With the advent of readily accessible generative artificial intelligence (GAI), a concern exists within the academic community that research data collected in the context of conducting doctoral dissertation research is authentic. The purpose of the present study was to explore the role of GAI in the production of new research paying particular…

Mixed-mode surveys are popular as they can save costs and maintain (or improve) response rates relative to single-mode surveys. Nevertheless, it is not yet clear how design decisions like survey mode or questionnaire length impact measurement quality. In this study, we compare measurement quality in an experiment of three distinct survey designs…

The use of inter-rater reliability (IRR) methods may provide an opportunity to improve the transparency and consistency of qualitative case study data analysis in terms of the rigor of how codes and constructs have been developed from the raw data. Few articles on qualitative research methods in the literature conduct IRR assessments or neglect to…

Data visualization literacy is "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" and is an emerging literacy type. Even though support exists for data literacy and data visualization use within the academic professions, limited research assessing data…

Medical simulations allow trainees to work within teams to develop their self-regulated learning (SRL) and socially-shared regulated learning (SSRL) skills (Bransen et al., 2022). Both skillsets help to better prepare medical trainees for the multifaceted challenges inherent in clinical practice. SRL skills are imperative in empowering learners to…

Effective management of digital identities and personal data is essential in modern society. Personal information management systems (PIMS) empower people to control their digital identities and personal data. Using the reasoned action approach (RAA) developed by Fishbein and Ajzen (2010), I derived the RAA-Trust Model for PIMS Adoption and…

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed…

Background: Data sharing improves the value, synthesis, and integrity of research, but rates are low. Data sharing might be improved if data sharing policies were prominent and actionable at every stage of research. We aimed to systematically describe the epidemiology of data sharing policies across the health research lifecycle. Methods: This was…

Purpose: This article argues that the potential of the vast amount of research, published each year in the history of education, remains untapped. Given the rapidly growing number of academic publications in the field, there is a need for research that is based on articles, chapters and monographs already published. While analyses of existing…

The purpose of the Faculty, Academic Careers and Environments (FACE) project is to understand who faculty are, what their academic careers look like, and how the environments in which they work shape their ability to thrive as instructors, researchers and public scholars in the community. This report provides an overview of a new conceptual model…

This report describes the two-year pilot study of how best to create a national study of faculty working at non-profit colleges and universities of all types across the country, given the social media and survey research environment of the 2020s. Since 2004, two major developments have significantly changed the landscape for academic employment:…

Real data are unlikely to be exactly normally distributed. Ignoring non-normality will cause misleading and unreliable parameter estimates, standard error estimates, and model fit statistics. For non-normal data, researchers have proposed a distributionally-weighted least squares (DLS) estimator to combines the normal theory based generalized…

In this study, we introduced a cross-classified multidimensional nominal response model (CC-MNRM) to account for various response styles (RS) in the presence of cross-classified data. The proposed model allows slopes to vary across items and can explore impacts of observed covariates on latent constructs. We applied a recently developed variant of…

This paper explores co-design in Japanese education for deploying data-driven educational technology and practice. Although there is a growing emphasis on data to inform educational decision-making and personalize learning experiences, challenges such as data interoperability and inconsistency with teaching goals prevent practitioners from…

This study employs advanced data mining techniques to investigate the DASS-42 questionnaire, a widely used psychological assessment tool. Administered to 680 students at Necmettin Erbakan University's Ahmet Kelesoglu Faculty of Education, the DASS-42 comprises three distinct subscales--depression, anxiety and stress--each consisting of 14 items.…