The case study draws on design thinking. It offers a research and innovation case method to address so-called wicked problems, that is, complex problems with many interdependent and incomplete factors and variables requiring deep understanding of the involved stakeholders and the innovative approach provided by design thinking. The case takes as…

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…

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…

A rising number of children are permanently excluded from school each year in England. Children's experiences of exclusion are underrepresented in the literature, effectively giving prominence to the views and interpretations of researchers. This qualitative study uses semi-structured interviews to explore the ways in which excluded children story…

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…

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…

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…

Including QR Codes on survey recruitment materials may be one method to reduce burden and encourage participation. The COVID-19 pandemic prompted a resurgence of QR Code use, so it is reasonable to assume they may now also be effective in survey outreach. In this article, we examine response by access mode (QR/URL) to better understand QR Code…

The methodological controversy surrounding ordinal outcome data has posed a distinct challenge to the conceptualization, design, and conduct of research in the social and behavioral sciences for more than 75 years. Accordingly, this study sought to supply a comprehensive and multidisciplinary perspective of the debate and in so doing lay the…

This case study is based on original research for a new teaching toolkit at the University of East Anglia (UEA), in Norwich, UK. The toolkit seeks to support the cultivation of equitable, fair, and dignified learning environments in UK Higher Education. It is grounded in decolonial principles that emphasize the relevance of ongoing reflexivity and…

Discrete-time survival analysis (DTSA) models are a popular way of modeling events in the social sciences. However, the analysis of discrete-time survival data is challenged by missing data in one or more covariates. Negative consequences of missing covariate data include efficiency losses and possible bias. A popular approach to circumventing…

In sparse data meta-analyses (with few trials or zero events), conventional methods may distort results. Although better-performing one-stage methods have become available in recent years, their implementation remains limited in practice. This study examines the impact of using conventional methods compared to one-stage models by re-analysing…

Despite their many benefits, longitudinal studies are much less common than one-time data collection or pre-post intervention designs. One reason for their scarcity is that longitudinal studies introduce requirements and challenges that non-longitudinal studies do not. One of the biggest challenges is participant attrition. In order to help…