Dragon Architect: Open Design Problems for Guided Learning in a Creative Computational Thinking Sandbox Game
Title | Dragon Architect: Open Design Problems for Guided Learning in a Creative Computational Thinking Sandbox Game |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Bauer, Aaron, Butler, Eric, Popović, Zoran |
Conference Name | Proceedings of the 12th International Conference on the Foundations of Digital Games |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-5319-9 |
Keywords | Collaboration, composability, computational thinking, game-based learning, policy, Policy-Governed Secure Collaboration, Policy-Governed systems, programming education, pubcrawl, Sandboxing |
Abstract | Educational games have a potentially significant role to play in the increasing efforts to expand access to computer science education. Computational thinking is an area of particular interest, including the development of problem-solving strategies like divide and conquer. Existing games designed to teach computational thinking generally consist of either open-ended exploration with little direct guidance or a linear series of puzzles with lots of direct guidance, but little exploration. Educational research indicates that the most effective approach may be a hybrid of these two structures. We present Dragon Architect, an educational computational thinking game, and use it as context for a discussion of key open problems in the design of games to teach computational thinking. These problems include how to directly teach computational thinking strategies, how to achieve a balance between exploration and direct guidance, and how to incorporate engaging social features. We also discuss several important design challenges we have encountered during the design of Dragon Architect. We contend the problems we describe are relevant to anyone making educational games or systems that need to teach complex concepts and skills. |
URL | https://dl.acm.org/citation.cfm?doid=3102071.3102106 |
DOI | 10.1145/3102071.3102106 |
Citation Key | bauer_dragon_2017 |