Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…

Educational data mining constitutes a recent research field which gained popularity over the last decade because of its ability to monitor students' academic performance and predict future progression. Numerous machine learning techniques and especially supervised learning algorithms have been applied to develop accurate models to predict…

Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…

The expansion of technical concepts into everyday business practices suggests a need for effectively teaching difficult subjects to non-technical users. This paper describes hands-on analogy, an innovative method for teaching technically difficult concepts using interactive, experiential learning activities and a gamified exercise. We demonstrate…

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…

The ongoing 'datafication' of contemporary society has a number of implications for schools and schooling. One is the increasing calls for schools to help develop young people's understandings about the role that digital data now plays in their everyday lives -- especially in terms of the 'data economy' and 'surveillance capitalism'. Reporting on…

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…

Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

The purpose of this literature review is to understand the current state of research on tools that collect data for the purpose of formative assessment. We were interested in identifying the types of data collected by these tools, how these data were processed, and how the processed data were presented to the instructor or student for the purpose…

This article introduces an accessible approach to implementing unmoderated remote research in developmental science -- research in which children and families participate in studies remotely and independently, without directly interacting with researchers. Unmoderated remote research has the potential to strengthen developmental science by: (1)…

This data file documentation accompanies new data files for the High School Longitudinal Study of 2009 (HSLS:09) Postsecondary Education Transcript Study and Student Financial Aid Records Collection (PETS-SR). HSLS:09 follows a nationally representative sample of students who were ninth-graders in fall 2009 from high school into postsecondary…

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…

In the age of big data, interactive data visualizations are becoming increasingly prevalent. The ability to focus on subsets of data is essential for exploring large temporal, geospatial, topical, and network datasets. In order to categorize all parts of data visualizations, various attempts have been made to build frameworks for how to interpret,…

In this paper, we propose the Social Semantic Server (SSS) as a service-based infrastructure for workplace and professional learning analytics (LA). The design and development of the SSS have evolved over eight years, starting with an analysis of workplace learning inspired by knowledge creation theories and their application in different…

With the increase in technology in all facets of our lives and work, there is an ever increasing set of expectations that people have regarding information availability, response time, and dependability. While expectations are affected by gender, age, experience, industry, and other factors, people have expectations of technology, and from…