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…

The Programme for International Student Assessment (PISA) introduced creative thinking as an innovative domain in 2022. This paper examines the unique methodological issues in international assessments and the implications of measuring creative thinking within PISA's framework, including stratified sampling, rotated form designs, and a distinct…

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…

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…

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…

The sampling approach [Fiedler, K. (2000a). "Beware of samples! A cognitive-ecological sampling approach to judgment biases." "Psychological Review, 107"(4), 659-676.] attributes judgment biases to the information given in a sample. Because people usually do not monitor the constraints of samples and do not control their judgments accordingly,…

Avoiding statistical mistakes is important for educators at all levels. Basic concepts will help you to avoid making mistakes using statistics and to look at data with a critical eye. Statistical data is used at educational institutions for many purposes. It can be used to support budget requests, changes in educational philosophy, changes to…