Digital Module 16: Longitudinal Data Analysis

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 begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

“I thought I’d have more trouble with white people!”: Exploring racial microaggressions between West African immigrants and African Americans

Racial tensions continue in 21st-century United States through the communication of racial microaggressions. We are interested in the communication of racial microaggressions directed towards West African immigrants by people with whom they expected to be allied, African Americans. Sixteen people who identified as West African immigrants were interviewed about communication struggles with African Americans in this qualitative, interpretive analysis. Owen’s thematic analysis was employed to analyze interview data. Results suggest the communicative impact of racial microaggressions on recipients is far-reaching and consequential. Narratives illustrate microaggressive communication occurs daily through invalidating, dismissive lines of questioning as well as targeted name calling and pejorative dialogue.     

The role of data analysis in inclusion processes and practices

This article outlines BPRS funded investigations into my own school's and other establishments' practices and processes within data analysis, needs identification and tracking of children's academic progress. It describes the evaluation of my school's then current practices and policies and the use of questionnaires and semi-structured interviews with my own staff, and assessment coordinators and senior leaders within exemplar schools. As well as outlining the main findings of my research this article assesses the introduction of new models of assessment for my own staff and pupils. This article also highlights how my research developed and the way my research process changed as it continued.     

The Path of Least Resistance: Using Available Tools to Support the E-Resources Lifecycle

On the surface, it might appear that libraries with different collections, staffing levels, and budgets would have to make use of different tools to address their e-resource management needs. However, in their review of electronic resources lifecycle work at North Carolina State University and Georgia Perimeter College, Tessa Minchew and Sofia Slutskaya discovered that this is not always the case. The presenters reviewed the electronic resources lifecycle and three distinct types of tools (content management systems/wikis, Microsoft Access, and Trello) that are being used in different ways to address different lifecycle-related tasks at each of their institutions.     

Classroom observation systems in context: A case for the validation of observation systems

Educational Assessment, Evaluation and Accountability - Researchers and practitioners sometimes presume that using a previously “validated” instrument will produce “valid”...     

Starting and Sustaining an Undergraduate Research Program: The SURIEM Experience at Michigan State University

Abstract

Mentoring undergraduate students in research is both rewarding and challenging. In this paper we present how we established a summer Research Experience for Undergraduates (REU) program in the mathematical sciences at Michigan State University. A goal of our REU is to include students who are at an early stage of their study of mathematics. We share our experiences in recruiting students, designing research projects, and mentoring our participants. We discuss the challenges we faced and the solutions we found while working with a diverse group of undergraduate students from across the nation.