The five SEERNet digital learning platforms (DLPs) present unique opportunities for researchers by offering tools, processes, and infrastructure to make research more efficient, scalable, and relevant. However, conducting research within a DLP may require a shift in a researcher's orientation or mindset in how they think about potential research…

Big Data offers opportunities and challenges in all aspects of human life. In relation to research ethics, Big Data represents a normative difference in degree rather than a difference in kind. Data are more messy, rapid, difficult to predict, and difficult to identify owners; but the principles of informed consent, confidentiality, and prevention…

Higher education is awash with data that, when refined, facilitates data-informed decisions. Such decision-making is much more prevalent in support of undergraduate education given the much larger number of undergraduates pursuing higher education in contrast to the much smaller proportion of graduate students. A simple extension of current…

During the COVID-19 pandemic, organizations increased virtual programming and adoption of online technologies. This article outlines the University of California assessment of tools for gathering data on participant learning outcomes from virtual educational programs. After assessing colleagues' experiences and searching for new web applications,…

The U.S. Department of Education's (ED) Office for Civil Rights (OCR) administers the Civil Rights Data Collection (CRDC), which is a mandatory survey of all public schools and school districts in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico. To support school districts' timely submission of accurate data, OCR takes steps…

Background: Content validity is a key measurement property that should be considered when selecting or reviewing a patient-reported outcome measure (PROM). In the field of communication disorders, there are several PROMs available, most of which are disease specific. It is unknown what the quality of the content validity of these PROMs is. Aims:…

This article considers the multiple relations that emerge from and between Facebook commenters, as well as between commenters, researchers, and the research project during recruitment. To do so, we draw on our experiences of recruiting individuals who have concerns about or are opposed to a range of recent social and legal changes in…

Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…

School-based citizen science (SBCS) provides opportunities for teachers to purposefully integrate mathematics and science content and practices throughout the year. With SBCS projects, students have countless opportunities to apply their mathematics skills within the context of science data collection and sense making. This article details how a…

A growing amount of educational research employs participatory methods in which young people actively gather and analyze data in collaboration with the investigators. Considering the diverse use of the label "participatory," we examined participatory studies with young people to understand how researchers justify using this approach and…

This paper considers how effectively inspection takes account of the 'lived experience' of young people in school and in their leisure time, and identifies some weaknesses in both data gathering and reporting. It asserts that Ofsted should be more forthright in its judgments of the curriculum range now offered in schools, and regrets its lack of…

Data extraction is a time-consuming and resource-intensive task in the systematic review process. Natural language processing (NLP) artificial intelligence (AI) techniques have the potential to automate data extraction saving time and resources, accelerating the review process, and enhancing the quality and reliability of extracted data. In this…

Multi-lab projects are large scale collaborations between participating data collection sites that gather empirical evidence and (usually) analyze that evidence using meta-analyses. They are a valuable form of scientific collaboration, produce outstanding data sets and are a great resource for third-party researchers. Their data may be reanalyzed…

In this paper, we propose a new method for selecting cases for in situ, immediate interview research: detector-driven classroom interviewing (DDCI). Published work in educational data mining and learning analytics has yielded highly scalable measures that can detect key aspects of student interaction with computer-based learning in close to…

Accurate data extraction is a key component of evidence synthesis and critical to valid results. The advent of publicly available large language models (LLMs) has generated interest in these tools for evidence synthesis and created uncertainty about the choice of LLM. We compare the performance of two widely available LLMs (Claude 2 and GPT-4) for…