Selection of appropriate study design and analytical methods is critical for producing robust research, as the design and analytical approach used can ultimately shape results and their interpretation. The objective of this research was to examine how findings from a large repeat cross-sectional data system compare to those from a sample of…

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…

In recent years, the possibilities and pitfalls of qualitative secondary analysis have been the subject of on-going academic debate, contextualised by the growing availability of qualitative data in digital archives and the increasing interest of funding councils in the value of data re-use. This article contributes to, and extends these…

The number of unique words in children's speech is one of most basic statistics indicating their language development. We may, however, face difficulties when trying to accurately evaluate the number of unique words in a child's growing corpus over time with a limited sample size. This study proposes a novel technique to estimate the latent number…

Intended to guide scholars who are new to qualitative research, this methods brief focuses mostly on what reviewers look for in manuscripts submitted for publication. The author acknowledges that reviewers' preferences likely reflect their theoretical perspectives, research-oriented coursework, mentors, and research and writing experiences. The…

Missing data (attrition and non-response) are a feature of most surveys especially longitudinal/panel studies. And many such studies now have multilevel designs and hence multilevel data structures. Recent advances in imputation methodology now offer social researchers opportunities to address issues of missing data in a statistically principled…

The Academic Pathway Study (APS) research program within National Science Foundation (NSF) Center for Advancement of Engineering Education (CAEE) ran from 2003-2010. It amassed a collection of longitudinal as well as cross-sectional data sets, of varying research method types and formats, from four different primary cohorts that included over…

Multiple imputation (MI), a two-stage process whereby missing data are imputed multiple times and the resulting estimates of the parameter(s) of interest are combined across the completed datasets, is becoming increasingly popular for handling missing data. However, MI can result in biased inference if not carried out appropriately or if the…

In this article, we investigate how the national imperative to increase opportunities for young women of color in science, technology, engineering, and mathematics (STEM) and to broaden their participation was taken up locally at two high schools in one school district. Using ethnographic and longitudinal data, we focus on four young women of…

Purpose: The purpose of this paper is to examine how Robbins ES has sustained high academic performance over almost 20 years despite several changes in principals. Design/methodology/approach: The paper analyzed longitudinal data based on: state-level academic and demographic data; two earlier studies of the school; and recent interviews with…

Substantial amount of research regarding L2 learners' beliefs has been conducted in recent years. However, not enough attention has been paid to investigating the nature of learners' beliefs; hence our understanding of the construct is contradictory in the sense that early research studies report stability in beliefs, while more recent studies…

Sharing longitudinal student record data and merging data from different sources is critical to addressing important questions being asked of higher education. The Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) is a multi-institution, longitudinal, student record level dataset that is used to answer…

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…

Teaching socioscientific issues (SSI) necessitates dialogic discourse activities. However, a majority of science teachers prefer monologic discourse in SSI contexts. In addition, some of these teachers are resistant to change (from monologic to dialogic discourse) despite certain professional development attempts. The purpose of the present…

Little longitudinal research has examined change in university teachers' elearning beliefs and practices after their initial experience with elearning. This study addresses this gap by focusing on six teachers who developed and implemented an elearning resource, and the changes they made to the resource and its implementation over two years. A…