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 article explores the history of digital testing technology. Using an organisation that pioneered the use of international large-scale assessments -- the International Association for the Evaluation of Educational Achievement (IEA) -- I discuss the role of computers, punched cards, answer cards and scanning machines as an example of…

This discussion paper explores the possibilities and risks that data linkage presents for the vocational education and training (VET) sector. Along with a broad overview of the nature of data linkage, it highlights possible applications for data linkage in the VET sector and examines the key challenges associated with its use. A number of case…

Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…