員工之任務科技適配度對於數位學習之學習成果與培訓遷移的影響

Abstract

本研究的目的是探討任務科技適配度對於員工數位學習之學習成果與培訓遷移的影響。本研究透過個案研究了解公司對於新聘人員設計的數位學習課程，並檢視該課程與新聘人員的工作任務適配程度。此研究之樣本為S公司的151位在2011年六月至八月招募的新人。本研究為量化研究，問卷是基於Goodhue及Thompson於 1998年設計的任務科技適配量表以及Felder及Soloman設計的學習型態量表加以修改。 學員學習資料如課程成績以及培訓遷移成績皆由S公司提供。本研究針對Goodhue的任務科技適配量表進行因素分析，結果顯示，該量表可粗分為三個面向：內容面、科技面及資料呈現面。本研究的假設則是藉由迴歸分析加以驗證；其中任務科技適配度分別對於學習成果及培訓遷移有正向關係，然而對於學習型態是否具有影響科技適配度與學習成果之間的關係的假設，則因樣本間的變異量不足而於本研究中不成立。

The purpose of this study is to explore how task technology fit (TTF) of e-learning influences employees’ learning and training transfer. Through an empirical study of a case company’s e-learning program for new recruits, this research examines whether the fit between the e-learning technology and employees’ realistic tasks has an effect on employees’ learning effectiveness. To fulfill the study objectives, the researcher worked with one of the largest real estate agencies in Taiwan, which was nicknamed the S Company for anonymity, to collect data needed. Survey questionnaires containing demographics, measures of visual-verbal learning style and task technology fit of e-learning were administered to S Company’s 151 new real estate agents who completed the training for new-hires in the period between June and August of 2011. Data for the outcome variables of the study, the e-learning test scores and the training transfer scores of each trainee were provided by the S company. Exploratory factor analysis result showed the factor structure of the TTF measure to be composed of three distinct components: content, technology and presentation of e-learning. Hierarchical regressions were used to test the direct effect of TTF on learning outcome and training transfer, as well as the mediating effect of learning outcome between TTF and training transfer. These hypotheses were supported which implied the importance of ensuring TTF when using e-learning to train employees. The moderating effect of visual-verbal learning style on the TTF-learning outcome connection, however, was not supported, due to small variances in agents’ homogeneous learning style.