網路自學模式與傳統自學模式比較研究

dc.contributor黃能堂zh_TW
dc.contributorDr. Neng-Tang Huangen_US
dc.contributor.author陳一明zh_TW
dc.contributor.authorI-Ming Chenen_US
dc.date.accessioned2019-09-03T11:33:48Z
dc.date.available2006-7-10
dc.date.available2019-09-03T11:33:48Z
dc.date.issued2006
dc.description.abstract本研究旨在探討網路自學模式與傳統自學模式學習成效之差異,為達成研究目的,本研究採用文獻分析與準實驗研究之不相等控制組設計,依立意取樣選取輔仁大學貿經系二年級之兩個班級為研究對象進行英語商務溝通自學模式教學課程。經教學實驗後,利用平均數、標準差、t檢定、共變數分析(ANCOVA)、單因子變異數分析(ANOVA)、Tukey事後比較等方法進行資料分析,最後得到以下結論: 一、 實驗組學生在英語商務溝通自學單元之學習成效顯著高於控制組之學習成效。 二、 不同性別在英語商務溝通自學單元之學習成效上並無顯著差異。 三、 實驗組學生對網路自學模式之學習滿意度持有正面的反應。zh_TW
dc.description.abstractThe main purposes of this study were to explore the theories of Autonomous learning, Language acquisition, and Web-based instruction, to compare the learning effectiveness of web-based autonomous learning model and conventional autonomous learning model, and to investigate students’ learning attitude toward web-based autonomous learning model. The methodologies of literature review and the quasi-experiment research were used in this research. The collected data was analyzed by statistic methods such as mean, sum of square, t-test, one-way ANOVA, ANCOVA, and Tukey post-hoc comparison. The major findings of this study were as follows: 1. The experimental group had significant higher mean achievement test score than the control group. 2. There was no significant difference between genders in learning achievement. 3. The experimental group had positive atttitude toward web-based autonomous model learning.en_US
dc.description.sponsorship科技應用與人力資源發展學系zh_TW
dc.identifierGN0692710071
dc.identifier.urihttp://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22GN0692710071%22.&%22.id.&
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/96686
dc.language中文
dc.subject網路自學模式zh_TW
dc.subject學習成效zh_TW
dc.subject學習滿意度zh_TW
dc.subjectweb-based autonomous learningen_US
dc.subjectlearning achievementen_US
dc.title網路自學模式與傳統自學模式比較研究zh_TW
dc.titleA Study of Comparison of Web-based Autonomous Model and Conventional Autonomous Modelen_US

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