知易行難：以施行理論觀點探索數位學習導入失敗

Easier Said Than Done: Exploring e-Learning Failure Case Based on Theory-in-Use Perspective

朱彩馨(Tsai-Hsin Chu) ； 李慶芳(Ching-Fang Lee) ； 許致嘉(Chih-Chia Hsu)

《中山管理評論》 22卷4期 (2014/12) Pp. 857-900

https://doi.org/10.6160/2014.12.06

摘要

近年來，愈來愈多的企業導入數位學習科技，期盼能夠提升員工能力與保存組織知識。許多文獻提出關鍵成功因素，希望促使數位學習的成功。然而，取得關鍵成功因素並不能確保成功地導入數位學習。因為組織往往並非不知曉關鍵成功因素，而是又緣於種種因素而無法實行。因此，數位學習失敗，可視為一種組織變革失敗的現象，乃因於組織成員無法改變舊有的學習習慣，來適應新的學習模式。本研究以一個數位學習失敗的個案，來了解組織為何知易行難。也就是說組織為何明知該實行關鍵成功因素卻無法執行之。細部而言，本研究基於Ａrgyris & Schön（1996）的雙環學習理論，檢視個案組織中既存的施行理論如何致使數位學習的失敗。而研究結果發現了五種導入數位學習時的組織施行理論，這些施行理論形成了認知與做法的障礙，最終致使數位學習失敗。本研究提醒施行理論的重要性，並提供組織導入數位學習的一個新視角。

關鍵字

數位學習失敗 ； 組織學習 ； 施行理論 ； 雙環學習

並列摘要

More and more organizations introduce an e-learning system with an expectation to enhance employee's capacities, as well as to manage organizational knowledge capital. Many critical success factors (CSFs) are suggested to help elearning implementation. However, research reports that to have CSFs cannot guarantee a successful e-learning implementation. An e-learning project fails because organizations cannot execute the CSFs for some reasons. In organizational learning perspective, an unsuccessful e-learning implementation can be a failure of organizational learning because the organization members cannot alter their old way of learning to the new one. Anchored on an e-learning failure case, this study explores the reason why an organization fails to introduce an e-learning system. Specifically, by Argyris & Schön's (1996) double-loop learning theory, we seek satisfying answers by examining the existing theory-in-use in the organization. Our findings unfolded five theories in-use embedded in e-learning implementation. These theories in-use created barriers in both cognition and action, thus resulted in the failure of the e-learning project. This study highlights the importance of theory in-use, and provides a new perspective and insights to understand e-learning implementation failure.

並列關鍵字

e-learning failure ； organizational learning ； theory in-use ； double-loop learning

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