Learners Self-directing Learning in FutureLearn MOOCs: A Learner-Centered Study

de Waard, I. and Kukulska-Hulme, A. (2019). Learners Self-directing Learning in FutureLearn MOOCs: A Learner-Centered Study. In: Transforming Learning with Meaningful Technologies. EC-TEL 2019. (Scheffel, M; Broisin, J; Pammer-Schindler, V; Ioannou, A and Schneider, J eds.), Lecture Notes in Computer Science, Vol 11722, Springer, Cham, pp. 127–141.

DOI: https://doi.org/10.1007/978-3-030-29736-7_10

URL: https://link.springer.com/book/10.1007/978-3-030-2...

Abstract

This qualitative research study focuses on how experienced online learners self-direct their learning while engaging in a MOOC delivered on the FutureLearn platform. Self-directed learning is an important concept within informal learning and online learning. This study distinguishes itself from previous MOOC learner studies, by reporting the self-directed learning using a bottom-up approach. By looking at self-reported learning logs and interview transcripts an in-depth analysis of the self-directed learning is achieved. The data analysis used constructed grounded theory, which aligns with the bottom-up approach where the learner data is coded and investigated in an open, yet evidence-based way, leaving room for insights to emerge from the learner data. The data corpus is based on 56 participants following three FutureLearn MOOCs, providing 147 learning logs and 19 semi-structured one-on-one interviews with a selection of participants. The results show five specific areas in which learners react with either the material or other learners to self-direct their learning: context, individual or social learning, technology and media provided in the MOOCs, learner characteristics and organising learning. This study also indicates how intrinsic motivation and personal learning goals are the main inhibitors or enablers of self-directed learning.

Viewing alternatives

Download history

Metrics

Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions

Item Actions

Export

About

Recommendations