This research project develops an electronic assessment model with vocabulary, clicker, and homework assessment questions for a broad range of undergraduate introductory statistics courses. Report generating programs incorporating the current state of data visualization research will be developed to automatically generate reports for students, course instructors, and supervisors, enabling rapid feedback on learning and instruction to all parties. The effectiveness of this new technology on student learning will be evaluated along with the progression of student learning of course outcomes and impact of different styles and methods for delivering questions. The intellectual merit of this project is its contribution to the field of statistics education by extending previous work on course level student learning outcomes (GAISE College Report) to the topic level and by developing assessments to measure these outcomes. These assessments will inform student learning and instruction by finding the relative difficulties students have in learning course outcomes, obtaining the most common patterns exhibited by students in their understanding of course learning outcomes, and identifying the most common problems students have in learning particular outcomes. The broader impact of this project is to affect assessment in undergraduate introductory statistics courses at many institutions by providing instructors at other institutions with an electronic assessment model with report generating software. This project will provide a template for electronic assessments in other introductory courses in STEM fields.
