Future Trends in Community of Inquiry Research and Big Data

Chapter 6 provides a summary of the topics around the Community of Inquiry, big data frameworks and tools, and additional commentary on these constructs. Additionally, the authors provide a concrete example of research work that has been updated with use of emerging big data technologies, provide concrete advice for future researchers working in these same or similar research areas, and describe further insights and sharing of the authors' research as it connects to constructs related to the CoI framework and online teaching and learning. Finally, the chapter includes predictions for future trends relating to big data and the constructs of the Community of Inquiry. Overall predictions are towards automated data analysis tools that are capable of looking into newer areas of analyses such as affective computing. A list of additional readings is included.

Educational Big Data and the Promise of Social Media

In Chapter 4, the authors focused on some tools and mindsets that are beneficial for conducting analysis and research in a big data context. In this chapter, they turn their focus to the “data” part of big data and examine some interesting sources to begin to work with. Social Media and related digital communications are the most prominently featured exemplars, but they also discuss other sources of data that can be analyzed. Finally, the authors also survey some interesting recent research being done both in Community of Inquiry and elsewhere that highlights strong data analytics approaches, interesting data sources, and novel conceptualizations of big data-type questions.

Tools for Educational Researchers Working With Big Data

Among the foremost challenges with big data is how to go about analyzing it. What new tools are needed to be able to properly investigate and model the large quantities of highly complex, often messy data? Chapter 4 addresses this question by introducing and briefly exploring the fields of Machine Learning, Natural Language Processing, and Social Network Analysis, focusing on how these methods and toolsets can be utilized to make sense of big data. The authors provide a broad overview of tools, ideas, and caveats for each of these fields. This chapter ends with a look at how one major public university in the United States, the University of Texas at Arlington, is beginning to address some of the questions surrounding big data in an institutional setting. A list of additional readings is provided.

Community of Inquiry Research Today

The Community of Inquiry framework provides a three-fold and multi-faceted way to consider effectiveness within an online, digital, and/or blended course setting. A broader understanding of online learning as social and interactive (e.g., Anderson & Elloumi, 2004) provides a theoretical grounding to understand the CoI framework for both course design as well as research. This chapter also describes key ideas that will be discussed in later chapters, including an overview of the Community of Inquiry framework, an overview of big data, learning analytics, predictive analytics, computational linguistics, social network analysis, and other conceptual ideas that foster analysis of online learners in large course settings or across programs. The authors offer a current understanding of the overall extant literature on the CoI framework as it relates to the key ideas since its conception around the year 2000. Additional readings are provided.

Big Data Analyses in the Community of Inquiry and Educational Research Spheres

Chapter 3 builds on the previous chapters and provides a summary of big data-style research within the Community of Inquiry scholarly literature, as well as examples from educational research broadly. This chapter also connects to the broader topics of machine learning, data analytics, learning analytics, and educational data mining. Constructs from the Community of Inquiry are integrated into this synthesis and overview. Unfortunately, only a fraction of the studies in educational research broadly today exhibit the tell-tale signs of big data: data volume and variety, new environments or instrumented sources of larger data, often with emerging tools and platforms critical to the analysis of the resulting datasets. A list of additional readings is provided.

Emerging Big Data Sources for Community of Inquiry-Focused Educational Researchers

This chapter extends on concepts from Chapter 1, namely the Community of Inquiry framework, and provides a further glimpse into the overarching trends in the more recent literature. Trends in the recent CoI literature include a focus beyond discussion board data, movement into social media, and a focus on big data. The relevance of social presence is explored as a crucial component of the CoI framework. The authors extend the idea of learning in community beyond the traditional learning management system into digital spaces such as social media (e.g., Twitter) that lends itself to analyses of large data sets. This chapter also provides concrete research vignettes into how one researcher has journeyed from single course research using the CoI framework to conceptualizing and designing study across multiple online courses and years of data collection. Such an evolution or transformation from small data research to big data is detailed.