Purpose: The primary objective of this research paper was to examine the objectivity of the preselected items evaluation (PIE) method, a prevalent translation scoring method deployed by international institutions such as UAntwerpen, UGent and the University of Granada. Design/methodology/approach: This research critically analyzed the scientific…

Rapid approaches are essential when resources are limited and when findings are required in real-time to inform decisions. Limitations exist in their design and implementation, which can lead to a reduced level of trust in findings. This review sought to map the methods used across rapid evaluations and research to facilitate timeliness and…

The data we encounter in real life often contain missing values. In sampling methods, missing value imputation is done with different methods. This article proposes novel logarithmic type imputation methods for estimating the population mean in the presence of missing data under ranked set sampling (RSS). According to the determined theoretical…

Missing data presents a significant challenge in Educational Data Mining (EDM). Imputation techniques aim to reconstruct missing data while preserving critical information in datasets for more accurate analysis. Although imputation techniques have gained attention in various fields in recent years, their use for addressing missing data in…

There is currently no universally adopted definition of rural either by government entities or by rural special education researchers. Yet, the replicability, generalizability, transferability, and validity of rural special education research is dependent upon the definition of rural researchers' use to situate their work. Examining the…

The growing popularity of generative artificial intelligence (AI) tools presents new challenges for data quality in online surveys and experiments. This study examines participants' use of large language models to answer open-ended survey questions and describes empirical tendencies in human versus large language model (LLM)-generated text…

Researchers increasingly have access to two types of data: (i) large observational datasets where treatment (e.g., class size) is not randomized but several primary outcomes (e.g., graduation rates) and secondary outcomes (e.g., test scores) are observed and (ii) experimental data in which treatment is randomized but only secondary outcomes are…

In this article, the authors address some of the scientific challenges associated with using observation as a research method. The authors ask how researchers contextualise and understand observation in terms of its theoretical underpinnings and how it is conducted. Using a vignette in the kindergarten context, the authors explore how observation…

Children's fuzziness leads to increased variance in the data, data loss, and high dropout rates in developmental studies. This study investigated the importance of 20 factors on the person (child, caregiver, experimenter) and situation (task, method, time, and date) level for the data quality as indicated via the number of valid trials in 11…

In the early months of the COVID-19 pandemic, many research funding organizations were faced with the choice of suspending their peer review panels, or else continuing their decision-making processes virtually. Although seen part of a longer drive to make peer review more cost and time efficient as well as to combat climate and sustainability…

Pre-registration refers to the practice of researchers preparing a time-stamped document describing the plans for a study. This open research tool is used to improve transparency, so that readers can evaluate the extent to which the researcher adhered to their original plans and tested their theory appropriately. In the current study, we conducted…

Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…

This study critically examines the biases and methodological shortcomings in studies comparing deaf and hearing populations, demonstrating their implications for both the reliability and ethics of research in deaf education. Upon reviewing the 20 most-cited deaf-hearing comparison studies, we identified recurring fallacies such as the presumption…

The integration of artificial intelligence (AI), and particularly generative AI, into research methods is rapidly transforming both academic and industry marketing research, including both methods practices and education regarding these practices. AI application within methods offers new opportunities for enhancing efficiency, automating…

This research methods Case Study is based on an Exploratory Practice (EP) inquiry that I conducted into peer feedback processes, collaborating with my undergraduate English-language learners as co-researchers. I introduce EP, focusing on its core principles and processes while offering an insider account of how these played out when applied in a…