Machine Learning for Education: Learning to Teach
Abstract
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 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 and how they can be utilized to improve training. 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 methods for improving warfighter education: learning to predict performance, identify player disengagement, and recommend lesson plans.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 2016
- Accession Number
- AD1030414
Entities
People
- Matthew C. Gombolay
- Reed Jensen
- Sung-hyun Son
Organizations
- Massachusetts Institute of Technology