Machine Learning Techniques for Analyzing Training Behavior in Serious Gaming
| Autor: | Reed Jensen, Sung-Hyun Son, Matthew C. Gombolay |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science 05 social sciences Training time Traditional classroom 020207 software engineering Context (language use) 02 engineering and technology Machine learning computer.software_genre Training (civil) Resource (project management) Artificial Intelligence Control and Systems Engineering Health care 0202 electrical engineering electronic engineering information engineering Commercial aviation 0501 psychology and cognitive sciences Artificial intelligence Electrical and Electronic Engineering Disengagement theory business computer 050107 human factors Software |
| Zdroj: | IEEE Transactions on Games. 11:109-120 |
| ISSN: | 2475-1510 2475-1502 |
| Popis: | Training time is a costly, scarce resource across domains such as commercial aviation, healthcare, and military operations. In the context of military applications, serious gaming—the training of warfighters through immersive, real-time environments rather than traditional classroom lectures—offers benefits to improve training not only in its hands-on development and application of knowledge, but also in data analytics via machine learning. In this paper, we explore an array of machine learning techniques that allow teachers to visualize the degree to which training objectives are reflected in actual play. First, we investigate the concept of discovery: learning how warfighters utilize their training tools and develop military strategies within their training environment. Second, we develop machine learning techniques that could assist teachers by automatically predicting player performance, identifying player disengagement, and recommending personalized lesson plans. These methods could potentially provide teachers with insight to assist them in developing better lesson plans and tailored instruction for each individual student. |
| Databáze: | OpenAIRE |
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