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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
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Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
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Julie Fitz; Julie Woods; Naomi Duran; Jennifer McCombs – Learning Policy Institute, 2025
Student participation in summer programming can be an effective way to address students' academic and developmental needs. When well implemented and well attended, summer enrichment programs, academic programs, and employment programs have demonstrated positive outcomes for youth in areas related to program content, including academic achievement…
Descriptors: Summer Programs, Educational Opportunities, Educational Quality, Regional Characteristics
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Julie Fitz; Julie Woods; Naomi Duran; Jennifer McCombs – Learning Policy Institute, 2025
As federal funding for summer learning as a pandemic recovery strategy phases out, state governments face decisions about their future role in supporting students' access to quality summer learning opportunities. This brief is based on the full report, "How States Are Expanding Quality Summer Learning Opportunities," and summarizes…
Descriptors: Summer Programs, Educational Opportunities, Educational Quality, Regional Characteristics
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M. B. Saikrishna – On the Horizon, 2025
Purpose: The purpose of this paper is to investigate how educators perceive and adapt their roles in the face of changes in technology-driven learning environments. The Gioia methodology explores how educators enable adaptive learning, broaden their pedagogical practice and promote cultural inclusivity to educate diverse students.…
Descriptors: Teacher Attitudes, Educational Technology, Technology Uses in Education, Teacher Role
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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