Forecasting and Evaluation of Network Learning

• Main Author: 陳建龍
• Other Authors: 王聰榮
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/21219367313730592951

碩士 === 國立臺北科技大學 === 技術及職業教育研究所 === 88 === Network Learning play an important role in 21st century, and the development of WWW till now, the number of users with different purpose is getting larger and larger. In such environment, if we can import accurately and effectively Network Learning for upgrade the learning level of personal or institution or whole country, the adopt of Network Learning will yield twice the result with half the effort. So, this research will forecast the numbers of adopting by the theory of Rogers(1995), and find out the influence of Network Learning adopting rate, and support the result for importing Network Learning of relative institutions. The research do forecasting by theories, and to harmony with relative characteristics of Network Learning for fitness of forecasting model. To prove the research by questionnaires, and do analysis the factors of influence Network Learning adopting rate. In other word, the research obey the rules of science research by questionnaire and theories. Therefore, the purposes of the research are: 1.Forecasting the adopting of Network Learning; 2.Analysis the factors of influence Network Learning adopting rate. By the analysis, “Administors have the knowledge and concept of "modern"” and “Administors have given fully support of network learning system” and “The stability of operation the on network learning system” are most important factors. “The needs of users are acknowledgement by administors” and “The ability of maintenance of network learning system” and “Fully acknowledgement to appoint the directors of network learning system” are the next best factors, others as like context of thesis. By the non-linear analysis, the adopting rate of 1996 to 1998 increase contiguously, but at 1999 decrease the adopting rate. Keywords: Network Learning, Diffusion, Innovation