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Guiyun Feng; Honghui Chen – Education and Information Technologies, 2025
Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…
Descriptors: Educational Research, Artificial Intelligence, Data Use, Algorithms
Frank Lee; Alex Algarra – Information Systems Education Journal, 2024
Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…
Descriptors: Visual Aids, Data Use, Data Collection, Naming
Dubrow, Joshua K. – International Journal of Social Research Methodology, 2022
The COVID 19 pandemic illuminates the role data has in public policy-making, i.e. datafication of society, and the importance of exploring the local sources of data to reveal errors in what has assuredly been from the beginning an undercount of cases and deaths. I note four interrelated error sources. The first two are common to any quantitative…
Descriptors: Data Use, COVID-19, Pandemics, Data Collection
Meholick, Sarah; Honey, Rose; LaTurner, Jason – National Center for Education Statistics, 2023
Statewide longitudinal data systems (SLDSs) can enable researchers, policymakers, and practitioners to identify and understand important relationships and trends across the education-to-workforce continuum. A well-developed SLDS can increase state and territory governments' ability to establish more informed and equitable policies, enable agency…
Descriptors: Longitudinal Studies, State Programs, State Policy, Data Collection
Snyder, Johnny – Information Systems Education Journal, 2019
Quantitative decision making (management science, business statistics) textbooks rarely address data cleansing issues, rather, these textbooks come with neat, clean, well-formatted data sets for the student to perform analysis on. However, with a majority of the data analyst's time spent on gathering, cleaning, and pre-conditioning data, students…
Descriptors: Data Analysis, Error Patterns, Data Collection, Spreadsheets
Liu, Kai; Tatinati, Sivanagaraja; Khong, Andy W. H. – IEEE Transactions on Learning Technologies, 2020
Activity-centric data gather feedback on students' learning to enhance learning effectiveness. The heterogeneity and multigranularity of such data require existing data models to perform complex on-the-fly computation when responding to queries of specific granularity. This, in turn, results in latency. In addition, existing data models are…
Descriptors: Context Effect, Models, Learning Analytics, Data Use
Esomonu, Nkechi Patricia-Mary; Esomonu, Martins Ndibem; Eleje, Lydia Ijeoma – International Journal of Evaluation and Research in Education, 2020
As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…
Descriptors: Foreign Countries, Expertise, Learning Analytics, Student Evaluation
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use