The purpose of this case study is to evaluate two methods of strategic planning within organizational visioning: Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis and Appreciative inquiry (Ai).  SWOT analysis is a method of strategic planning that is popular within companies and organizations due to its simple, yet thorough, approach.  Ai has recently emerged as an approach to strategic visioning and planning within organizational development.  However, little research has been conducted to evaluate either approach to organizational visioning, and there is a growing need to compare the two techniques.  In this case study, participants within one organization were divided, with half of the staff participating in Ai and the other half participating in SWOT.  Data for this mixed methods study was gathered through observation, focus group interviews, and pre-test, post-test, and delayed post assessments tests.  Through the explanatory sequential design, quantitative data evaluated the change in organizational commitment and vision clarity as a result of the interventions; while, qualitative data further explored participants\' perception of the intervention process and resulting effects.  The study found a statistically significant interaction between intervention treatments and the pre-test and post-test scores within the organizational commitment construct.  Seven themes emerged from the qualitative data; however, only two themes were specifically associated with an intervention treatment.  Participants in the SWOT intervention described the visioning process to be frustrating and negative; while, Ai participants found that the visioning process confirmed many of their beliefs and values about the department.  Recommendations for future practice suggest the use of Strengths, Opportunities, Aspiration, Results (SOAR) as an approach that combines and maximizes Ai and SWOT.  Suggestions for future research are to explore SWOT as a precursor to di-visioning within the Visioning Process Model. / Master of Science in Life Sciences