Abstract
The learning sciences field is in need of new automated methodological approaches that offer deeper insights into the dynamics of learner interaction and discourse across scaled learning platforms. In this paper, we explore MOOC learners’ discourse by employing Group Communication Analysis (GCA), a methodology for quantifying and characterizing the discourse between learners in online interactions. Commonly used approaches in MOOCs derive insight into the learning processes from aggregated text or structural data. In contrast, GCA makes use of linguistic cohesion analysis across sequences of learners’ interactions in multi-party communication. GCA calculates six inter-and intra-personal sociocognitive measures of such interactions and from these identify distinct interaction profiles through a cluster analysis. With this method, we were able to diagnostically reveal four robust profiles amongst MOOC learners. This study presents a unique analysis of the sociocognitive processes that comprise the interaction between learners. The scalability of the methodology opens the door for future research efforts directed towards understanding and improving scaled peer-interactions.
| Original language | English |
|---|---|
| Pages (from-to) | 1815-1822 |
| Number of pages | 8 |
| Journal | Proceedings of International Conference of the Learning Sciences, ICLS |
| Volume | 3 |
| Issue number | 2018-June |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 13th International Conference of the Learning Sciences, ICLS 2018: Rethinking Learning in the Digital Age: Making the Learning Sciences Count - London, United Kingdom Duration: 23 Jun 2018 → 27 Jun 2018 |