SBIR Phase I: Student Gaming and Algorithms
SBIR Phase I: Student Gaming and Algorithms
批准号:
1912785
负责人:
Bryan Goerger
金额:
$22.45万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2020-06-30
中文摘要
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英文摘要
This SBIR Phase I project will focus on developing and demonstrating feasibility of a first multi-player educational gaming platform where the experience in the game directly translates to real world skills in skilled trade. The platform will be a multiplayer experience in which gamers collaborate to complete construction projects and design and engineering efforts in the real world. This approach to training the next generation of construction professionals provides an efficient approach to train the next generations of construction managers, estimators, contractors, field superintendents and tradesmen. Since the construction industry continues to trail others related to the adoption of technology, the timeliness of this educational technology that links STEM learning within a simulated construction project is underscored. This technology will also address the challenge of making education, especially in the skilled trades, more accessible to socioeconomic disparate populations, and to other students not able to attend traditional universities to acquire these skills. This SBIR Phase I project will focus on developing and demonstrating feasibility of the high-risk components of the Design Builder Pro Simulator application. In general, the Phase I will require curriculum development and developing a prototype of the user interface, gaming and design layout. The prototype software will be integrated with intelligent algorithms to adjust gaming difficulty based on student performance. More specifically, the project includes the following 3 objectives: 1. Design and build alpha technology that successfully passes verification testing. Success metrics include the alpha prototype software interface and gaming subcomponents is developed and successfully passes all technical verification. 2. Develop intelligent algorithms to adaptively adjust game parameters. Success metrics include the developed algorithms accurately adjust game difficulty based on subject performance. 3. Complete a usability study to validate the student experience and core curriculum. Success metrics include Improved student knowledge about and interest in construction, significant positive quantitative and qualitative metrics from user validation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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