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Luna, J. M.; Fardoun, H. M.; Padillo, F.; Romero, C.; Ventura, S. – Interactive Learning Environments, 2022
The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…
Descriptors: Online Courses, Student Characteristics, Classification, Student Behavior
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Nachouki, Mirna; Naaj, Mahmoud Abou – International Journal of Distance Education Technologies, 2022
The COVID-19 pandemic constrained higher education institutions to switch to online teaching, which led to major changes in students' learning behavior, affecting their overall performance. Thus, students' academic performance needs to be meticulously monitored to help institutions identify students at risk of academic failure, preventing them…
Descriptors: Academic Achievement, Academic Advising, College Students, Classification
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Ansyari, Muhammad Fauzan; Groot, Wim; De Witte, Kristof – Journal of Professional Capital and Community, 2022
Purpose: Professional development interventions (PDIs) are crucial for equipping teachers to use data effectively. Relying on previous studies reporting on such interventions, this paper aims to identify and synthesise the goals, dimensions and conditions of PDIs for data use. This paper also examines the evidence of the effect of such…
Descriptors: Literature Reviews, Meta Analysis, Data Use, Faculty Development
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Deeva, Galina; De Smedt, Johannes; De Weerdt, Jochen – IEEE Transactions on Learning Technologies, 2022
Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…
Descriptors: Electronic Learning, MOOCs, Dropouts, Prediction
Matthew John Davidson – ProQuest LLC, 2022
Digitally-based assessments create opportunities for collecting moment to moment information about how students are responding to assessment items. This information, called log or process data, has long been regarded as a vast and valuable source of data about student performance. Despite repeated assurances of its vastness and value, process data…
Descriptors: Data Use, Psychometrics, Item Response Theory, Test Items
Richard Hendra; Johanna Walter; Audrey Yu – MDRC, 2024
Government agencies collect vast amounts of administrative data in their day-to-day activities, primarily for program operations. But the information is less often used as a research tool or fully harnessed for its evidence-building potential. This brief is the fourth in a series of publications from MDRC about the Temporary Assistance for Needy…
Descriptors: Data Collection, Data Use, Evidence Based Practice, Program Administration
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Lukas Höper; Carsten Schulte – Informatics in Education, 2024
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…
Descriptors: Student Empowerment, Data Use, Computer Science Education, Artificial Intelligence
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Yuqin Yang; Xueqi Feng; Gaoxia Zhu; Daner Sun – Interactive Learning Environments, 2024
This interventional case study adopted a data-supported reflective assessment (DSRA) design to help pre-service teachers (PTs) engage in effective Knowledge Building (KB) and examined the mechanisms of this design to support PTs' productive KB discourse. The participants were 80 PTs from two classes taking the same course. Statistical analysis of…
Descriptors: Preservice Teachers, Teacher Characteristics, Reflection, Evaluation
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Ali Kürsat Erümit; Hasan Yigit Cebeci; Sefa Özmen – TechTrends: Linking Research and Practice to Improve Learning, 2024
Although big data applications in education have different usage areas, they can make important contributions to the evaluation of universities and education systems, decision-making and strategy development, and improvement of the education system. In this study, which is considered to contribute to the academicians who will work on big data in…
Descriptors: Data Use, Higher Education, Bibliometrics, Educational Research
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Janine Arantes – Learning, Media and Technology, 2024
As a result of the growing commercial marketplace for teachers' digital data, a new organization that includes educational data brokers has evolved. Educational data brokerage is relatively intangible due to the ease of de-identified data being collected and sold via educational technology. There is an urgent need to expose how the brokerage of…
Descriptors: Data Collection, Educational Technology, Commercialization, Privacy
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Safiye Temel-Aslan; Hulya Ertas-Kilic; Melihan Unlu; Betul Keray-Dincel – Science Insights Education Frontiers, 2024
Data literacy, which is considered among 21st century skills, is becoming increasingly important. In particular, incentives for data-driven decision-making draw attention to data literacy. Data literacy is also critical for teachers who need to use data in educational settings. Therefore, there is a need for data on whether teachers are equipped…
Descriptors: Data Use, Data Interpretation, Literacy, 21st Century Skills
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Cherise McBride; Clifford H. Lee; Elisabeth Soep – Reading Research Quarterly, 2024
Rapidly developing technological advances have raised new questions about what makes us uniquely human. As data and generative AI become more powerful, what does it mean to learn, teach, create, make meaning, and express ourselves, even as machines are trained to take care of these tasks for us? With youth, and in the context of literacy and media…
Descriptors: Literacy, Media Education, Adolescents, Young Adults
Dan Goldhaber; Nick Huntington-Klein; Nate Brown; Scott Imberman; Katharine O. Strunk – National Center for Analysis of Longitudinal Data in Education Research (CALDER), 2024
The COVID-19 pandemic forced widespread school closures and a shift to remote learning. A growing body of research has examined the effects of remote learning on student outcomes. But the accuracy of the school modality measures used in these studies is questionable. The most common measures--based on self-reports or district website…
Descriptors: Handheld Devices, Telecommunications, COVID-19, Pandemics
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Center for Learner Equity, 2024
Collected Biannually since 1968, the Civil Rights Data Collection (CRDC) represents the U.S. Department of Education's most substantial effort to understand data related to students' educational opportunities throughout K-12 schooling, particularly for historically marginalized student populations. Due to the COVID-19 pandemic, the Department…
Descriptors: Students with Disabilities, Elementary Secondary Education, Public Schools, Charter Schools
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Wisam Sedawi; Angela Calabrese Barton – Journal of the Learning Sciences, 2024
Background: Studies of socio-scientific decision-making in times of crisis are in their infancy. This study investigates how minoritized youth engage and make sense of newly developed COVID-19 vaccines and their intersections with the evolving multi-pandemic. Guided by theories of lively data, data sense and epistemic injustice, we center the…
Descriptors: Foreign Countries, Youth, COVID-19, Immunization Programs
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