博碩士論文 etd-0624117-104105 詳細資訊


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姓名 蘇韋丞(Wei-cheng Su) 電子郵件信箱 lucky1994@gmail.com
畢業系所 資訊管理學系研究所(Information Management)
畢業學位 碩士(Master) 畢業時期 105學年第2學期
論文名稱(中) “Coding Peekaboom”-網頁遊戲導向程式語意標記系統
論文名稱(英) “Coding Peekaboom” Game-Based Programming Semantic Tagging System
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    紙本論文:3 年後公開 (2020-07-24 公開)

    電子論文:使用者自訂權限:校內 3 年後、校外 3 年後公開

    論文語文/頁數 英文/61
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    摘要(中) 在這個研究中,我們將向各位介紹一個以網頁遊戲為開發基礎的程式語意標記系統-"Coding Peekaboom"。對學習程式語言有興趣的人,在自己練習題目中經常面臨許多問題,為了幫助程式語言學習者辨識他們所面對的程式問題,我們設計了"Coding Peekaboom"系統來收集程式碼和程式撰寫問題的概念標籤。除此之外,我們也想知道基於遊戲的群眾外包機制,除了應用在像是標記圖片等一些比較普遍的領域之外,是否真的能夠適用在諸如收集程式語言概念這種特定的領域;另外,"Coding Peekaboom"的遊戲機制是否能吸引參與者願意持續地在這樣需要具備程式語言基礎的工作中完成群眾外包任務?實驗結果顯示,藉由"Coding Peekaboom"收集到的語意概念標籤,其品質是相當優秀的,這個結果證明了群眾外包運用在如此特定領域的可靠性。另外,我們也在實驗中使用了腦波儀來觀察受測者的腦波以探討遊戲機制是否能提高參與者參與的心流體驗。腦波分析以及問卷結果顯示他們在實驗過程中相當有可能已經進入心流狀態,使受測者持續沉浸在遊戲中,這樣的機制也讓參與者願意留在這特定、複雜的領域中,並且想要完成更多題目。在未來,我們能藉由"Coding Peekaboom"收集到的資料,應用於自動識別每段程式碼其所包含的概念,並幫助程式語言學習者,特別是新手,能夠有效地辨識他們目前所遇到的問題與協助其找到合適的解決方案,讓程式語言學習者能夠擁有更順暢的學習體驗。
    摘要(英) This study introduces a game-based semantic tagging system, “Coding Peekaboom”, to collect the concepts of a piece of code. People who are interested in learning programming skills often face many problems while practicing by their own. To help programming learners identify the problems they encountered, this study developed a crowdsourcing game, “Coding Peekaboom”, for collecting programming concepts of pieces of code and programming questions to examine whether a game-based crowdsourcing mechanism can really be adopted in such specific domain, and whether the game-based mechanism can make participants be willing to join and continue the identify concepts tasks. An experiment has been conducted to collect the programming concepts from “Coding Peekaboom” with EEG device. “Coding Peekaboom” shows a great result in concepts quality with 94% in average of correct concept coverage. The brainwave analysis and questionnaire results show that participants are likely to enter a state of flow with the kind of game-based mechanism. With the high quality programming concepts collected from “Coding Peekaboom”, the study can further investigate concept recognition of each piece of code to help programming learners, especially novices, find the solutions to their questions efficiently and effectively.
    關鍵字(中)
  • 腦波儀
  • 遊戲
  • 標籤
  • 程式語意
  • 群眾外包
  • 心流理論
  • 關鍵字(英)
  • Game
  • Flow experience
  • EEG
  • Labeling
  • Segmentation
  • Programming annotation
  • Crowdsourcing
  • 論文目次 論文審定書 i
    ACKNOWLEDGEMENT ii
    中文摘要 iii
    ABSTRACT iv
    Table of Content v
    1. INTRODUCTION 1
    2. RELATED STUDY 7
    2.1 Crowdsourcing tagging 7
    2.2 Game-based crowdsourcing system 9
    2.3 Flow theory 11
    2.4 Concepts quality 14
    3. CODING PEEKABOOM DESIGN 16
    4. METHODOLOGY 22
    4.1 Participants 22
    4.2 Apparatus 23
    4.3 Experiment Setup 24
    4.4 Evaluation Instrument 27
    5. RESULT 32
    5.1 Concepts quality 32
    5.2 Flow experience in the game 37
    5.2.1 Brainwaves 37
    5.2.2 Flow experience questionnaire 40
    5.2.3 Correlation between brainwaves and questionnaire 41
    6. DISCUSSION 45
    7. CONTRIBUTION & FUTURE WORK 49
    8. REFERENCE 51
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    口試委員
  • 陳年興 - 召集委員
  • 蕭依涵 - 委員
  • 林怡伶 - 指導教授
  • 口試日期 2017-07-28 繳交日期 2017-07-24

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