Purpose: This paper aims to consider ways to visually model data generated by qualitative case studies, pointing out a need for visualizations that depict both synchronic relations across representations and how those relations change diachronically. To develop an appropriate modeling approach, the paper critically examines Max Boisot's I-Space…

College students complete end-of-term surveys during their undergraduate education to report on their experiences of curriculum, faculty, and overall course satisfaction. Significant decisions are based on these surveys' results, despite limited and potentially unrepresentative results. Low student response rates on digital, electronic course…

Preschool, understood as being both a physical and psychological environment, is, according to objectives in national curriculum, required to be inclusive for all those who attend it. Previous studies have identified the stereotypical norms of several everyday activities of preschools, including both interactions and premises. The aim of this…

The purpose of this paper is to detail an exploratory case study which highlights a process to modernize an undergraduate marketing curriculum by incorporating aspects of digital marketing and analytics in all courses. In comparison to most other university models that offer, at best, one course in digital marketing, this paper details a blueprint…

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module…

The retention of new teachers is a noteworthy issue among physical education teachers. One way to combat attrition is with the implementation of induction programs that have a strong emphasis on mentoring. Mentoring creates a "growth-in-connection" for the novice physical education teacher as well as the mentor. The relational cultural…

In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload…

Serious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires-postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict…

A customized guide about liberatory design thinking processes that have been tested within college settings to support changes that enhance equity in policies and practices within institutions. This research is based on case studies of several institutions, including focus group interviews with the campus design teams and an analysis of artifacts.…

Dealing with the vast quantities of text that students generate in Massive Open Online Courses (MOOCs) and other large-scale online learning environments is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as students write in forums, assignments, and surveys. This paper introduces to the…

This paper is a research dissertation based on a qualitative case study conducted on Teachers' Experiences within a Data-Driven Decision Making (DDDM) process. The study site was a Title I elementary school in a large school district in Central Florida. Background information is given in relation to the need for research that was conducted on the…

The growth in the availability of longitudinal data--data collected over time on the same individuals--as part of program evaluations has opened up exciting possibilities for evaluators to ask more nuanced questions about how individuals' outcomes change over time. However, in order to leverage longitudinal data to glean these important insights,…

Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…

Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…

Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…