Self-Guided Learning: The value of self-directed projects in Statistics for Business and Economics Angela D. Mitchell, Ph.D. Associate Professor of Business and Economics Area Coordinator Wilmington College Wilmington, Ohio 45177 937-382-6661 x211 angela_mitchell@wilmington.edu Introduction: It is becoming increasingly important to develop the critical thinking skills of undergraduate students as they prepare for their careers. Teaching such skills seems to fit well within a statistics courses for Business and Economics students. Although students may be able to work textbook problems or solve a case study with the assistance of Excel, can they really apply the concepts? Rarely will problems they face in their careers be so neatly designed as a textbook case study. The objective of this teaching initiative is to allow the students to navigate through a problem from data collection to analysis and interpretation. This project grew out of a general concern with the typical statistics courses. It has been found that there is a “need to change the way we teach business statistics” (Johnson & John, 2003, p. 93). Students benefit from active learning strategies that “facilitate student engagement and enhance student learning” (Harrington & Schibik, 2004, p. 361). In addition, Harrington and Schibik (2003) note that “rarely are statistical analysis projects done in isolation” (p. 363). Lastly, it is important for students to be able to “communicate findings both in writing and orally” (Blair, 2006, p. 40). It was decided that self-directed group projects, culminating in papers and presentations would offer just such opportunities for student learning. The poster will present and describe an approach to implementing self-guided learning in an undergraduate statistics course. Self-guided learning is incorporated into the course through three data projects assigned throughout the term. The poster will focus especially on ways that conference participants might be able to use similar structures at their institutions to create important real-world statistics projects. Finally the poster will present preliminary data to demonstrate the affect of the self-guided approach on student learning. A. Mitchell Proposal ASSA Meeting – January 2011