Closing the Experiential Learning Loops Using Learning Analytics Cycle

Abstract

In ubiquitous learning, authentic experiences are captured and later reused as those are rich resources for foreign vocabulary development. This article presents an experiential theory-oriented approach to the design of learning analytics support for sharing and reusing authentic experiences. In this regard, first, a conceptual framework to support vocabulary learning using learners' authentic experiences is proposed. Next, learning experiences are captured using a context-aware ubiquitous learning system. Finally, grounded in the theoretical framework, the development of a web-based tool called learn from others (LFO) panel is presented. The LFO panel analyzes various learning logs (authentic, partially-authentic, and words) using the profiling method while determining the top-five learning partners inside a seamless learning analytics platform. This article contributes to the research in the area of theory-oriented design of learning analytics for vocabulary learning through authentic activities and focuses on closing the loops of experiential learning using learning analytics cycles.