國際人力資源發展研究所

Permanent URI for this communityhttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/118

∥ 系所沿革

在全球化潮流下，國際人力資源的發展更趨重要。相對地，國際人力資源專業工作者的培育需求也必然更顯迫切。在此背景下，國立臺灣師範大學「國際人力教育與發展研究所」(Graduate Institute of International Workforce Education and Development, IWED)於民國九十二年（九十二學年度）成立，隸屬於科技學院；於民國九十八年(九十八學年度)更名為「國際人力資源發展研究所」(Graduate Institute of International Human Resource Development, IHRD)，並改隸國際與僑教學院。民國一百零三年(壹零三學年度)，國際與僑教學院與社會科學院合併後更名為國際與社會科學院。

∥ 系所特色

本所成立於民國九十二年，為全國第一所採用全英語授課，並同時招收本國籍與國際學生的系所。以培育國際企業、各國政府機構及國際性非營利組織人力資源規劃與管理專業人才為目標。本所的成立及發展正是反映前述時勢所趨，希望成為引領此領域之先驅，提供學生發展成為國際化人力資源專業人才的基礎和專業課程，以培養其具備進入全球化職場的素養和關鍵知能，學生在畢業後授予管理學碩士學位(MBA Degree)。

本國學生的招生方式包含推薦甄選及碩士一般生考試，考試科目為「管理學」和「英文」；國際學生的招生方式為申請入學和僑生海外聯招。國際化是我們的一大特色，除了師大的學習環境之外，本所與美國伊利諾大學香檳分校University of Illinois at Urbana Champaign (UIUC)長期學術合作，學生在完成課程且通過甄選後，可申請赴UIUC擔任訪問學生，提供學生多元學習的環境與機會。

∥ 本系教育目標

一、培育人力資源發展與管理之專業人才。

二、培育國際化與跨文化管理之專業人才。

∥ 歷屆學生來源

本所歷屆的學生來源除本國學生外，包括美國、加拿大、巴拿馬、貝里斯、宏都拉斯、尼加拉瓜、聖露西亞、薩爾瓦多、玻利維亞、聖克里斯多福、海地、法國、西班牙、波蘭、羅馬尼亞、匈牙利、捷克、波斯尼亞、塞內加爾、拉脫維亞、俄羅斯、布吉納法索、甘比亞、馬拉威、史瓦濟蘭、印度、泰國、菲律賓、印尼、日本、蒙古、越南等國。學生在大學主修有商管、經濟、心理、教育、外語、政治、社會、英語、中文、及工業設計等等，十分多元，是一個真正國際化的學習場域。

∥ 學生未來出路

本所國內畢業生英語文能力及人資專業在各界備受肯定，且畢業生遍佈知名企業如：台積電、台達電、宏達電、鴻海集團、緯創、台電公司等知名企業；此外，學生也可朝公務體系發展，或繼續深造博士學位。

外籍學生中，外交部國合會推薦學生大多為各邦交國官員，畢業返國後通常擔任該國人力資源發展之重要職務。

∥ 師資

目前本所的師資係結合了六位本所專任教師，以及多位兼任教師共同投入及組成本所堅強優秀教學陣容，每一位教師皆擁有國內外著名大學博士學位，不但能以英語授課，學術涵養亦十分深厚。未來將持續努力透過傅爾布萊特獎助（Fulbright Grant）計畫與本校學術交流交換等管道，禮聘客座教授或交換教授於本所任教。

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系所網址：http://www.ihrd.ntnu.edu.tw/main.php

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Effects of the Heterogeneity of Game Complexity and User Population in Learning Performance of Business Simulation Games.
(Elsevier, 2012-12-01) Tao, Y.; Yeh, C.R.; Hung, K.C.
Previous studies on business simulation games (BSGs) have concluded that improved performance may not be the primary benefit of using BSGs, due to mixed results between student performance and perceptions. Two relevant and insightful issues attract our attention, namely, the impacts of the heterogeneous student population and the different complexity levels of BSG software. To address these issues, the present study aims to understand the relationship between student profile/characteristics and performance in the classroom with BSG-facilitated learning. An in-depth case study is conducted on a general college course designed to teach three different complexities of BSGs to students enrolled in different majors. Four student profile factors are individually tested for differences in performance scores as evaluated by the teacher. Additionally, the influences of 11 student characteristics are assessed with regard their self-reported perceived learning performances. Regression analysis and ANOVA are used to investigate the impacts of heterogeneous users and game complexity on student performance. Based on the regression analyses of the data collected from 43 respondents who participated in the general course, the study concludes that knowledge and skill may influence the heterogeneous student population; moreover, student participation and tacit learning preference improve performance, and students with an auditory learning preference or high learning motivation may not perform well in classroom BSG learning. However, the low value of adjusted R square implies that more dimensions or variables are needed to increase the explaining power of the performance scores in the regression analyses. In contrast, heterogeneous BSG software with different complexity levels present different results. The current research contributes practical and incremental knowledge on the complexity of heterogeneous BSG software on performance scores and the perceived learning performance of heterogeneous student populations. With the research limitations acknowledged, a series of suggestions for teachers pertaining to appropriate applications of BSGs in classes is offered as well as recommendations to BSG providers. Nevertheless, in-depth analyses are required, preferably with larger student population samples, to further explore the insignificant relationship between student perceptions and attitude under nonlinear extended complexity.