Title page for etd-0624117-104105


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URN etd-0624117-104105
Author Wei-cheng Su
Author's Email Address lucky1994@gmail.com
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Department Information Management
Year 2016
Semester 2
Degree Master
Type of Document
Language English
Title “Coding Peekaboom” Game-Based Programming Semantic Tagging System
Date of Defense 2017-07-28
Page Count 61
Keyword
  • Game
  • Flow experience
  • EEG
  • Labeling
  • Segmentation
  • Programming annotation
  • Crowdsourcing
  • Abstract 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.
    Advisory Committee
  • Nian-Shing Chen - chair
  • I-Han Hsiao - co-chair
  • Yi-Ling Lin - advisor
  • Files
  • etd-0624117-104105.pdf
  • Indicate in-campus at 3 year and off-campus access at 3 year.
    Date of Submission 2017-07-24

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