A Study on a Supporting Model for Curriculum Decision-Making Using Data Warehouse Technology

• Main Authors: Hsu, Ming-Ju, 徐明珠
• Other Authors: Yung, Chaur-Shin
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/97002366509655939193

博士 === 國立臺灣師範大學 === 工業教育學系 === 95 === A Study on a Supporting Model for Curriculum Decision-Making Using Data Warehouse Technology Hsu, Ming-Ju Abstract While facing swift changes and constant evolutions derived from globalization and information technologies, proper and effective curriculum developments by colleges and universities are critical and consequential in upgrading the quality of education to cope with the dynamic impacts from both internal and external challenges. However, it is difficult and arduous in making curriculum decisions due to the imminence and complexity of the process, the multiple factors involved and the characteristics of specific knowledge domain of each university curriculum. Traditional curriculum development process which mostly dependent on document analysis and consulting meeting seems to be outdated and ineffective. Curriculum decision making process needs be simplified and crystallized by decision-support technique available via computer and information technologies, so that university curriculums are optimized to meet essential requirements improving the quality of education. The university curriculum database constructed and maintained by the Ministry of Education (MOE) has stored a large amount of curriculum data, which could be examined and extracted to establish a University Curriculum Data Warehouse (UCDW) in support of various curriculum developments. The main purpose and objective of this research was therefore to establish a model using data warehouse technique to facilitate the curriculum development process, when properly constructed this model can help colleges and universities make effective curriculum decisions. The main axis of the research study was based on the literature theory of the curriculum, combined with curriculum policies and regulations, professional opinions and expert knowledge to form the three curriculum development factors in the curriculum decision-support model, which are curriculum situation analysis, curriculum organization and curriculum decision-making. Data Warehouse and Data Mining techniques were carried out to explore the UCDW to verify the validity of the model for Knowledge Discovery in Database (KDD). As the model was refined and its feasibility established, it can become a viable method to be used for Curriculum Knowledge Discovery in Data Warehouse (CKDD) and can significantly improve the curriculum decision making process. This research study was comprehensive in essence: literature analysis, expert questionnaire survey, and decision support technology were carried out, laying the triangular foundations for this research study. Data Warehouse and Data Mining techniques were applied to extract the data from UCDW, the data were then analyzed both quantitatively and qualitatively to verify and calibrate the research findings from the triangulation study. It combined multiple research methods with various statistical tools for meaningful data analysis, so it had characteristics of a hybrid research approach. Among these methods of study, the main purpose of applying expert structured questionnaire and in-depth interviews was to use triangulation analysis and calibration to establish decision-making factors for university curriculums, to break through the predicament that research study in university curriculum is so scarce that it can’t provide a good theoretical basis for a sound curriculum decision-making research. The primary objective of this decision-support model therefore was to utilize the studied results from literature analysis and expert survey in establishing a framework of the model for curriculum decision-making, which was further verified by Data Warehouse and Data Mining techniques. Moreover, this framework was then applied to a CKDD case study on all the departments of Journalism’s curriculums in all the universities in Taiwan, to study the effect of curriculum decision-support of this model. In the statistical analysis of the curriculum data, descriptive statistics was first conducted to capture the profile of the status, so that situation analysis for the curriculum development could be followed secondly. Decision Tree and Association Rule were used to examine the curriculum subjects and variables to determine the structure and relationship among the curriculums. The principles of decision-making were then established based on the established rules. The rules resulted from the different research methods showed high degree of consistency, more importantly, the rules retrieved from the decision-support model were more accurate and efficient than from those of modeling through traditional method of curriculum development. This finding significantly proved the feasibility of this model in support of curriculum decision-making using Data Warehouse technology. Finally, this research study developed several important models for curriculum developments and decision makings, including the Research Model for Curriculum Decision-Making Using Data Warehouse, the Decision Tree Model for Curriculum Knowledge Discovery in Data Warehouse (CKDD), the Association Rules and Model for CKDD, the Supporting Model for Curriculum Development Using Data Warehouse Technology and the Supporting Model for Curriculum Decision-Making Using Data Warehouse Technology, etc. The results of this research hopefully provide positive suggestions for those personnel who work on curriculum developments, college curriculum website and Department of Journalism for further improvement in their respective curriculum programs. Furthermore, hopefully this research study has laid a foundation for more meaningful follow-up studies that could be applied to many related areas toward the new era of curriculum developments, which is completely based on a comprehensive model using Data Warehouse technology.