| The purpose of the study was to examine, by a mixed-method research methodology, principals' use of a relational database management system (RDMS) to assist in data-driven decision making (D3M). The study explored (a) the frequency of use, (b) the manner of use, (c) the role that staff development/training played in the extent of usage, (d) the relationship between the amount and perceived quality of staff development and principals' use of the system, and (e) the challenges principals face in using the relational database management system for data-driven decision making.; The study examined the use of four types of data: demographic, achievement, perception, and school process with five elements of data-driven decision-making concepts: collecting, analyzing, reporting, using, and communicating. A Web-based online survey was sent to nine hundred fifty-nine kindergarten through grade twelve California school principals. The overall response rate was 24.8 percent. Interviews were conducted with twelve participants from the survey sample.; The study revealed that during a twelve-month period, principals use the relational database management system an average of eleven times to collect student achievement data; nine times to analyze and use achievement data; and six times to analyze, report, and communicate achievement data. The findings show that principals use the system as a tool to correlate both standardized and criterion reference tests' scores with student ethnicity, language proficiency, California state standards, and instructional strategies. Fifty percent of the interviewed principals indicated that staff development was helpful in preparing them to collect, analyze, and report data for D3M.; Another important finding was a statistically significant relationship (p < .05) between the amount of and perceived quality of staff development and the frequency with which principals used the RDMS. Finally, principals indicated that staff development, time, difficulty of use, and system reliability were the challenges in using the relational database management system for data-driven decision making. |
