資料探勘應用於模擬訓練知識品質評量之研究：以國軍射擊模擬器訓練為例

A Data Mining Approach for Knowledge Quality Assessment: An Example of the Military Marksmanship Simulator-Based Training

王瑞德(Jui-Te Wang) ； 林永裔(Yung-I Lin) ； 簡定華(Ding-Hua Jian) ； 侯昰佑(Shi-You Hou) ； 陳奇逸(Ji-Yi Chen) ； 陳卉怡(Hui-Yi Chen)

《品質學報》 20卷3期 (2013/06) Pp. 251-273

https://doi.org/10.6220/joq.2013.20(3).01

摘要

由於知識經濟時代來臨，為因應日趨複雜以及多變的商業環境，企業內之員工必須擁有專業的知識與能力來應對；而如今科技大幅演進，造就了模擬訓練之崛起，不僅協助企業解決新興的訓練挑戰，亦創造了其他教學媒介無法提供之教學優勢，但發展至此，對於模擬訓練績效的研究，始終無法成功且有效地掌握模擬訓練的優勢，主要因為學習者通常無法準確地評估學習後的自身「知識品質」。本研究主要目的在運用資料探勘技術並結合信心基礎學習理論，來評量學習者的知識品質，進而改善學習者的學習或訓練績效，以減少員工作業或決策上的錯誤，並提升工作績效。依據信心基礎學習理論，使用「知識程度」和「信心程度」兩項構面來評估學習者所習得的知識品質，並應用群集分析與決策樹方法來找出影響學習或訓練績效的關鍵因子，並評估學習者的學習績效，以即時提供改善建議。研究結果顯示，結合信心基礎學習理論可提升知識品質與學習績效評估的準確率，另外，本研究所提出的方法，可在模擬學習環境中幫助決策者（或學習者）評量學習者的知識品質，了解優秀學習者與其他學習者之主要差異，藉此定義優秀訓練者主要的學習行為模式，以建立更有效率的學習環境，以提升訓練成效。本研究以國軍步槍射擊模擬器訓練為例。

關鍵字

知識品質 ； 資料探勘 ； 信心基礎學習理論 ； 模擬訓練 ； 學習評量

並列摘要

In the age of knowledge economy, business employees need to have competent expertise to be survived in a rapidly changing business environment. Due to the advance of new technologies, many organizations have utilized the simulation-based training, which provides numerous benefits better than traditional training approaches, to improve their human resource training to meet the challenge. However, many organizations still cannot fully utilize the advantages of simulation-based training, because it is difficult to evaluate the knowledge quality of a learner using the simulation-based training. The objective of this research is to develop a data mining approach integrated with the theory of confidence-based learning to assist decision makers in evaluating learners' knowledge quality. Based on the theory, knowledge quality of a learner is measured by two dimensions: knowledge and confidence. According to the data collected from questionnaire and simulation-based training, this research applies the clustering analysis and the decision tree analysis to determine key factors that influence the performance of simulation-based training. In addition, the decision rules generated from the decision tree analysis can be used to assess knowledge quality of a learner during the simulation-based training. From the experimental results, it shows that the proposed methodology can help decision maker understand and determine superior learning behaviors and assess learners' knowledge quality. The proposed methodology is illustrated with an example of a rifle simulation-based training.

並列關鍵字

knowledge quality ； data mining ； confidence-based learning ； simulation-based training ； learning evaluation

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