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• W3204047679 abstract "For citizen science games (CSGs) to be successful in advancing scientific research, they must effectively train players. Designing tutorials for training can be aided through developing a skill chain of required skills and their dependencies, but skill chain development is an intensive process. In this work, we hypothesized that free recall may be a simpler yet effective method of directly eliciting skill chains. We elicited 23 skill chains from players and developers and augmented our reflexive thematic analysis with 11 semi-structured interviews in order to determine how players and developers conceptualize skill trees and whether free recall can be used as an alternative to more resource-intensive cognitive task analyses. We provide three main contributions: (1) a comparison of skill chain conceptualizations between players and developers and across prior literature; (2) insights to the process of free recall in eliciting CSG skill chains; and (3) a preliminary toolkit of CSG skill-based design recommendations based on our findings. We conclude CSG developers should: give the big picture up front; embrace social learning and paratext use; reinforce the intended structure of knowledge; situate learning within applicable, meaningful contexts; design for discovery and self-reflection; and encourage practice and learning beyond the tutorial. Free recall was ineffective for determining a traditional skill chain but was able to elicit the core gameplay loops, tutorial overviews, and some expert insights." @default.
• W3204047679 created "2021-10-11" @default.
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• W3204047679 date "2021-10-05" @default.
• W3204047679 modified "2023-10-13" @default.
• W3204047679 title "How do Players and Developers of Citizen Science Games Conceptualize Skill Chains?" @default.
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• W3204047679 doi "https://doi.org/10.1145/3474671" @default.
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