Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…

Shoeprints are a common type of evidence found at crime scenes and are regularly used in forensic investigations. However, their utility is limited by the lack of reference footwear databases that cover the large and growing number of distinct shoe models. Additionally, existing methods for matching crime-scene shoeprints to reference databases…

The National Institute of Mental Health created the National Database for Autism Research (NDAR) to accelerate autism knowledge through data sharing and collaboration. However, our experience using NDAR reveals systematic challenges across several aspects of data submission, selection, management, and analysis that limit utility of this resource.…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

In May of 2020, the Advanced Distributed Learning Initiative (ADL) and the Defense Acquisition University (DAU) partnered with USALearning/PowerTrain to create a practical application of ADL's 2019 TLA Reference Implementation. The purpose of this project was to recreate key components of the Reference Implementation with commercially-available,…

This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

Purpose: In this paper, the challenging and thorny issue of assessing graduate attributes (GAs) is addressed. An interdisciplinary team at The University of Alberta -- developed a formative model of assessment centered on students and instructor interaction with course content. Design/methodology/approach: The paper starts by laying the…

Data is a powerful tool for the healthcare industry to use for managing, analyzing, and reporting on critical events in the field. The analysis of broad, salient data files aids healthcare businesses in uncovering hidden patterns, market trends, and customer preferences; these details may then be used to improve the quality and delivery of care to…

This paper describes an innovative approach for teaching the challenges in the management of data warehouse development. The approach contains lecture material providing conceptual background about the management of data warehouse development, a simulation game supporting experiential learning, and a post-play debriefing to support synthesis of…