Total Learning Architecture (TLA) Enables Next-generation Learning via Meta-adaptation

Technology is becoming ever more central to teaching and training. In classrooms, students use intelligent tutors and adaptive tests instead of textbooks and worksheets. In daily life, mobile devices enable blended, on-demand and ubiquitous life-long learning applications. Connected, pervasive media enables compelling transmedia learning (Raybourn, 2014) experiences. However, learning opportunities are still often implemented in “walled gardens” or stand-alone technology systems that must be manually curated and coordinated with all the others through costly, one-off efforts of developers or individual instructors. Next-generation learning refers to a vision for breaking down technical barriers between different learning technologies so that learners and instructors can transition seamlessly between them, increasing usability and impact on learning. The Advanced Distributed Learning (ADL) Initiative proposes an open-source set of specifications together called the Total Learning Architecture (TLA) to achieve this vision. TLA enables technologies to interoperate by sharing data about learners and content, mixing media and delivery methods as context changes, and sequencing recommendations (Regan, Raybourn, & Durlach, 2013). The initial reference implementation demonstrates multiple systems interacting via the TLA in an adaptive training use case for cyber operators. In the present paper, we describe recommendations for achieving new learning opportunities via meta-adaptation, or recommendations for more adaptive learning experiences that cross technical boundaries and connect systems, making each one more effective than it would be alone. Through system interoperability and meta-adaptation, the TLA facilitates an ecosystem of technologies that can work together to enhance their impact on learning.