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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/87063


    題名: 探討獎章機制與英語發音能力對英語發音學習成效、遊戲成效、學習動機、遊戲心流及行為模式之影響──以大型多人線上角色扮演遊戲為例;Effects of Digital Badge Mechanisms and English Pronunciation Ability on English Pronunciation Performance, Gaming Performance, Learning Motivation, Gaming Flow and Behavioral Patterns: A Case of MMORPG
    作者: 彭琮樺;Peng, Cong-Hua
    貢獻者: 網路學習科技研究所
    關鍵詞: 數位遊戲式學習;數位獎章機制;先備能力;英語發音學習成效;遊戲成效;學習動機;遊戲心流;行為模式;digital game-based learning;digital badge mechanisms;Prior ability;English pronunciation performance;gaming performance;learning motivation;gaming flow;behavioral pattern
    日期: 2021-08-23
    上傳時間: 2021-12-07 14:39:09 (UTC+8)
    出版者: 國立中央大學
    摘要: 這個全球化的世代中,英語是一項在國際上溝通必須具備的技能。學習英語對於母語為中文的學習者是個具有挑戰性的課題,尤其是英語口說及發音,在傳統的英語教學環境下,通常缺乏接近真實的英語對話練習環境。近期越來越多研究使用數位遊戲式學習進行英語發音教學,使學習的過程充滿樂趣,同時輔助學習者提高其學習動機與學習成效。在數位遊戲式學習的環境中,數位獎章機制所提供的獎章目標有助於提升學習者進行學習活動的意願,在追求獎章條件目標的過程中,能有效地使學習者更熱忠及沉浸於學習活動。然而獎章不總是對學習是正面影響,獎章可能會產生造成將學習活動的重點從學習轉移至收集獎章的負面影響,因此過去有些研究開始使用不可預期的獎章或成就,避免讓學習者是為獲得獎章而學習。然而,有關於探討不可預期特性的獎章應用於教育的研究很少,大部分為應用在線上學習或課堂,尚未發現將不可預期獎章應用於數位遊戲式學習上並結合英語發音學習,以及比較與可預期獎章對學習者的影響,也有一些研究提到在可預期獎章中加入些許不可預期獎章,以提高學習者的興趣,因此本研究開發結合英語發音的線上角色扮演之遊戲式學習系統「傳奇島冒險」,並且在本系統中設計了不同預期特性獎章機制的學習環境,分別是可預期獎章版、不可預期獎章版及可預期加不可預期獎章版。本研究旨在數位遊戲式英語發音學習環境中,探討不同獎章機制對學習者其英語發音學習成效、遊戲成效、學習動機、遊戲心流及行為模式之影響及各變項之相關性,同時探討不同英語發音能力的學習者,在相同的學習環境中對英語發音學習成效、遊戲成效、學習動機、遊戲心流之影響。
    本研究共有60位學習者,將其依照不同獎章機制分為三組(可預期獎章組、不可預期獎章組及可預期加不可預期獎章組),各組分別均有20人,並再進一步使用英語發音能力分組,三組中的高低英語發音能力的學習者分別各10人,研究工具包含英語發音學習成效測驗卷、學習動機量表、遊戲心流量表及系統紀錄檔。根據本研究的實驗結果表明,在線上角色扮演的數位遊戲式英語發音學習環境下,不同獎章機制對學習者的影響,主要發現有以下五點(1)不同獎章機制組的學習者其英語發音學習成效皆顯著進步,然而在後測及進步分數的例句,則分別為可預期加不可預期獎章組及可預期獎章組好於不可預期獎章組;(2)可預期加不可預期獎章組的遊戲成效最好,其次是可預期獎章組,最後是不可預期獎章組;(3)在學習動機及遊戲心流,各組皆無呈現顯著差異;(4)可預期獎章組與可預期加不可預期獎章組的行為模式大致相同,僅不可預期獎章組有呈現幾項的獨有行為轉移,各組的行為轉移總數皆差不多;(5)可預期獎章組的英語發音學習成效與獎章類遊戲成效之間呈現最多的相關性,不可預期獎章組為英語發音學習成效與學習類遊戲成效之間呈現最多的相關性,可預期加不可預期獎章組則最少,然而三組的學習動機與遊戲心流皆無呈現顯著相關性。
    在線上角色扮演遊戲的數位遊戲式英語發音學習環境下,不同獎章機制對不同英語發音能力學習者的影響,主要發現有以下三點(1)不同獎章機制組內的不同英語發音能力學習者其英語發音學習成效皆顯著進步;(2)可預期獎章組內的不同英語發音能力學習者其遊戲類、獎章類及輔助類遊戲成效的顯著差異最多。不可預期獎章組內的不同英語發音能力學習者其學習類遊戲成效的顯著差異最多。可預期加不可預期獎章組僅在學習類遊戲成效的整個學習任務準確率90%達次數呈現顯著差異,以上結果皆為高能力學習者大於低能力學習者;(3)在學習動機及遊戲心流,各組學習者皆無呈現顯著差異。
    本研究的結果有助於在數位遊戲式學習結合英語發音學習的研究者在設計遊戲中的獎章機制時,提供未來的研究方向。此外,本研究開發的系統,也能提供給未來教學者應用不同獎章機制於不同的教學環境中。
    ;In this globalized generation, English is a necessary skill for international communication. Learning English is a challenging task for native Chinese learners, especially English speaking. In the traditional English classroom, there is usually a lack of native environment for practicing speaking English. Recently, more and more research has been conducted on the use of digital game-based learning for English speaking instruction to make the learning process fun and to help learners improve their motivation and learning outcomes. In digital game-based learning environment, digital badge mechanisms provide goals of badges that support learner to increase willingness to engage in learning activities because the process of achieving goals of badges can effectively immerse learners in learning. However, badges are not always a positive effect on learning. Badges may have negative effects that will shift the focus of learning activities from learning to collecting badges. Therefore, there were few researches on the application of badges to education for unexpected characteristics, most of which are applied to online learning or the classroom. We have not found the application of unexpected badges to digital game-based English pronunciation learning, and compared the effects of expected badge on learners. In addition, some studies mentioned adding some unexpected badges on the expected badges to increase learners′ learning interest. In this study, we developed a game learning system called "Legends Island Adventure", which combines English pronunciation learning with MMORPG, and designed learning environments for different badge mechanisms with different characteristics of expectancy, namely, expected badge mechanism edition, unexpected badge mechanism edition, and expected and unexpected badge mechanism edition. The purpose of this study is to explore the effects and correlation of different badge mechanisms on learners′ English speaking learning performance, game performance, learning motivation, gaming flow experience, and behavior patterns in a digital game-based English speaking learning environment, and to investigate the effects of different prior knowledge on learners′ English pronunciation learning performance, gaming performance, learning motivation, and gaming flow experience in the same learning environment.
