Analytics-based approach to the study of learning networks in digital education settings

Investigating howgroups communicate, build knowledge and expertise, reach consensus or collaboratively solve complex problems, became one of the main foci of contemporary research in learning and social sciences. Emerging models of communication and empowerment of networks as a form of social organization further reshaped practice and pedagogy of online education, bringing research on learning networks into the mainstream of educational and social science research. In such conditions, massive open online courses (MOOCs) emerged as one of the promising approaches to facilitating learning in networked settings and shifting education towards more open and lifelong learning. Nevertheless, this most recent educational turn highlights the importance of understanding social and technological (i.e., material) factors as mutually interdependent, challenging the existing forms of pedagogy and practice of assessment for learning in online environments. On the other hand, the main focus of the contemporary research on networked learning is primarily oriented towards retrospective analysis of learning networks and informing design of future tasks and recommendations for learning. Although providing invaluable insights for understanding learning in networked settings, the nature of commonly applied approaches does not necessarily allow for providing means for understanding learning as it unfolds. In that sense, learning analytics, as a multidisciplinary research field, presents a complementary research strand to the contemporary research on learning networks. Providing theory-driven and analytics-based methods that would allow for comprehensive assessment of complex learning skills, learning analytics positions itself either as the end point or a part of the pedagogy of learning in networked settings. The thesis contributes to the development of learning analytics-based research in studying learning networks that emerge fromthe context of learning with MOOCs. Being rooted in the well-established evidence-centered design assessment framework, the thesis develops a conceptual analytics-based model that provides means for understanding learning networks from both individual and network levels. The proposed model provides a theory-driven conceptualization of the main constructs, along with their mutual relationships, necessary for studying learning networks. Specifically, to provide comprehensive understanding of learning networks, it is necessary to account for structure of learner interactions, discourse generated in the learning process, and dynamics of structural and discourse properties. These three elements – structure, discourse, and dynamics – should be observed as mutually dependent, taking into account learners’ personal interests, motivation, behavior, and contextual factors that determine the environment in which a specific learning network develops. The thesis also offers an operationalization of the constructs identified in the model with the aim at providing learning analytics-methods for the implementation of assessment for learning. In so doing, I offered a redefinition of the existing educational framework that defines learner engagement in order to account for specific aspects of learning networks emerging from learning with MOOCs. Finally, throughout the empirical work presented in five peer-reviewed studies, the thesis provides an evaluation of the proposed model and introduces novel learning analytics methods that provide different perspectives for understanding learning networks. The empirical work also provides significant theoretical and methodological contributions for research and practice in the context of learning networks emerging from learning with MOOCs

What is the source of social capital? the association between social network position and social presence in Communities of Inquiry

It is widely accepted that the social capital of students – developed through their participation in learning communities – has a signif-icant impact on many aspects of the students ’ learning outcomes, such as academic performance, persistence, retention, program sat-isfaction and sense of community. However, the underlying social processes that contribute to the development of social capital are not well understood. By using the well-known Community of In-quiry (CoI) model of distance and online education, we looked into the nature of the underlying social processes, and how they relate to the development of the students ’ social capital. The results of our study indicate that the affective, cohesive and interactive facets of social presence significantly predict the network centrality mea-sures commonly used for measurement of social capital

Automated cognitive presence detection in online discussion transcripts

In this paper we present the results of an exploratory study that examined the use of text mining and text classification for the au-tomation of the content analysis of discussion transcripts within the context of distance education. We used Community of In-quiry (CoI) framework and focused on the content analysis of the cognitive presence construct given its central position within the CoI model. Our results demonstrate the potentials of proposed ap-proach; The developed classifier achieved 58.4 % accuracy and Co-hen’s Kappa of 0.41 for the 5-category classification task. In this paper we analyze different classification features and describe the main problems and lessons learned from the development of such a system. Furthermore, we analyzed the use of several novel classifi-cation features that are based on the specifics of cognitive presence construct and our results indicate that some of them significantly improve classification accuracy. 1

Social presence in massive open online courses

The capacity to foster interpersonal interactions in massive open online courses (MOOCs) has frequently been contested, particularly when learner interactions are limited to MOOC forums. The establishment of social presence-a perceived sense of somebody being present and "real"-is among the strategies to tackle the challenges of online learning and could be applied in MOOCs. Thus far, social presence in MOOCs has been under-researched. Studies that previously examined social presence in MOOCs did not account for the peculiar nature of open online learning. In contrast to the existing work, this study seeks to understand how learners perceive social presence, and the different nuances of social presence in diverse MOOC populations. In particular, we compare perceptions of social presence across the groups of learners with different patterns of forum participation in three edX MOOCs. The findings reveal substantial differences in how learners with varying forum activity perceive social presence. Perceptions of social presence also differed in courses with the varying volume of forum interaction and duration. Finally, learners with sustained forum activity generally reported higher social presence scores that included low affectivity and strong group cohesion perceptions. With this in mind, this study is significant because of the insights into brings to the current body of knowledge around social presence in MOOCs. The study's findings also raise questions about the effectiveness of transferring existing socio-constructivist constructs into the MOOC contexts.System Engineerin

Social presence in online discussions as a process predictor of academic performance

With the steady development of online education and online learning environments, possibilities to support social interactions between students have advanced significantly. This study examined the relationship between indicators of social presence and academic performance. Social presence is defined as students ' ability to engage socially with an online learning community. The results of a multiple regression analysis showed that certain indicators of social presence- i.e., continuing a thread and complimenting, expressing appreciation – were significant predictors of final grades in a master's level computer science online course. Moreover, the study also revealed that teaching presence – operationalized through the changes in instructional design- moderated the association between social presence and academic performance, indicating that a course design that increased the level of meaningful interactions between students had a significant impact on the development of social presence and thus, could positively affect students ' academic performance. This is especially important in situations when discussions are introduced to promote the development of learning outcomes (e.g., critical thinking) assessed in courses. Another implication of our results is that indicators of social presence can be used for early detection of students at risk of failing a course. This finding informs research and practice in the emerging field of learning analytics by prompting the opportunities to offer actionable insights into the reasons why certain students are lagging behind. These insights are grounded in indicators of the quality of social knowledge construction rather than a simple quantity of discussion posts