Investigating self-directed learning dimensions: Adapting the Bouchard framework

Abstract

Self-Directed Learning (SDL) is gaining interest, as online learning is increasingly learner-centered. FutureLearn courses provide an array of online interactions and content deliveries, which have allowed the authors to investigate a diversity of SDL elements. This preliminary research examines the SDL taking place in three FutureLearn courses, and categorises those learner actions into meaningful elements and dimensions for the learners. The SDL framework by Bouchard [1] is used to interpret the self-reported findings coming from active learners. The research uses a grounded theory approach to look for learner experiences related to four dimensions (algorithmic, conative, semiotic, and economic) of the Bouchard [1] framework, and to discover new dimensions. Various research instruments are used: online surveys, learning logs, and one-onone interviews, all collected pre-, during, or post-course. The initial adaptation of Bouchard’s framework offers insights into SDL, its meaning, and value as perceived by the learners.