How Learners Participate in Connectivist Learning: An Analysis of the Interaction Traces From a cMOOC

Abstract

In this research paper, the authors analyse the collected data output during a 36 week cMOOC. Six-week data streams from blogs, Twitter, a Facebook group, and video conferences were tracked from the daily newsletter and the MOOCs' hashtag (#Change 11). This data was analysed using content analysis and social network analysis within an interpretative research paradigm. The content analysis was used to examine the technology learners used to support their learning while the social network analysis focused on the participant in different spaces and their participation patterns in connectivist learning.The findings from this research include: 1) A variety of technologies were used by learners to support their learning in this course; 2) Four types of participation patterns were reveled, including unconnected floaters, connected lurkers, connected participants, and active contributors. The participation of learners displays the participation inequality typical of social media, but the ratio of active contributors is much higher than xMOOCs; 3) There were five basic structures of social networks formed in the learning; and 4) The interaction around topics and topic generation supports the idea of learning as network creation after the analysis of participation patterns that are based on some deep interactive topic. The aim of this study is to gain insight into the behaviors of learners in a cMOOC in an open and distributed online environment, so that future MOOCs designers and facilitators can understand, design and facilitate more effective MOOCs for learners.

Exploring a Personal Social Knowledge Network (PSKN) to aid the observation of connectivist interaction for high‐ and low‐performing learners in connectivist massive open online courses

“…Unfortunately, because of the large number of students in a single cMOOC course, it becomes nearly impossible for the instructor to monitor every student’s interactions and provide personalized feedback to them. Scholars have proposed to solve these challenges using data mining and learning analytics methods, through which machine algorithms would automatically detect learning engagement and interactions in the cMOOCs environment (Wang, Anderson, & Chen, ). In this paper, we introduce a learning analytics approach using the Personal Social Knowledge Network (PSKN) as a means to provide assessment on students’ connectivist interaction and learning in cMOOCs.…”

“…Thus, the connectivist interactions in cMOOCs, refer not only to the interactions among learners, but also with the content and teacher; importantly, these interactions both with others and the content are vital for connection building, network formation and knowledge creation (Wang et al, ). A variety of research studies have explored the connectivist interactions within cMOOCs environments (Downes, ; Siemens, ; Wang et al, ). These studies generally conclude that it is critical for instructors to be able to monitor and understand their students’ interaction behaviors as well as the relationship between these behaviors and students’ learning outcomes (Hughes & Dobbins, ).…”

“…Both human node and content node are important for connection building; and the network should demonstrate not only connections between learners but also the combination of learner‐to‐learner and learner‐to‐content interactions that leads to social relationship building as well as knowledge creation. Correspondingly, examining connection interactions from the network and connectivist perspective of learning (Downes, ; Siemens, ; Wang et al, ) shads new lights to our understanding about learning in the cMOOCs context and also to support instructors and students to monitor their learning and behavior in cMOOCs.…”

A Cross-Sectional Evaluation of EFL Students' Critical Thinking Dispositions in Digital Learning

“…Some previous studies have similar findings. These results are reflected by the weak truth-seeking in both freshmen and seniors [10] and the weak truth-seeking and systematicity showed in the distance education [6].…”

“…For instance, based on the theory of connectivism, educators take an essential role in digital learning. According to a concept about human's mind and behaviors, learners' behaviors in the online learning environment greatly impact the design of MOOCs [6]. Accordingly, as a concept about human's mind and behaviors, the critical thinking disposition deserves attention.…”