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    题名: 在真實情境下結合圖像與位置辨識促進英文寫作;Facilitating EFL Writing with Image and Location Recognitions in Authentic Context
    作者: 潘思羽;Pan, Ssu-Yu
    贡献者: 網路學習科技研究所
    关键词: EFL 寫作;真實情境;圖像轉文字辨識技術;位置轉文字辨識技術;情境化與真實社會化機制;EFL writing;authentic context;Image-to-text recognition;Location-to-text recognition;contextualization and authentic socialization mechanism
    日期: 2023-07-12
    上传时间: 2024-09-19 16:56:49 (UTC+8)
    出版者: 國立中央大學
    摘要: 近年來隨著教學理念和方法的不斷發展,現代的英文教學更加注重學生的主動參與、互動性、情境導向和實際應用,以提高學生的學習成效和應用能力。另外,英文寫作一直是EFL學習的一大挑戰,學習者需要具備足夠詞彙量,以及對語法和句構的清楚觀念,才能準確的傳達思想。因此,科技推動下,過去已有許多研究使用辨識技術來為在真實情境進行的EFL寫作提供協助,然而仍然缺乏如何將情境化與社會化與識別技術做整合,來為學習者在真實情境中的英文寫作提供更多協助。在本研究中,研發了一個手機應用程式—Advanced AuthWrite,整合了情境化(Contextualization)、真實社會化機制(Authentic Socialization mechanism)、進階圖像轉文字辨識技術(Advanced Image-to-text recognition, Advanced ITR)及進階位置轉文字辨識技術(Advanced Location-to-text recognition, Advanced LTR),為學習者的真實情境英文寫作提供幫助。進階的辨識技術根據圖像和位置的辨識結果,為學習者分類並提供不同難易度的相關單字;真實社會化讓學習者與同儕能根據寫作內容、ITR圖像及LTR地點進行交流和溝通,進而改進文章。
    本研究將34名高職生分成兩組進行十二週的實驗活動。實驗共有兩個階段,第一階段探討利用進階ITR與LTR進行情境化學習對EFL寫作的影響,第二階段則是探討真實社會化機制對EFL寫作的影響。結果顯示,第一階段使用進階ITR及LTR的情境化學習中,進階ITR圖像有助於激發學習者更多的寫作靈感,而進階LTR地點也藉由ITR圖像產生中介作用,幫助學習者更適當的處理寫作主題,使得他們的寫作表現有所提升;在第二階段,同儕們透過真實社會化機制提供給學習者的鼓勵性評論激勵了學習者為他們的文章闡述更詳細的內容,此外,較進階的ITR詞彙對EFL寫作表現有明顯的影響,他們能更正確的將自己的想法透過文字傳達出來。這意指利用進階ITR和LTR進行情境化學習整合真實社會化機制,能更進一步的幫助學習者的EFL寫作,寫出更有意義的內容,獲得更好的寫作表現。;As teaching philosophies and methods continuously develop recently, current English teaching focuses more on the positive engagement of learners, interactivity, contextual guidance, and practical application in order to improve learners′ learning achievement and application ability. In addition, English writing has always been a challenge for EFL learners, who need to have sufficient vocabulary and a clear understanding of grammar and sentence structure in order to convey their thoughts accurately. Consequently, many previous studies have been conducted using recognition technologies to facilitate EFL writing in authentic contexts, however, there is still a lack of how to integrate contextualization and socialization with recognition technologies to help learners write EFL writing in authentic contexts more effectively. In this study, a mobile application-Advanced AuthWrite-was developed to integrate Contextualization, Authentic Socialization mechanism, Advanced Image-to-text recognition (Advanced ITR), and Advanced Location-to-text recognition (Advanced LTR) to support learners′ English writing in real-life situations. Advanced recognition technologies categorize and provide learners with relevant vocabularies at different levels of difficulty based on the recognition of images and places; authentic socialization allows learners to communicate with their peers based on their writing content, ITR images, and LTR places to improve their essays.
    In this study, a total of 34 vocational high school students were divided into two groups for a 12-week experimental activity. The experiment was conducted in two stages. The stage 1, we studied the influence of using advanced ITR and LTR for contextualizing learning on EFL writing, while in stage 2, we investigated the effects of authentic socialization mechanisms on EFL writing performance. The results revealed that in stage 1, using advanced ITR and LTR for contextualization writing, advanced ITR images helped to inspire more ideas, while advanced LTR places have a mediation effect through ITR images to help learners address the writing topic more appropriately and enhance their writing performance; in stage 2, through authentic socialization mechanisms, the encouragement provided to learners by peers motivated learners to explain more details in their essays. Also, the advanced ITR vocabulary had a significant impact on EFL writing performance, as they were able to convey their thoughts more accurately through the texts. Therefore, the integration of authentic socialization mechanisms and advanced ITR and LTR for contextualization learning can effectively facilitate learners′ EFL writing, to write more meaningful content and achieve better writing performance.
    显示于类别:[網路學習科技研究所 ] 博碩士論文

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