS-I) are presented here. The dimensionality of the OUS-I, effectiveness of the reverse coding used in the instrument, and the effectiveness of the rating scale are investigated.