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Yun Du – International Journal of Web-Based Learning and Teaching Technologies, 2024
This paper deeply discusses the transformation potential of integrating Internet big data into the pre-school education model in colleges and universities. Through in-depth analysis, we studied the challenges and opportunities faced by preschool education in colleges and universities, and discussed the innovative influence of big data technology…
Descriptors: Educational Innovation, Preschool Education, Data Analysis, Data Collection
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Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
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Yaqian Zheng; Deliang Wang; Junjie Zhang; Yanyan Li; Yaping Xu; Yaqi Zhao; Yafeng Zheng – Education and Information Technologies, 2025
Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…
Descriptors: Individualized Instruction, Electronic Learning, Academic Achievement, Student Educational Objectives
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Sefton-Green, Julian; Pangrazio, Luci – Educational Philosophy and Theory, 2022
Amidst ongoing technological and social change, this article explores the implications for critical education that result from a data-driven model of digital governance. The article argues that traditional notions of critique which rely upon the deconstruction and analysis of texts are increasingly redundant in the age of datafication, where the…
Descriptors: Data Analysis, Governance, Educational Philosophy, Barriers
Wendy Castillo; David Gillborn – Annenberg Institute for School Reform at Brown University, 2023
'QuantCrit' (Quantitative Critical Race Theory) is a rapidly developing approach that seeks to challenge and improve the use of statistical data in social research by applying the insights of Critical Race Theory. As originally formulated, QuantCrit rests on five principles; 1) the centrality of racism; 2) numbers are not neutral; 3) categories…
Descriptors: Educational Research, Data Use, Educational Researchers, Interdisciplinary Approach
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Apryl L. Poch; Pyung-Gang Jung; Kristen L. McMaster; Erica S. Lembke – Grantee Submission, 2025
Data-Based Instruction (DBI) has a strong empirical base for supporting the intensive academic needs of students who do not respond to standard treatment protocols. However, teachers use DBI infrequently in practice. In a previous study (Poch et al., 2020), teachers reported supports such as coaching facilitated DBI implementation, whereas access…
Descriptors: Data Use, Teaching Methods, Faculty Development, Special Education Teachers
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Seyma Birinci – ProQuest LLC, 2024
The purpose of this study was to explore how teachers engaged in data use for instructional decision making. A grounded theory research design was used to analyze interviews of 10 special education teachers. Special education teachers were asked to complete an online survey and were interviewed with questions to reveal their experiences with…
Descriptors: Individualized Instruction, Decision Making, Data Use, Special Education Teachers
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Toyokawa, Yuko; Horikoshi, Izumi; Majumdar, Rwitajit; Ogata, Hiroaki – Smart Learning Environments, 2023
In inclusive education, students with different needs learn in the same context. With the advancement of artificial intelligence (AI) technologies, it is expected that they will contribute further to an inclusive learning environment that meets the individual needs of diverse learners. However, in Japan, we did not find any studies exploring…
Descriptors: Barriers, Affordances, Artificial Intelligence, Inclusion
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Tamara Nelson-Fromm; Bahare Naimipour; Tamara Shreiner; Mark Guzdial – Social Education, 2024
Data literacy, an important goal for social studies education, involves teaching students how to comprehend, analyze, interpret, evaluate, create, and argue with data and data visualizations such as timelines, maps, and graphs. Digital data visualizations support rapid inquiry and explorations that would be difficult on paper - such as adding data…
Descriptors: Visual Aids, Social Studies, Educational Technology, Technology Uses in Education
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Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
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Usher, Maya; Hershkovitz, Arnon – Journal of Science Education and Technology, 2022
Higher education instructors constantly rely on educational data to assess and evaluate the behavior of their students and to make informed decisions such as which content to focus on and how to best engage the students with it. Massive open online course (MOOC) platforms may assist in the data-driven instructional process, as they enable access…
Descriptors: College Faculty, Data Use, MOOCs, Teaching Methods
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Stewart, Bonnie; Miklas, Erica; Szcyrek, Samantha; Le, Thu – International Journal of Educational Technology in Higher Education, 2023
In recent decades, higher education institutions around the world have come to depend on complex digital infrastructures. In addition to registration, financial, and other operations platforms, digital classroom tools with built-in learning analytics capacities underpin many course delivery options. Taken together, these intersecting digital…
Descriptors: Learning Analytics, Higher Education, College Faculty, Teacher Attitudes
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Saadia, Drissi – International Journal of Web-Based Learning and Teaching Technologies, 2021
Cloud computing, internet of things (IoT), artificial intelligence, and big data are four very different technologies that are already discussed separately. The use of the four technologies is required to be more and more necessary in the present day in order to make them important components in today's world technology. In this paper, the authors…
Descriptors: Teaching Methods, Computer Science Education, Computer Software, Artificial Intelligence
Naomi LaRue Witham-Travers – ProQuest LLC, 2024
The purpose of this qualitative descriptive study was to explore how experienced elementary educators in Central Montana described their use of new knowledge from research evidence to inform their teaching practice. Data sources included 15 semi-structured interviews and two focus groups. The Cognitive Affective Model of Conceptual Change was…
Descriptors: Elementary School Teachers, Evidence Based Practice, Teaching Methods, Experienced Teachers
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