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Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
Manel van Kessel; Inge Molenaar; Carolien A. N. Knoop-van Campen; Mario de Jonge; Nadira Saab – Journal of Learning Analytics, 2025
Adaptive learning technologies (ALTs) provide teachers with student data in teacher dashboards (TDs). However, there is substantial variation in dashboard use among teachers, and many find it difficult to draw conclusions based on student data. Teachers' skills, knowledge, and contextual conditions are believed to be essential in effective…
Descriptors: Elementary School Teachers, Technology Uses in Education, Teacher Attitudes, Data Collection
Zhi Li; Wenxiang Zhang – Education and Information Technologies, 2025
In the swiftly changing realm of education, technology serves as a key instrument in transforming the methods of teaching, learning experiences, and educational outcomes. Legal and governance issues, integral to maintaining order and justice in societies, are equally pertinent in the realm of education. The digital age introduces concerns like…
Descriptors: Educational Technology, Technology Uses in Education, Technological Advancement, Legal Responsibility
Kean Birch; Janja Komljenovic; Sam Sellar; Morten Hansen – Learning, Media and Technology, 2025
The COVID pandemic highlighted the increasing deployment of digital technologies in educational institutions, defined as 'edtech'. The most visible edtech was video conferencing software, but a swathe of edtech startups have sought to roll out their products and services to educational institutions. We focus specifically on the deployment of…
Descriptors: Educational Technology, Technology Uses in Education, Higher Education, Videoconferencing
Atabek Yigit, Elif; Balkan Kiyici, Fatime; Kiyici, Mübin – International Journal of Technology in Education and Science, 2022
The purpose of this study is to determine the trend in studies related to Science instruction and ICT. The study has been studied with extensive data, and the data mining method has been used. Some articles entered the ERIC database within the research scope and published in January 2020, starting from 1965. In this context, 1,783,418 articles…
Descriptors: Technology Uses in Education, Science Instruction, Literature Reviews, Data Use
Catherine Ferguson – Issues in Educational Research, 2025
The use of artificial intelligence (AI) in higher education has mostly focused on issues associated with teaching and assessment. In this paper I used AI to support the analysis of data which consisted of public comments on a newspaper article. This small, low risk research was chosen to demonstrate the potential use of AI and how it may support…
Descriptors: Artificial Intelligence, Data Analysis, Technology Uses in Education, Higher Education
Nurten Gündüz; Mehmet Sincar – Problems of Education in the 21st Century, 2025
Without regulations for higher education institutions in the metaverse, ethical transgressions are unavoidable. Educational metaverse systems, which integrate artificial intelligence, essentially depend on big data as their core technology, leading to considerable privacy issues. Therefore, this study examines data privacy and security issues, a…
Descriptors: Higher Education, Information Security, Privacy, Artificial Intelligence
Robin Clausen – Discover Education, 2025
Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…
Descriptors: Dropout Prevention, Data Analysis, Principals, School Counselors
Krista Bixler; Marjorie Ceballos – Leadership and Policy in Schools, 2025
Instructional leadership is a complex dimension, which requires that principals possess expertise in goal setting, leading the instructional program, and creating the conditions for a successful school environment. Effective instructional leaders manage the instructional program by planning, coordinating, and evaluating the work of teachers and…
Descriptors: Principals, Instructional Leadership, Artificial Intelligence, Educational Technology
Zeynab (Artemis) Mohseni; Italo Masiello; Rafael M. Martins – Education and Information Technologies, 2024
There is a significant amount of data available about students and their learning activities in many educational systems today. However, these datasets are frequently spread across several different digital services, making it challenging to use them strategically. In addition, there are no established standards for collecting, processing,…
Descriptors: Elementary School Students, Data, Individual Development, Learning Trajectories
Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
Rafael Ferreira Mello; Elyda Freitas; Luciano Cabral; Filipe Dwan Pereira; Luiz Rodrigues; Mladen Rakovic; Jackson Raniel; Dragan Gaševic – Journal of Learning Analytics, 2024
Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…
Descriptors: Literature Reviews, Learning Analytics, Natural Language Processing, Data Collection
Knox, Jeremy – Learning, Media and Technology, 2023
This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…
Descriptors: Ethics, Artificial Intelligence, Social Justice, Governance
Teng Teng – European Journal of Education, 2025
The application of big data in education sparks debates on its effects. Researchers explore its impact on learning outcomes, with divergent views on neural networks' potential and negative consequences. This study assesses big data's influence on basic literacy skills in music education for 5th graders. Using clustering and k-density analyses,…
Descriptors: Elementary School Students, Music Education, Data Analysis, Data Collection
Nongluk Weerasiri; Pinanta Chatwattana – Journal of Education and Learning, 2025
The community-based learning model via game simulation to promote community public health diagnosis skills, or CBL model via game simulation, is a research tool that was devised based on the concepts of public health diagnosis using the seven community tools (geo-social mapping, genogram, community organization chart, local health system,…
Descriptors: Public Health, Educational Games, Computer Simulation, Game Based Learning

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