This article provides an introduction to randomized response polling, a technique which was designed to allow for questioning on sensitive issues while protecting the respondent's privacy and avoiding social desirability bias. It is described in terms that are suitable for presentation and use in any classroom environment. Instructions for plain…

In response to the evolving needs of knowledge synthesis, this manuscript introduces the concept of narrative reanalysis, a method that refines data from initial reviews, such as systematic and reviews, to focus on specific sub-phenomena. Unlike traditional narrative reviews, which lack the methodological rigor of systematic reviews and are…

Unnoticed by most, some technology corporations have changed their terms of service to allow user data to be transferred to clouds and even to be used to train artificial intelligence systems. As a result of these developments, remote data collection may in many cases become impossible to be conducted anonymously. Researchers need to react by…

Measuring opportunities to learn (OTL) is crucial for evaluating education quality and equity, but obtaining accurate and comprehensive OTL data at a large scale remains challenging. We attempt to address this issue by investigating measurement concerns in data collection and sampling. With the primary goal of estimating group-level OTLs for large…

Purpose: The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size,…

Family income questions in general purpose surveys are usually collected with either a single-question summary design or a multiple-question disaggregation design. It is unclear how estimates from the two approaches agree with each other. The current paper takes advantage of a large-scale survey that has collected family income with both methods.…

Artificial intelligence (AI) and data science (DS) are receiving a lot of attention in various fields. In the educational field, the need for education utilizing AI and DS is also being emerged. In this context, we have created an AI/DS integrating program that generates a compound classification/regression model using characteristics of compounds…

Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…

School attendance zone boundary (AZB) data remain relatively underdocumented and understudied within the field of education, despite their critical implications for educational (in)equity. AZBs shape student outcomes and residential sorting patterns both by determining the public schools a student is assigned to and by signaling neighborhood…

Systematic reviews (SRs) of preclinical studies are marked with poor methodological quality. In vitro studies lack assessment tools to improve the quality of preclinical research. This methodological study aimed to identify, collect, and analyze SRs based on cell culture studies to highlight the current appraisal tools utilized to support the…

Across higher education, educational developers and their supporting campus communities are being called upon to scale up evidence-informed practices, to enhance student experiences, and to document the changes. This article builds on the work of scholars who have taken up this evaluative challenge, by examining varied aspects of the evidencing…

This single-site case study will seek to answer the following question: how is the concept of privacy addressed in relation to a student success information system within a small, public institution of higher education? Three themes were found within the inductive coding process, which used interviews, documentation, and videos as data resources.…

Given their potential, "Big Data and Analytics" can help institutions of higher education to thoroughly examine newly emerging challenges, explore and identify new ways to address them, and predict future outcomes for growth. Considering how new "Big Data and Analytics" are, existing knowledge about the potential value to…

Single-case designs (SCDs) are a class of research methods for evaluating the effects of academic and behavioral interventions in educational and clinical settings. Although visual analysis is typically the first and main method for primary analysis of data from SCDs, quantitative methods are useful for synthesizing results and drawing systematic…

We note two possibilities for how our science might capitalize on advances in computing that harness and weave "big data" into the rich tapestry of how human development unfolds. First, we propose that the classic theoretical models that have guided developmental research since the 1970s and the hierarchical analytical models used to…