When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

Coding is a process of assigning meaning to a given piece of evidence. Evidence may be found in a variety of data types, including documents, research interviews, posts from social media, conversations from learning platforms, or any source of data that may provide insights for the questions under qualitative study. In this study, we focus on text…

Research on "computer-supported collaborative learning" (CSCL) is often concerned with the question of how scaffolds or other characteristics of learning may affect learners' social and cognitive engagement. Such engagement in socio-cognitive activities frequently materializes in discourse. In quantitative analyses of discourse,…

This paper provides a tutorial on epistemic network analysis (ENA), a novel method for identifying and quantifying connections among elements in coded data and representing them in dynamic network models. Such models illustrate the structure of connections and measure the strength of association among elements in a network, and they quantify…

Learning to solve "complex problems"--problems whose solutions require the application of more than basic facts and skills--is critical to meaningful participation in the economic, social, and cultural life of the digital age. In this paper, we use a theoretical understanding of how professionals use reflection-in-action to solve complex…