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Eirini Kalaitzopoulou; Athanasios Christopoulos; Paul Matthews – Informatics in Education, 2025
While research on Learning Analytics (LA) is plentiful, it often prioritises perspectives on LA systems over the practical ways instructors use data to analyse and refine the learning process per se. The present study addresses this inadequacy by investigating how student data is employed by educators in UK Higher Education Institutions (HEIs) and…
Descriptors: Information Literacy, Learning Analytics, Data Use, College Faculty
Marijn Martens; Ralf De Wolf; Lieven De Marez – Technology, Knowledge and Learning, 2025
Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…
Descriptors: Algorithms, Decision Making, Learning Analytics, Secondary School Students
Anil Harun Kiliç; Serkan Izmirli – Asian Journal of Distance Education, 2024
This study conducted a systematic literature review of articles on learning analytics published between 2004 and January 2024. A total of 1,064 articles, identified using the keyword "learning analytic*" in the Scopus database, were analyzed. The study integrated systematic literature review and bibliometric analysis approaches to…
Descriptors: Literature Reviews, Learning Analytics, Foreign Countries, Data Use
Rotem Abdu; Shai Olsher – Mathematics Teacher Education and Development, 2025
Group composition affects learning by individuals. Dialogic pedagogy approaches demonstrate that this is particularly true when each grouped student knows something others do not (i.e., "mutuality" grouping). Learning analytics can help grouping by providing teachers with data on students' content-specific learning. What are mathematics…
Descriptors: Mathematics Teachers, Grouping (Instructional Purposes), Learning Analytics, Mathematics Instruction
Isabel Hilliger; Constanza Miranda; Sergio Celis; Mar Pérez-Sanagustín – British Journal of Educational Technology, 2024
Several studies have indicated that stakeholder engagement could ensure the successful adoption of learning analytics (LA). Considering that researchers and tech developers may not be aware of how LA tools can derive meaningful and actionable information for everyday use, these studies suggest that participatory approaches based on human-centred…
Descriptors: Learning Analytics, Higher Education, Stakeholders, College Curriculum
Zeynab Mohseni; Italo Masiello; Rafael M. Martins; Susanna Nordmark – Journal of Learning Analytics, 2024
Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this…
Descriptors: Learning Analytics, Visual Learning, Visualization, Intervention
Selwyn, Neil – Research Papers in Education, 2022
Schools now face considerable pressure to be using educational data to inform decision-making and become more efficient. Key to this rise of the 'data-driven' school is the increased use of digital technologies -- with computer-based data processing fuelling hopes for the technology-driven 'smart schooling' and a general 'datafication' of…
Descriptors: Data Use, Decision Making, Computer Uses in Education, Foreign Countries
Rania Mohamed Al Morsy; Mahmoud Kamal Abouraia; Hany Mohamed Galal; Nehad Hussein Elgamal – International Society for Technology, Education, and Science, 2024
To broaden the scope of innovation that leverages contemporary technologies, education sectors worldwide are depending more and more on creative technological tools. On the other hand, not much research has been done on how these tools are adopted and used, or how they can improve decision-making in non-Western contexts. As a result, the goal of…
Descriptors: Learning Analytics, Decision Making, Foreign Countries, Private Colleges
Rand Al-Dmour; Hani Al-Dmour; Yazeed Al-Dmour; Ahmed Al-Dmour – Journal of International Students, 2025
In this study, we examine the role of AI-driven marketing in international student recruitment, focusing on how perceived usefulness, trust, and personalization influence decision-making. Grounded in the Technology Acceptance Model (TAM), the Trust-Based Decision-Making Model, and the Personalization--Privacy Paradox, we studied how AI-powered…
Descriptors: Foreign Students, Student Recruitment, Trust (Psychology), Privacy
Hamad, Faten; Fakhuri, Hussam; Abdel Jabbar, Sinaria – New Review of Academic Librarianship, 2022
Libraries hold large amounts of data, which can contribute to improvements in the quality of library services. Data resources of modern library have the characteristics of big-data, where library can use big-data methods to achieve reform and innovation, including resource transferring, resource utilisation, social identity, thinking innovation.…
Descriptors: Foreign Countries, Learning Analytics, Academic Libraries, Data Use
Tomás Bautista-Godínez; Gerardo Castañeda-Garza; Ricardo Pérez Mora; Hector G. Ceballos; Verónica Luna de la Luz; J. Gerardo Moreno-Salinas; Irma Rocío Zavala-Sierra; Roberto Santos-Solórzano; Carlos Iván Moreno Arellano; Melchor Sánchez-Mendiola – Journal of Learning Analytics, 2024
The adoption of learning analytics (LA) in higher education institutions (HEIs) in Mexico is still at an early stage despite increasing global interest and advances in the field. The use of educational data remains a challenging puzzle for many universities, which strive to provide students, teachers, and institutional administrators with…
Descriptors: Foreign Countries, Learning Analytics, Universities, Program Implementation
Hector Vargas; Ruben Heradio; Gonzalo Farias; Zhongcheng Lei; Luis de la Torre – IEEE Transactions on Education, 2024
Contribution: A competency assessment framework that enables learning analytics for course monitoring and continuous improvement. Our work fills the gap in systematic methods for competency assessment in higher education. Background: Many institutions are shifting toward competency-based education (CBE), thus encouraging their educators to start…
Descriptors: Competency Based Education, Learning Analytics, Higher Education, College Students
Iouri Kotorov; Yuliya Krasylnykova; Mar Pérez-Sanagustín; Fernanda Mansilla; Julien Broisin – Journal of Learning Analytics, 2024
The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…
Descriptors: Decision Making, Case Studies, Instructional Innovation, Teaching Methods
Rebecka Rundquist; Kristina Holmberg; John Rack; Zeynab Mohseni; Italo Masiello – Journal of Learning Analytics, 2024
The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…
Descriptors: Learning Analytics, Elementary Secondary Education, Mathematics Education, Data Analysis
Rosemary Vellar; Boris Handal; Sean Kearney; Chris Forlin – Issues in Educational Research, 2024
Evidence based decision making is essential for enabling improved student learning. Teacher motivations and beliefs about the types and use of data are critical determinants of decision making. Our research explored the types of data teachers use and consider valuable when measuring improvement in student learning. Findings from 294 teachers from…
Descriptors: Catholic Schools, Elementary Secondary Education, Learning Analytics, Student Needs

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