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Periodic Tapping Mechanisms of Skill Learning in a Fast-Paced Video Game

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DataCite Commons2023-07-07 更新2024-07-13 收录
下载链接:
https://kilthub.cmu.edu/articles/dataset/Periodic_Tapping_Mechanisms_of_Skill_Learning_in_a_Fast-Paced_Video_Game/21599775
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Dataset, software, and computational models used for a project entitled "Periodic Tapping Mechanisms of Skill Learning in a Fast-Paced Video Game". <br> This folder includes the 3 ACT-R models that are referenced in the paper as well as all the code and data that were used to preprocess and analyze the data. We are leveraging ACT-R's periodic tapping motor extension to simulate human learning at very fast speed (&lt;= 500 ms) in the Auto Orbit video game. <br> Folder organization: 1) Periodic Tapping Skill Learning - Code: This includes the ACT-R models, demographic information, Human &amp; model measure files, and all the scripts that were used to generate the figures and statistics <br> 2) Periodic Tapping Skill Learning - Data: This includes the game scores and event files (log files) for both humans and ACT-R models
提供机构:
Carnegie Mellon University
创建时间:
2022-11-22
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