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Liyanachchi Mahesha Harshani De Silva; María Jesús Rodríguez-Triana; Irene-Angelica Chounta; Gerti Pishtari – Journal of Computing in Higher Education, 2025
With technological advances, institutional stakeholders are considering evidence-based developments such as Curriculum Analytics (CA) to reflect on curriculum and its impact on student learning, dropouts, program quality, and overall educational effectiveness. However, little is known about the CA state of the art in Higher Education Institutions…
Descriptors: Learning Analytics, Curriculum Evaluation, Higher Education, Stakeholders
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
Hutt, Stephen; Das, Sanchari; Baker, Ryan S. – International Educational Data Mining Society, 2023
The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…
Descriptors: Data Analysis, Decision Making, Data Collection, Foreign Countries
Sahin, Muhittin; Ulucan, Aydin; Yurdugül, Halil – Education and Information Technologies, 2021
E-learning environments can store huge amounts of data on the interaction of learners with the content, assessment and discussion. Yet, after the identification of meaningful patterns or learning behaviour in the data, it is necessary to use these patterns to improve learning environments. It is notable that designs to benefit from these patterns…
Descriptors: Electronic Learning, Data Collection, Decision Making, Evaluation Criteria
Ian Hardy; Vicente Reyes; Louise G. Phillips; M. Obaidul Hamid – Journal of Education Policy, 2024
Data infrastructures exist in a variety of formats. This article draws on the insights of senior personnel involved in developing a new data dashboard in one state jurisdiction in Australia. While literature on dashboards often focuses on the teachers and learners influenced by them, there is less attention to those involved in their development…
Descriptors: Learning Analytics, Learning Processes, Learning Management Systems, Computer Software
Yang, Tzu-Chi; Liu, Yih-Lan; Wang, Li-Chun – Educational Technology & Society, 2021
The recently increased importance of practicing precision education has attracted much attention. To better understand students' learning and the relationship between their individual differences and learning outcomes, the bird-eye view possible for educational policymakers and stakeholders from educational data mining and institutional research…
Descriptors: Institutional Research, Prediction, Learning Analytics, Undergraduate Students
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Saar, Merike; Prieto, Luis P.; Rodríguez Triana, María Jesús – Technology, Pedagogy and Education, 2022
Research indicates that data-informed practice helps teachers change their teaching and promotes teacher professional development (TPD). Although educational data are often collected from digital spaces, in-action evidence from physical spaces is seldom gathered, providing an incomplete view of the classroom reality. Also, most learning analytics…
Descriptors: Data Collection, Data Use, Teaching Methods, Faculty Development
Cowan, Jackie; Hogan, Anna; Enright, Eimear – Journal of Educational Administration and History, 2022
The intensification of data collection practices in schooling -- often due to state accountability requirements -- has resulted in the widespread adoption of commercial student management systems (SMS) in schools. Drawing on a qualitative case study of a New Zealand primary school, this paper investigates its adoption of a commercial SMS, and the…
Descriptors: Commercialization, School Administration, Public Schools, Accountability
Beardsley, Marc; Martínez Moreno, Judit; Vujovic, Milica; Santos, Patricia; Hernández-Leo, Davinia – British Journal of Educational Technology, 2020
Advances in the field of multimodal learning analytics (MMLA) research is often accomplished by actively exploring new technologies and techniques related to the collection and analysis of data. Exploration of ethical principles and procedures for governing the use of new technologies and techniques, however, is not as readily pursued. As…
Descriptors: Records (Forms), Decision Making, Data Collection, Learning Analytics
Hakimi, Laura; Eynon, Rebecca; Murphy, Victoria A. – Review of Educational Research, 2021
This article presents the findings of a systematic qualitative analysis of research in the ethics of digital trace data use in learning and education. From the resulting analysis of 77 peer-reviewed studies, we (1) map the characteristics of research by study type, academic community, institutional setting, and national context; (2) identify the…
Descriptors: Ethics, Data Use, Data Collection, Learning Analytics
Perez, Zeke, Jr.; von Zastrow, Claus – Education Commission of the States, 2023
Data governance is a core obligation for leaders and staff across any agency that collects, stores or uses individuals' data. It ensures that individuals' personal information is protected, and can support the continuous improvement of data quality and use, particularly when it includes well-defined processes, structure and responsibilities.…
Descriptors: Governance, Data Use, Privacy, Information Management
Brown, Michael – Teaching in Higher Education, 2020
Despite their increasingly widespread adoption in post-secondary education, scholars and practitioners know very little about the impact of digital data displays on instructors' sense-making and academic planning. In this manuscript, I report the results of comparative case studies of five different introductory physics instructors at three…
Descriptors: College Faculty, Learning Analytics, Introductory Courses, Physics
Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Bezerra, Luis Naito Mendes; Silva, Márcia Terra – International Journal of Distance Education Technologies, 2020
In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…
Descriptors: Learning Analytics, Data Collection, Class Size, Online Courses
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