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David Lundie – Journal of Comparative and International Higher Education, 2024
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…
Descriptors: Data, Data Collection, Data Use, Governance
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Michael E. Young; Megan Miller; Christopher Urban; Claudia Petrescu – Discover Education, 2024
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…
Descriptors: Graduate Study, Masters Programs, Decision Making, Benchmarking
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Wylie, Tom – FORUM: for promoting 3-19 comprehensive education, 2023
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…
Descriptors: Inspection, Schools, Youth, Data Collection
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James Edward Hill; Catherine Harris; Andrew Clegg – Research Synthesis Methods, 2024
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…
Descriptors: Artificial Intelligence, Search Engines, Data Collection, Natural Language Processing
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Jens H. Fünderich; Lukas J. Beinhauer; Frank Renkewitz – Research Synthesis Methods, 2024
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…
Descriptors: Data Collection, Cooperation, Data Analysis, Data Use
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Ryan S. Baker; Stephen Hutt; Nigel Bosch; Jaclyn Ocumpaugh; Gautam Biswas; Luc Paquette; J. M. Alexandra Andres; Nidhi Nasiar; Anabil Munshi – Educational Technology Research and Development, 2024
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…
Descriptors: Electronic Learning, Anxiety, Metacognition, Data Collection
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Haesebrouck, Tim – Sociological Methods & Research, 2023
The field of qualitative comparative analysis (QCA) is witnessing a heated debate on which one of the QCA's main solution types should be at the center of substantive interpretation. This article argues that the different QCA solutions have complementary strengths. Therefore, researchers should interpret the three solution types in an integrated…
Descriptors: Qualitative Research, Comparative Analysis, Data Analysis, Data Collection
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Julian Schuessler; Peter Selb – Sociological Methods & Research, 2025
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…
Descriptors: Data Collection, Graphs, Error of Measurement, Statistical Bias
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Nicholas Norman Adams – International Journal of Social Research Methodology, 2024
The global scale of COVID-19 has constrained academics from conducting much person-facing research. Reactively, trend is increasing for digital-based methodologies capturing already existing online data. Scholars often 'scrape' user-postings from internet forums using coding algorithms and text capture tools, before analysing data, drawing…
Descriptors: Research Methodology, Educational Trends, Informed Consent, COVID-19
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Alexander Skulmowski – Educational Psychology Review, 2024
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…
Descriptors: Artificial Intelligence, Ethics, Research, Information Utilization
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Asson, Sarah; Frankenberg, Erica; Maselli, Annie; Burfoot-Rochford, Ian; Fowler, Christopher S.; Buck, Ruth Krebs – Education Finance and Policy, 2023
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…
Descriptors: Attendance, Zoning, Equal Education, Data Collection
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Rebecca Whittle; Joie Ensor; Miriam Hattle; Paula Dhiman; Gary S. Collins; Richard D. Riley – Research Synthesis Methods, 2024
Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…
Descriptors: Data, Individual Characteristics, Participant Characteristics, Meta Analysis
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Tsangaridou, Niki; Charalambous, Charalambos Y. – Quest, 2023
Focusing on systematic observation, one of the most potent methods of studying teaching quality, represents one of the numerous contributions of Daryl Siedentop to the profession. While he had a clear focus on issues of validity and reliability concerning systematic observation, over the past decades, attention to such issues appears to have…
Descriptors: Physical Education Teachers, Observation, Validity, Reliability
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John Jerrim – Review of Education, 2023
Two commonly used approaches to capturing information about teachers are random probability surveys and teacher panels. This paper reviews the strengths and limitations of these two approaches in the context of capturing information about the teacher workforce. A case study is then presented drawing upon recent teacher survey data collections in…
Descriptors: Foreign Countries, Teacher Surveys, Data Collection, Test Construction
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Allyson Skene; Laura Winer; Erika Kustra – International Journal for Academic Development, 2024
This article explores potential uses, misuses, beneficiaries, and tensions of learning analytics in higher education. While those promoting and using learning analytics generally agree that ethical practice is imperative, and student privacy and rights are important, navigating the complex maze of ethical dilemmas can be challenging, particularly…
Descriptors: Learning Analytics, Higher Education, Ethics, Privacy
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