    A total of 60 learners in this study are divided into three groups (expected badge group, unexpected badge group, and mixed expected badge group). According to different digital badge mechanisms, there were 20 students in each digital badge mechanism group. Furthermore, each digital badge mechanism group was divided into subgroups by English pronunciation ability. In the three groups, there are 10 learners of high English pronunciation ability and 10 learners of low English pronunciation ability. The research tools in this study included English pronunciation learning performance test, learning motivation scale, flow exprience scale and system log file. According to the results of this study, in the MMORPG-based digital game-based English pronunciation learning environment. The effects of different digital badge mechanisms on learners are mainly found as follows: (1) learners in different badge groups improved significantly in English pronunciation learning performance. However, in post-test and improvement scores, the mixed expected badge group and the expected badge group were significantly better than the unexpected badge group. (2) In the results of the gaming performance, expected and unexpected badge group was the best, followed by the expected badge group and the unexpected badge group. (3) There was no significant difference in learning motivation and gaming flow among all groups. (4) The behavior patterns of the expected badge group were roughly the same as that of the expectable plus unexpected medal group. Only the unexpected badge group showed several unique behaviors shifts, and the total number of behaviors shifts of each group was similar. (5) The expected badge group showed the most correlations between English pronunciation learning effectiveness and medal-like game effectiveness, the unexpected badge group showed the most correlations between English pronunciation learning effectiveness and learning game performance, and the mixed expected badge group showed the least correlations. However, none of the three groups showed significant correlations between learning motivation and game mind flow.
    In the MMORPG-based digital game-based English pronunciation learning environment, the effects of different badge mechanisms on learners with different English pronunciation ability are mainly found as follows: (1) The results of English pronunciation performance of learners with different pronunciation abilities in different badge groups were significantly improved. (2) The results of gaming, badging and assistance categories gaming performance showed the most significant differences in the expected badge group. The number of significant differences in learning categories gaming performance of different English pronunciation ability learners in the unexpected badge group is the most. The expected badge group and the unexpected badge group only showed a difference in the total learning task accuracy of 90% of the learning category gaming performance. All the above results showed that the high English pronunciation ability learners were greater than the low English pronunciation ability learners
    The results of this study will be helpful for researchers who combine digital game-based learning with English pronunciation learning to design the badge mechanism in games and provide future research directions. In addition, the system developed in this study can also provide future researchers with different badge mechanisms in different teaching environments.
    顯示於類別:[網路學習科技研究所 ] 博碩士論文

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