Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA)

Zhang, Jingjing; Skryabin, Maxim; Song, Xiongwei

doi:10.1080/01587919.2016.1226230

Cited by 61 publications

(46 citation statements)

References 35 publications

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“…These difference between regular forum users and occasional posters was explicitly taken into account by Poquet and Dawson [19] showing that regular users shape a denser and more centralised communication network since they have more opportunities to establish connections. In the context of structural analysis of forum communication networks, different studies used exponential random graph models (ERGMs) [21] or related statistical network analysis models to identify factors that influence the emergence of the observed network characteristics [19,13,31,14]. In general these results reveal an effect of reciprocated ties and a lack of centralization of the networks to few influential users.…”

Section: Related Workmentioning

confidence: 96%

Dynamics of MOOC discussion forums

Boroujeni¹,

Hecking

Hoppe

et al. 2017

Proceedings of the Seventh International Learning Analytics &Amp; Knowledge Conference

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In this integrated study of dynamics in MOOCs discussion forums, we analyze the interplay of temporal patterns, discussion content, and the social structure emerging from the communication using mixed methods. A special focus is on the yet under-explored aspect of time dynamics and influence of the course structure on forum participation. Our analyses show dependencies between the course structure (video opening time and assignment deadlines) and the overall forum activity whereas such a clear link could only be partially observed considering the discussion content. For analyzing the social dimension we apply role modeling techniques from social network analysis. While the types of user roles based on connection patterns are relatively stable over time, the high fluctuation of active contributors lead to frequent changes from active to passive roles during the course. However, while most users do not create many social connections they can play an important role in the content dimension triggering discussions on the course subject. Finally, we show that forum activity level can be predicted one week in advance based on the course structure, forum activity history and attributes of the communication network which enables identification of periods when increased tutor supports in the forum is necessary.

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Section: Related Workmentioning

confidence: 96%

Dynamics of MOOC discussion forums

Boroujeni¹,

Hecking

Hoppe

et al. 2017

Proceedings of the Seventh International Learning Analytics &Amp; Knowledge Conference

View full text Add to dashboard Cite

show abstract

“…For instance, the research questions addressing the determinants of learning included how participants self-regulated their learning Kizilcec et al, 2017;Littlejohn et al, 2016;, people's motivations for participating or learning in a MOOC (Milligan & Littlejohn, 2017;Rieber, 2017;Shapiro et al, 2017;Stich & Reeves, 2017), and the learner behaviour in the course (de Lima & Zorrilla, 2017;Kahan, Soffer & Nachmias, 2017). Articles focusing on interactions in MOOCs examined the modes of discussion that characterised the participation of learners in forums (Gillani & Eynon, 2014;Zhang et al, 2016), the modes of communication offered to learners, namely asynchronous or synchronous (Li et al, 2014), the processes of interaction between users and organisers in the case of cMOOCs (Andersen & Ponti, 2014), or the modes of interaction and their role in the co-construction of new knowledge (Kellogg et al, 2014). As can be seen by these various studies, one does not question whether or not (and if so, how) the content specifies the learning process and/or interactions.…”

Section: Categories Of Research Objectsmentioning

confidence: 99%

Research on MOOCs in Major Referred Journals

Babori

Zaid

Fassi

2019

IRRODL

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Over the last decade, several studies have focused on massive open online courses (MOOCs). The synthesis presented here concentrates on these studies and aims to examine the place held by content in these studies, especially those produced between 2012 and 2018: sixty-five peer reviewed papers are identified through five major educational technology research journals. The analysis revealed that these research articles covered a wide diversity of content. Content was mainly defined in terms of objectives of MOOCs, prerequisites required for participation in the MOOC, types of learning scenarios, and, though rarely, through the strategies used to convey content. In addition, empirical studies adopted a variety of conceptual frameworks which focused mainly on learning strategies without relating to the content in question. Finally, content was seldom considered as a research object. These results can provide MOOC researchers and instructors with insights for the study and design of MOOCs by taking into account the specificity of their content.

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“…Statistical network modelling through methods such as exponential random graph models (ERGM) or stochastic actor-oriented models (SAOMs) are used to estimate the processes forming learner-to-learner networks using assumptions about the formation of social networks [23]. Results highlight that reciprocity of interactions often occur beyond chance, whereas closure is less common, and preferential attachment interpreted as learner popularity has not been observed [13,24,25].…”

Section: Limitations Of La Forum Modellingmentioning

confidence: 99%

Are forum networks social networks? A methodological perspective

Poquet¹,

Tupikina²,

Santolini³

2019

Preprint

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The mission of learning analytics (LA) is to improve learner experiences using the insights from digitally collected learner data. While some areas of LA are maturing, this is not consistent across all LA specialisations. For instance, LA for social learning lack validated approaches to account for the effects of cross-course variability in learner behavior. Although the associations between network structure and learning outcomes have been examined in the context of online forums, it remains unclear whether such associations represent bona fide social effects, or merely reflect heterogeneity in individual posting behavior, leading to seemingly complex but artefactual social network structures. We argue that to start addressing this issue, posting activity should be explicitly included and modelled in forum network representations. To gain insight to what extent learner degree and edge weight are merely derivatives of learner activity, we construct random models that control for the level of posting and post properties, such as popularity and thread hierarchy level. Analysis of forum networks in twenty online courses presented in this paper demonstrates that individual posting behavior is highly predictive of both the breadth (degree) and frequency (strength) in forum communication networks. This implies that, in the context of forum-based modelling, degree and frequency may not reflect the social dynamics. However, results suggest that clustering of the network structure is not a derivative of individual posting behaviour. Hence, weighted local clustering coefficient may be a better proxy for social relationships. The empirical results are relevant to scientists interested in social interactions and learner networks in digital learning, and more generally to researchers interested in deriving informative social network models from online forums.

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Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA)

Cited by 61 publications

References 35 publications

Dynamics of MOOC discussion forums

Dynamics of MOOC discussion forums

Research on MOOCs in Major Referred Journals

Are forum networks social networks? A methodological perspective

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