Adaptive Learner Assessment to Train Social Media Analysts

Abstract

The Twiner project provides a practice environment to support a learner in analysis and interpretation of an ongoing situation through a social media data framework. Within this framework exists a host practice environment complemented by a set of modular components for facilitating training, known as the GTRI Learner Assessment Engine, or GLAsE. GLAsE maps the evaluated learner activity to individual components of analysis, i.e., the learning objectives. It estimates learner proficiency for individual learning objectives based on observations of the learner actions while performing the learning tasks. GLAsE represents the state of the world using a Learner Model that provides the current state of the learner’s domain competency, and a Curriculum Model that represents the concepts, activities, and skills of an expert analyst in this domain. GLAsE may produce advice and hints for the learner at multiple points in the assessment process, which are then passed to the learner via the practice environment as a form of direct feedback for the learner’s performance. Through these capabilities, GLAsE reduces the time necessary for domain experts to dedicate to novice training and increases the agility and responsiveness of the training system.