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…

As Ratnam makes clear, a cultural-historical perspective on teacher/faculty excessive entitlement is indispensable if we are to use this concept to work with, rather than undermine, education practitioners. In this chapter, a networked relational model of activity is proposed as a tool for understanding excessive entitlement from a…

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…

Graph neural networks (GNN) are vital for analyzing real-world problems (e.g., network analysis, drug interaction, electronic design automation, e-commerce) that use graph models. However, efficient GNN acceleration faces with multiple challenges related to high and variable sparsity of input feature vectors, power-law degree distribution in the…

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…

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,…

This dissertation is about a particular style of research. The philosophy of this style is that in order to scientifically understand deep learning, it is fruitful to investigate what happens when neural networks are trained on simple, mathematically well-defined tasks. Even though the training data is simple, the training algorithm can end up…

Professional development for the further education sector (FE) in England, whether commissioned by the Education and Training Foundation (ETF), or the Department for Education (DfE), is typically formal learning. There are usually measurable outcomes, and practitioners are asked to identify changes to their practice. The focus on outcomes means…

Open and distance learning (ODL) activities aim to meet the expectations and needs of different individuals, societies, and systems by ensuring the continuation of learning with a lifelong learning philosophy and an egalitarian policy for everyone, regardless of time and place. Support services, which address the differentiated expectations and…

Knowledge applied to innovation is increasingly recognized as an explanatory factor of economic growth. Innovation derives from applying knowledge to generate new products or processes. National Innovation Systems (NIS) performs as the formal or informal network of people within institutions interacting to produce and apply knowledge to…

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…

Some patients benefit from a treatment while others may do so less or do not benefit at all. We have previously developed a two-stage network meta-regression prediction model that synthesized randomized trials and evaluates how treatment effects vary across patient characteristics. In this article, we extended this model to combine different…