程紹同Cheng, Shao-Tung蔡雅欣Tsai, Ya-Hsin2019-09-052022-08-012019-09-052017http://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22G060430056A%22.&%22.id.&http://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/105044在資訊經濟的時代裡，數據已經成為各領域間競爭之利器，如何分析、運用資料以解決各項議題，進而獲得價值，將成為各領域的首要課題。然而，在國內運動領域中，是否也能善用大數據的效益尚不得而知。鑑此，本研究蒐集並分析臺灣大數據碩博士論文內容數量及相關聯情形，進而推估運動大數據未來研究方向。研究對象以2011年-2016年間所發表過的大數據論文為主，採用內容分析法，並以自編「臺灣大數據論文內容分析登錄表」做為研究工具，運用次數分配表及百分比分析進行資料處理。透過臺灣大數據論文全面分析與探討，本研究結論如下： 一、臺灣大數據論文研究現況 自2013年始有論文的產出，2015年論文篇幅數量最多，期刊以社會科學領域最多，學位論文以國立臺灣大學等七所學校佔近五成最多。 二、臺灣大數據論文研究內容 (一)研究主題：在各研究主題統計上，以「其他」為最多，「運動」則相對較少。 (二)研究目的：研究目的以「分析性研究」佔近五成為最多，「敘述性研究」與「理論性研究」兩者並重。 (三)研究方法：研究方法以「次級分析法」佔近五成為最多，其次為「系統建構法」，第三多為「調查研究法」及「實驗研究法」，四者所佔比例超過八成。 (四)統計方法：統計方法以「未使用統計方法」超過五成為最多，其次為「其他」，兩者所佔比例超過八成。 三、臺灣運動大數據未來研究趨勢 目前臺灣運動大數據研究議題較為單一，然而，在穿戴式科技的普及下，個人體適能等相關議題將會成為臺灣運動大數據未來研究趨勢。 基於上述結果，建議大數據研究者及相關單位：（一）增加實證性研究。（二）結合專業（運動領域）與實務課程規劃。（三）強化各種研究方法之應用。對後續研究建議：（一）增加關鍵字數量。（二）研究方法加入德爾菲法 (Delphi method)。（三）增加次要類目，進一步探討各主題之趨勢。（四）研究對象加入其他論文形式。In the era of information economy, data has become a global tool for international competition in the world. The information analysis and applications have been critical for decision makers of governments, industries, (non) profit organizations, to solve various issues and create values. However, there is few Big Data academic studies have been done including in the field of sport in Taiwan. Thus, the purpose of this study was to analyze Taiwan’s these and dissertations of Big Data during 2011-2016. Content analysis was applied for discussion. Through the comprehensive analysis and discussion of Taiwan’s these and dissertations of Big Data, the conclusions of this study are as follows: A. The status of Big data papers in Taiwan Since 2013 the first paper came out, the quantity of the paper kept growing. The highest production of publication is in 2015 recently. The highest production of journal publication is from social science. For thesis and dissertation, the highest production (50%) is from National Taiwan University among seven universities. B. The research content of Big data papers in Taiwan (a)Theme of the study: The subject of statistics in the “other” have the largest number, “sport” is relatively few. (b)Purpose of the study: “Analytical research” have the largest number, “Narrative research” and “Theoretical research” are as much as two. (c)Research methods: “Secondary analysis”accounted for almost fifty percent, the second one is “System construction”, the third one is “Survey Research” and the forth one is “Experimental Research”. The proportion of the two are more than eighty percent. (d)Statistical methods: The large number of statistical method is “No statistical method” more than fifty percent, the second is “other”. The proportion of the two are more than eighty percent. C. The trend of Sport Big data future research in Taiwan The research topic of Taiwan's Sports Big Data is relatively simple. However, under the popularization of wearable device, personal fitness and other related issues will become the future research trend of Taiwan's Sport Big data. Based on the results, the recommendation is as follow: (a) increase the empirical study. (b) combined with professional (sports field) and practical curriculum. (c) strengthen the various methods. For the future researcher, the recommendation is (a) increase the number of keywords. (b) use Delphi method in method. (c) increase secondary categories. (d) increase other forms of paper into research object.運動大數據內容分析法SportBig DataContent analysis