Development and initial assessment of Texas Cooperative Extension's white-tailed dear management module

Abstract

The purpose of this study was to evaluate the development and initial use of Texas Cooperative Extension’s (TCE) White-tailed Deer Management Module (WDMM) delivered over the Internet. The results of this study will provide suggestions about future online wildlife management modules. Data were collected from two populations using questionnaires. A sample of six county Extension agents (CEA’s) and four Extension specialists were selected by an Extension wildlife specialist who perceived them to be professionals in the fields of wildlife and range management. This first sample is also referred to as change agents. The second sample, also known as early users, consisted of 27 anonymous CEA’s and landowners within TCE’s District 10. Quantitative and qualitative methods were used to collect and analyze data. The results are as follows: Thus, the development of WDMM was the responsibility of the Extension specialist and researcher. The Extension specialist and researcher did seek professional opinions on content and layout information. Results suggested that CEA’s and Extension specialists agreed the WDMM would be a beneficial educational tool for new landowners. Overall, WDMM was perceived to be user friendly, visually appealing, and provided useful content. Although most change agents responded positively to most questions, there were a few that would like to see more educationally challenging questions. For example, there were a few questions that respondents felt were of the “elementary” and “kindergarten” level. They would like more questions concerning management. The majority of early users were in support of WDMM. Data gathered from the WDMM Feedback Questionnaire agreed with data gathered from change agents. In general, most early users said that they were pleased with the WDMM. Recommendations were made based on these findings to expand the WDMM. Some of these include: 1) Expanding WDMM; 2) Replicating this study using random sampling; 3) Collecting computer knowledge and skills and demographics on future studies; 4) Developing similar modules to see if they gain the same positive response.