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Evaluation of an Experimental Data Management System for Program Data at the College LevelNair, Hema 29 July 2016 (has links)
An experimental data management system has been designed, developed, and implemented in this dissertation. The system satisfies the requirements specifications of the Department of Curriculum and Instruction in the School of Education. The university in this study has installed some learning management systems and assessment systems, such as Banner®, Canvas®, TracDat®, and Taskstream® (university’s name is omitted for anonymity purposes). These systems individually do not perform the necessary data analysis and data management to generate appropriate reports. The system developed in this study can generate more metrics and quantitative measures for reporting purposes within a shorter time. These metrics provide credible evidence for accreditation.
Leadership is concerned with improving the effectiveness, efficiency, accountability, and performance of educational programs. The continuity, sustainability, and financial support of programs depend on demonstrating the evidence that they are effective and efficient, that they meet their objectives, and that they contribute to the mission and the vision of the educational institution. Leadership has to employ all means at its disposal in order to collect such evidence. The data management system provides comprehensive data analysis that can be utilized as evidence by the leadership to accomplish its goals.
The pilot system developed in this research is web-based and platform independent. It leverages the power of Java® at the front-endand combines the reliability and stability of Oracle® as the back-end database. It has been tested on-site by some members of the departmental faculty and one administrator from the Dean’s Office in the School of Education.
This research is a mixed methods study with quasi-experimental treatment. It is a single case experimental study. There is no control group. The sample chosen is a convenient sample.
The results of this study indicate that the system is highly usable for assessment work. The data analysis results generated by the system are also actionable. These results assist by identifying gaps in student performance and in curriculum and instruction practices.
In the future, the system developed in this dissertation can be extended to other departments in the School of Education. Some implications are provided in the concluding chapter of this dissertation.
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