This study investigates inter- and intracoder reliability, proposing a new approach based on social network analysis (SNA) and exponential random graph models (ERGM). During a recent exit poll, the responses of voters to two open-ended questions were recorded. A coding experiment was conducted where a group of coders coded a sample of text…

As learning analytics use grows across U.S. colleges and universities, so does the need to discuss the plans, purposes, and paths for the data collected via learning analytics. More specifically, students, faculty, and others who are impacted by learning analytics use should have more information about their campus' learning analytics practices…

Although researchers recognize the importance of discussing support for math learning within online learning communities, there is a lack of relevant network classifying methods and analyses at the group level to understand the behavioral differences between groups with varying levels of activity, including their mathematical literacies. In this…

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently…

Checking for possible inconsistency between direct and indirect evidence is an important task in network meta-analysis. Recently, an evidence-splitting (ES) model has been proposed, that allows separating direct and indirect evidence in a network and hence assessing inconsistency. A salient feature of this model is that the variance for…

Churn in e-learning refers to learners who gradually perform less and become lethargic and may potentially drop out from the course. Churn prediction is a highly sensitive and critical task in an e-learning system because inaccurate predictions might cause undesired consequences. A lot of approaches proposed in the literature analyzed and modeled…

This article analyzes the Common Core State Standards initiative as an innovation network. Using narrative data and quantitative analysis of hypertext linkages on the World Wide Web, we describe a network of about 3200 organizations that arose to scale up the Common Core State Standards and link them to aligned academic resources such as…

This paper is part 4 in a series of workshops that examine the properties of some simple models of vocabulary networks. This Workshop explores how the overall activity level of a vocabulary network can be altered by changing the connections in the network (i.e., by implementing relinking events). The Workshop is linked to an online practice room…

Process data from educational assessments enhance the understanding of how students answer cognitive items. However, effectively making use of these data is challenging. We propose an approach to identify solution patterns from operation sequences and response times by generating networks from process data and defining network features that…

Since 2001, the National Institutes of Health (NIH) have funded the Institutional Development Award (IDeA) Network of Biomedical Research Excellence (INBRE) to expand biomedical research capacity among states in which NIH funding was historically low. The Western IDeA Region comprises seven states: Alaska, Hawaii, Idaho, Montana, New Mexico,…

We note two possibilities for how our science might capitalize on advances in computing that harness and weave "big data" into the rich tapestry of how human development unfolds. First, we propose that the classic theoretical models that have guided developmental research since the 1970s and the hierarchical analytical models used to…

The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to…

Network models of the WAIS-IV based on regularized partial correlation matrices have been reported to outperform latent variable models based on uncorrected correlation matrices. The present study sought to compare network and latent variable models using both partial and uncorrected correlation matrices with both types of models. The results show…

Career adaptability is better described as interconnected resources than as manifestations of a common factor. Using a sample of 1053 responses to the Career Adapt-Abilities Scale, we compared traditional confirmatory factor analysis models (unidimensional, bifactor, hierarchical) with a confirmatory network model, which is found to outperform the…

In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be…