This qualitative study identified the best practices utilized by community colleges to achieve systemic and cultural agreement in support of the integration of institutional effectiveness measures (key performance indicators) to inform decision making. In addition, the study identifies the relevant motives, organizational structure, and processes to support the continuing organization development as the institution transitions to an information rich decision making environment.
A multi-dimensional conceptual framework consisting of four concepts and theories was used to situate the study. The conceptual framework elements were: John Levin's (2001) Four Domains of Globalization (globalization), L. E. Greiner's (1998) Five Stages of Organizational Development (organizational change and development), Robert Stringer's (2002) Leadership and Organizational Climate model (organizational culture), and lastly a data management analysis framework developed by Rand Corporation researchers Gina Ikemoto and Julie Marsh (2007) (knowledge management).
Three Academic Quality Improvement Program (AQIP) community colleges from the Higher Learning Commission's North Central Association were selected as participants. Colleges participating in AQIP were selected because Program participants actively pursue the integration of continuous process improvement and total quality management principals into the management practices of their institutions. The merging of these principles into the cultural fabric of the institution is vital to developing a data-driven decision-making environment that steers the organization towards enhanced organizational effectiveness. To ensure transferability of the study's findings purposefully sampling with random sort and maximum variation were applied to identify the participating colleges.
The study's findings affirmed research from organizational development literature (Weick, 1993; Greiner, 1998) that states; in order to reduce ambiguity in interpreting data results (information) and achieve maximum benefit, organizational members must have at their disposal a process, data management infrastructure and supporting cultural environment to fully implement data-driven decision making practices throughout the community college organization. Derived from the findings, the Knowledge-management and Effectiveness Integration Model (KEIM) provides as formative process that will help administrators, faculty, and staff transform their institutions into a data-driven decision making college and assist them in understanding the significance, implications, and importance of the data they collect. The KEIM provides a practical implementation approach for community colleges seeking to establish a comprehensive data and knowledge management process as it addresses the behavioral complexity of the organizational culture and highlights leadership roles needed to create a supportive organizational climate for the transformative change.
|Commitee:||Haynes, Dennis, Spangehl, Stephen|
|Department:||Community College Leadership|
|School Location:||United States -- Illinois|
|Source:||DAI-A 73/11(E), Dissertation Abstracts International|
|Subjects:||Community college education, Higher Education Administration, Business education|
|Keywords:||Academic quality imporvement program (AQIP), Community colleges, Data-driven decision making, Decision-making, Institutional effectiveness, Knowledge management, Organizational development|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be