Predicting student performance using educational data is a significant area of machine learning research. However, class imbalance in datasets and the challenge of developing interpretable models can hinder accuracy. This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification…

Purpose: In the early 1980s, researchers and speech-language pathologists (SLPs) collaborated to develop the Systematic Analysis of Language Transcripts (SALT). Research and development over the ensuing decades has culminated into SALT Solutions, a set of tools to assist SLPs to efficiently complete language sample analysis (LSA) with their…

Many education researchers have advocated grounding abstract mathematical and scientific concepts in students' lived experiences, environmental interactions, and perceptions. This dissertation explores the causal effects of various grounding strategies in instructional settings, specifically on the topic of statistical sampling. The first chapter…

Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…

There is a need to improve the ways in which Qualitative Comparative Analysis (QCA) handles qualitative data. To this end, we propose to include ideas and routines from Grounded Theory (GT) in QCA. We will first argue that there is a natural fit between the two on the ontological level. On the methodological level, we will demonstrate in what ways…

Background: Digital storytelling (DST) has been embraced in classrooms around the world as a way to unpack issues of identity and positionality which are critical for any pedagogy concerned with social justice. However, adopting this process-orientated practice into higher education raises ethical concerns especially in relation to the normative…

Could the research you read be fundamentally flawed? Could critical defects in methodology slip by you undetected? To become informed consumers of research, students need to thoughtfully evaluate the research they read rather than accept it without question. This second edition of a classic text gives students the tools they need to apply critical…

Students may need explicit training in informal statistical reasoning in order to design experiments or use formal statistical tests effectively. By using scientific scandals and media misinterpretation, we can explore the need for good experimental design in an informal way. This article describes the use of a paper that reviews the measles mumps…

In "Using Learning Progressions to Design Vertical Scales that Support Coherent Inferences about Student Growth" (hereafter ULR), Briggs and Peck suggest that learning progressions could be used as the basis of vertical scales with naturally benchmarked descriptions of student proficiency. They propose and provide a single example of a…

In several subdomains of the social, behavioral, health, and human sciences, research questions are increasingly answered through mixed methods studies, combining qualitative and quantitative evidence and research elements. Accordingly, the importance of including those primary mixed methods research articles in systematic reviews grows. It is…

This exchange represents a follow-up to an article on the effects of state high school exit examinations that previously appeared in this journal (Warren, Grodsky, & Kalogrides 2009). That 2009 article was featured prominently in a report by the National Research Council (NRC) that evaluated the efficacy of test-based accountability systems.…

Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…

A standard topic in many Introductory Statistics courses is the analysis of dependent samples. A simple graphical approach that is particularly relevant to dependent sample comparisons is presented, illustrated and discussed in the context of analyzing five real data sets. Each data set to be presented has been published in a textbook, usually…

This article re-assesses the methodological difficulties involved in researching the powerful in education. It reviews the major areas and issues that researchers focused on: problems of access, different types of interviewing, interpretation of data generated through interviews and ethical issues. It argues that in most aspects researching…

Until recently, much of the research on students' understanding of statistical ideas has focused on their conceptions of center or on what constitutes a good sample. In the past decade research on students' statistical thinking has broadened and increasing interest has been paid to how students think about variability in data or variability in…