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Wei Liu – International Journal of Research & Method in Education, 2024
Underlying thematic analysis are a few fundamental human cognitive processes, such as categorizing, prototyping and metaphorical mapping. By unpacking these basic processes of human cognition, this paper hopes to provide a cognitive basis for thematic analysis as a foundational method in data analysis for qualitative research. In particular, it…
Descriptors: Qualitative Research, Cognitive Processes, Classification, Data Analysis
Weihua An – Sociological Methods & Research, 2024
Egocentric networks represent a popular research design for network research. However, to what extent and under what conditions egocentric network centrality can serve as reasonable substitutes for their sociocentric counterparts are important questions to study. The answers to these questions are uncertain simply because of the large variety of…
Descriptors: Research Design, Network Analysis, Data Analysis, Social Influences
Corrado Matta; Jannika Lindvall; Andreas Ryve – American Journal of Evaluation, 2024
In this article, we discuss the methodological implications of data and theory integration for Theory-Based Evaluation (TBE). TBE is a family of approaches to program evaluation that use program theories as instruments to answer questions about whether, how, and why a program works. Some of the groundwork about TBE has expressed the idea that a…
Descriptors: Data Analysis, Theories, Program Evaluation, Information Management
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
Ihnwhi Heo; Fan Jia; Sarah Depaoli – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The Bayesian piecewise growth model (PGM) is a useful class of models for analyzing nonlinear change processes that consist of distinct growth phases. In applications of Bayesian PGMs, it is important to accurately capture growth trajectories and carefully consider knot placements. The presence of missing data is another challenge researchers…
Descriptors: Bayesian Statistics, Goodness of Fit, Data Analysis, Models
Liyang Sun; Eli Ben-Michael; Avi Feller – Grantee Submission, 2024
The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…
Descriptors: Evaluation Methods, Comparative Analysis, Computation, Data Analysis
Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
Yixun Xing – Teaching Statistics: An International Journal for Teachers, 2024
Generative artificial intelligence (AI) has shown the potential to reshape the world and redefine daily workflows. One specific instance of generative AI, ChatGPT, specializes in understanding natural language and generating human-like conversational text. Its free access, user-friendly interface, and instant feedback have propelled its popularity…
Descriptors: Artificial Intelligence, Synchronous Communication, Statistics, Data Analysis
Jeremy Seeman; Aaron R. Williams; Claire McKay Bowen – Urban Institute, 2025
The Nebraska Statewide Workforce & Educational Reporting System (NSWERS) is a state longitudinal data system (SLDS) that coordinates data sharing, processing, and dissemination efforts across the Nebraska public school systems, Nebraska community colleges, the University of Nebraska system, the Nebraska Department of Labor, and other statewide…
Descriptors: Privacy, Access to Information, Data, State Programs
Xiaona Xia; Tianjiao Wang – Asia-Pacific Education Researcher, 2024
The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…
Descriptors: Learning, Behavior, Achievement, Learning Analytics
Alexis Henshaw – Journal of Political Science Education, 2024
Some in our discipline have recently voiced the opinion that political science is a data science. What follows from this argument is that we as instructors are training the next generation of data scientists, especially professionals and researchers who will work with big data. This paper explores the implications for political science education,…
Descriptors: Political Science, Data Science, Data Analysis, Role of Education
Danielle S. McNamara – Grantee Submission, 2024
Our primary objective in this Special Issue was to respond to potential criticisms of AIED in potentially "perpetuating poor pedagogic practices, datafication, and introducing classroom surveillance" and to comment on the future of AIED in its coming of age. My overarching assumption in response to this line of critiques is that humans…
Descriptors: Educational Practices, Educational Quality, Intelligent Tutoring Systems, Artificial Intelligence
Seliem El-Sayed; Filip Paspalj – Research Ethics, 2024
Recital 33 GDPR has often been interpreted as referring to 'broad consent'. This version of informed consent was intended to allow data subjects to provide their consent for certain areas of research, or parts of research projects, conditional to the research being in line with 'recognised ethical standards'. In this article, we argue that broad…
Descriptors: Ethics, Social Science Research, Standards, Data Analysis
Joanna Clifton-Sprigg; Jonathan James – British Educational Research Journal, 2025
Using newly released detailed data on absence from school, we find a 'Friday effect'--children are much less likely to attend schools in England on Fridays. We use daily level data across the whole of England and find that this pattern holds for different schools and for different types of absence, including illness-related authorised and…
Descriptors: Foreign Countries, Attendance Patterns, Student Behavior, Attendance
Nani Teig – Research in Science Education, 2024
The advancement of technology has led to a growing interest in assessing scientific inquiry within digital platforms. This shift towards dynamic and interactive inquiry assessments enables researchers to investigate not only the accuracy of student responses ("product data") but also their steps and actions leading to those responses…
Descriptors: Learning Strategies, Problem Solving, Science Process Skills, Inquiry