學習管理系統之分析與運用研究 ─以某跨國半導體設備H公司為例

NCUIR > School of Management at National Central University > Executive MBA > Electronic Thesis & Dissertation > Item 987654321/98002

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/98002

Title:	學習管理系統之分析與運用研究 ─以某跨國半導體設備H公司為例
Authors:	黃若綺;HUANG, JUO-CHI
Contributors:	高階主管企管碩士班
Keywords:	學習管理系統;數位學習;組織學習;半導體產業;Learning Management System (LMS);Digital Learning;Organizational Learning;Semiconductor Industry
Date:	2025-06-04
Issue Date:	2025-10-17 12:14:46 (UTC+8)
Publisher:	國立中央大學
Abstract:	隨著數位轉型浪潮席捲全球，企業組織對於員工專業能力提升、知識管理與跨區域學習協作的需求日益增加。學習管理系統(Learning Management System, LMS)作為企業數位學習的關鍵平台，已不再僅是訓練工具，而是整合人力資源、強化組織競爭力的重要基礎設施。為因應此趨勢，本研究以跨國半導體設備製造龍頭企業H公司為個案，透過文獻探討與假設性案例分析法，系統性檢視其學習管理系統的應用現況與優化潛力。本研究從技術功能、使用情境與組織支持三個構面切入，分析H公司現行學習管理系統的運作成果與挑戰。本研究結果顯示，該系統已建置課程管理、學習地圖、測驗與評估、學習歷程追蹤及報表分析等完整模組，並初步整合人力資源資訊系統，展現出可支援全球學習規模化的潛能。然而，在實務應用上，系統面臨學習內容更新不即時、課程互動性薄弱、跨地區操作體驗不一致等問題，影響整體學習參與度與推動效率。為因應上述問題並強化學習管理效益，本研究提出四項具體結論，包括：第一是系統基礎穩定但仍需強化即時性、互動性與全球一致性；第二是使用者高度期待友善介面與智能推薦功能；第三是學習管理系統優化策略應導入人工智慧推薦、敏捷課程管理、數據儀表板與KPI整合；第四是學習效能推動應整合技術、制度與文化三位一體，尤其需強化主管參與與學習文化建構。在此基礎上，本研究亦提出五項實務建議：第一是建構以職能為基礎的學習地圖，強化學習與職務對接；第二是導入人工智慧與數據分析模組，提升學習推薦精準度與成效評估效率；第三是建立課程敏捷更新與在地化適配機制，強化全球一致性與學習相關性；第四是設計制度化推動與績效串聯機制，提升學習與企業目標間的連結；第五是深化社群互動與學習文化，運用遊戲化與協作機制提升學習參與與跨部門知識流動。本研究亦揭示研究限制：其一，研究對象限於單一企業，樣本以中高階主管為主，限制視角多元性；其二，欠缺量化資料與學習成效指標佐證；其三，尚未實際建置KPI追蹤模組與數據分析平台。基於此，未來可從以下方向擴展：一、深入探討人工智慧推薦機制對學習成效之實質影響；二、進行跨產業與跨區域比較研究；三、建構學習管理系統學習成效評估模型；四、探索學習文化於系統導入過程中的中介機制，進而建立具地域適應性的文化強化策略。整體而言，本研究有助於提升H公司學習管理系統在全球營運與人才發展上的應用價值，亦可作為半導體產業及其他高科技企業規劃與優化數位學習策略之理論依據與實務參考。 ;With the wave of digital transformation sweeping across the globe, enterprises are facing growing demands for enhancing employee competencies, managing knowledge, and fostering cross-regional learning collaboration. The Learning Management System (LMS), as a critical platform for corporate digital learning, has evolved beyond a mere training tool to become a foundational infrastructure that integrates human resources and strengthens organizational competitiveness. In response to this trend, this study adopts a case analysis of H Company, a leading multinational semiconductor equipment manufacturer, using literature review and hypothetical case analysis methods to systematically examine the current application and optimization potential of its LMS. This research analyzes the operational performance and challenges of H Company’s LMS from three dimensions: technical functionality, user scenarios, and organizational support. Findings reveal that the system has established comprehensive modules, including course management, learning maps, testing and evaluation, learning progress tracking, and reporting analytics. The system has also begun integrating with human resource information systems, demonstrating potential for supporting global-scale learning. However, in practice, the LMS faces issues such as untimely content updates, limited course interactivity, and inconsistent cross-regional user experiences, all of which hinder learning engagement and implementation effectiveness. To address these issues and enhance LMS efficiency, the study proposes four key conclusions: (1) while the system foundation is stable, improvements are needed in timeliness, interactivity, and global consistency; (2) users strongly expect a more user-friendly interface and intelligent recommendation functions; (3) LMS optimization strategies should incorporate AI-driven recommendations, agile course management, data dashboards, and KPI integration; (4) learning effectiveness should be promoted through a triad of technology, institutional support, and cultural alignment, with special emphasis on managerial engagement and the development of a learning culture. Based on these findings, the study further provides five practical recommendations: (1) build a competency-based learning map to strengthen the alignment between learning and job roles; (2) adopt AI and data analytics modules to improve recommendation accuracy and evaluation efficiency; (3) establish agile course updates and localized adaptation mechanisms to ensure global consistency and content relevance; (4) design institutional mechanisms that link learning with performance outcomes to reinforce alignment with corporate goals; (5) deepen social learning and cultivate a learning culture by leveraging gamification and collaborative mechanisms to boost engagement and cross-departmental knowledge flow. This study also acknowledges several limitations: first, the research focuses on a single company with samples mainly consisting of mid- to senior-level managers, limiting the diversity of perspectives; second, it lacks quantitative data and performance metrics to substantiate learning outcomes; third, a KPI tracking module and data analytics platform have yet to be fully implemented. Future research may explore: (1) the concrete impact of AI-driven recommendations on learning effectiveness; (2) cross-industry and cross-regional comparative studies; (3) the development of an LMS learning outcome evaluation model; (4) the mediating role of learning culture in system implementation, thereby establishing culturally adaptive reinforcement strategies. Overall, this research contributes to enhancing the global application value of H Company’s LMS in operations and talent development and serves as both a theoretical foundation and practical reference for digital learning strategy planning and optimization in the semiconductor and broader high-tech industries.
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