Conversation Quest in MEGA World (Multiplayer Educational Game for All)

Maiga Chang, Cheng Ting Chen, Kuan Hsing Wu, Pei Shan Yu

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    13 Citations (Scopus)

    Abstract

    The research team has developed a web-based massively multiplayer educational game platform named MEGA World. It allows teachers to create their own virtual worlds and to design a series of learning and assessment activities (i.e., quests and quest chain in a commercial game) for their students. The platform is also a multilingual platform that supports any languages and makes teachers capable of accessing external resources (e.g., multimedia, materials, online meetings, etc.). Students can learn and reach the predefined learning goals by taking and solving the quests while playing. Seven types of quests have been provided for teachers, including greeting, item collection and delivery, sorting, treasure hunting and digging, calculation, fill-in-the-blank, and short answer quest types. The research team is further design and develop conversation quest activities for Foreign English Learners (EFLs) to practice their speaking skills. While people believe that learners’ communicating skills can be improved by using a language to interact with native speakers, in many cases to have a native speaker practicing with the learners is not an available or an affordable option for them. This paper mainly focuses on how the teachers can build a place that provide simulated conversation scenarios within a no-pressure environment via the creation of conversation quests and the use of MEGA World.

    Original languageEnglish
    Title of host publicationLecture Notes in Educational Technology
    Pages77-82
    Number of pages6
    DOIs
    Publication statusPublished - 2019

    Publication series

    NameLecture Notes in Educational Technology
    ISSN (Print)2196-4963
    ISSN (Electronic)2196-4971

    Keywords

    • Educational game
    • English
    • Language learning
    • Multiplayer
    • Stealth Assessment

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