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…

In this study, we examine friendship centrality and reciprocity between kindergarteners who exhibit externalizing classroom behaviors and their classroom peers. Teachers nominated children who display externalizing classroom behaviors, and we collected network data via individual interviews of 411 children (mean age = 6.7 years; SD = 0.33) from 21…

Network analytics has the potential to examine new behaviour patterns that are often hidden by the complexity of online interactions. One of the varied network analytics approaches and methods, the model of collective attention, takes an ecological system perspective to exploring the dynamic process of participation patterns in online and flexible…

Background: As a non-cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning…

Time-course model-based network meta-analysis (MBNMA) has been proposed as a framework to combine treatment comparisons from a network of randomized controlled trials reporting outcomes at multiple time-points. This can explain heterogeneity/inconsistency that arises by pooling studies with different follow-up times and allow inclusion of studies…

This study used social network analysis to evaluate whether sex heterophily, the degree to which peers are different in sex, between 126 children with autism (ages 5-12 years) and their peers affected social network connectivity. Results indicate that: (1) the quantity and sex of friends were more important in predicting social network…

Due to more college students recovering from addictions, institutions are implementing collegiate recovery communities (CRCs). CRCs provide academic and social support needed for recovering students to succeed and stay sober. Social network analysis tested whether the social connections within a CRC were related to relapse prevention among…

The emergence of social networks and social media has resulted in exponential increase in the amount of data that link diverse types of richly structured digital objects e.g., individuals, articles, images, videos, music, etc. Such data are naturally represented as heterogeneous networks with multiple types of objects e.g., actors, video,…

This study investigates a possible way to analyze chat data from collaborative learning environments using epistemic network analysis and topic modeling. A 300-topic general topic model built from TASA (Touchstone Applied Science Associates) corpus was used in this study. 300 topic scores for each of the 15,670 utterances in our chat data were…

We describe preliminary applications of network analysis techniques to eye-tracking data collected during a collaborative learning activity. This paper makes three contributions: first, we visualize collaborative eye-tracking data as networks, where the nodes of the graph represent fixations and edges represent saccades. We found that those…

The role of student interactions in learning situations is a foundation of sociocultural learning theory, and social network analysis can be used to quantify student relations. We discuss how self-reported student interactions can be viewed as processes of meaning making and use this to understand how quantitative measures that describe the…

This study examined whether clique isolation predicted an increase in depressive symptoms and whether this association was mediated by loneliness and perceived social acceptance in 310 children followed from age 11-14 years. Clique isolation was identified through social network analysis, whereas depressive symptoms, loneliness, and perceived…

Earlier studies have suggested that higher education institutions could harness the predictive power of Learning Management System (LMS) data to develop reporting tools that identify at-risk students and allow for more timely pedagogical interventions. This paper confirms and extends this proposition by providing data from an international…