Classroom response systems: Using task technology fit to explore impact potential
The primary purpose of this study is to determine how students are impacted by the use of Classroom Response System (CRS) technology. This research explores the nature of the outcomes experienced by students and their perceptions on the leading pedagogy and practices for using CRS technology in the classroom. The research is both quantitative and qualitative in nature. Using the Task-Technology Fit (Goodhue and Thompson 1995) theoretical model and Kirkpatrick's four-level model (Kirkpatrick 1996) to define outcomes, this study employs a quasi-experimental design with two large Information Systems classes over the course of a semester. One class, the Treatment Group, used CRS technology and the other, the Control Group, did not. Data collected from this quasi-experiment were analyzed for patterns using Multivariate Adaptive Regression Splines (MARS), a data mining technique, used to profile types of students based on their experienced outcomes, personality, and levels of perceived fit. Follow-on qualitative discussions with students provided insight to student perceptions about CRS technology use. Findings from the study suggest that automated CRS technology produces different outcomes for students than analog response systems, based on both the student's personality profile and their level of perceived fit. Suggestions for future research are also presented.