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Oleksandra Poquet – British Journal of Educational Technology, 2024
The paper argues that learning analytics as a research field can benefit from a theory-informed shared language to describe sensemaking of learning and teaching data. To make the case for such shared language, first, I critically review prominent sensemaking theories to then demonstrate how studies in learning analytics do not use coherent…
Descriptors: Learning Analytics, Data, Affordances, Theories
Soo Mang Lim; Husaina Banu Kenayathulla – Routledge, Taylor & Francis Group, 2024
This book explores Learning Analytics (LA) programmes and practices in Malaysia as well as looking at the underlying forces, dilemmas and policy challenges for quality assurance in higher education institutions (HEIs). This chapters provide a comprehensive discussion of trends in academic quality assurance in higher education. It articulates a…
Descriptors: Learning Analytics, Educational Quality, Quality Assurance, Higher Education
Kyle M.L. Jones; Lisa Janicke Hinchliffe – College & Research Libraries, 2025
As institutions of higher education further develop their learning analytics efforts, academic library practitioners are called upon to participate in these efforts and have opportunities to shape their campus strategies. Nonetheless, library practitioners may not be prepared with the knowledge, skills, and strategies to engage with campus…
Descriptors: Academic Libraries, Librarians, Privacy, Learning Analytics
Simon Kitto; H. L. Michelle Chiang; Olivia Ng; Jennifer Cleland – Advances in Health Sciences Education, 2025
There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic…
Descriptors: Feedback (Response), Learning Analytics, Educational Technology, Allied Health Occupations Education
Ran Bao; Jianyong Chen – Technology, Knowledge and Learning, 2025
Multimodal learning analysis emphasizes using diverse data from various sources and forms for precise examination of learning patterns. Despite recent rapid advancements in this field, conventional learning analysis remains predominantly cross-sectional and group-focused, which is insufficient for understanding continuous and personalized learning…
Descriptors: Learning Analytics, Data Use, Evaluation Methods, Learning Processes
Peer reviewedMegan N. Imundo; Siyuan Li; Jiachen Gong; Andrew Potter; Tracy Arner; Danielle S. McNamara – Grantee Submission, 2025
Personalized learning (PL) is a student-centered instructional approach in which learning goals, pacing, content, and environments are customized to address individual student needs (Bernacki et al., 2021; Ellis, 2009; Lee, 2014; Miliband, 2006; Office of Educational Technology, 2010; Sota, 2016; Zhang et al., 2020). In grades K-12, PL has been…
Descriptors: Self Determination, Individualized Instruction, Electronic Learning, Higher Education
Allyson Skene; Laura Winer; Erika Kustra – International Journal for Academic Development, 2024
This article explores potential uses, misuses, beneficiaries, and tensions of learning analytics in higher education. While those promoting and using learning analytics generally agree that ethical practice is imperative, and student privacy and rights are important, navigating the complex maze of ethical dilemmas can be challenging, particularly…
Descriptors: Learning Analytics, Higher Education, Ethics, Privacy
Qin Ni; Yifei Mi; Yonghe Wu; Liang He; Yuhui Xu; Bo Zhang – IEEE Transactions on Learning Technologies, 2024
Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…
Descriptors: Cognitive Style, Electronic Learning, Prediction, Identification
Xiaona Xia; Tianjiao Wang – Asia-Pacific Education Researcher, 2024
The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…
Descriptors: Learning, Behavior, Achievement, Learning Analytics
Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
Ping Tian; Jing Pu – International Journal of Information and Communication Technology Education, 2024
This paper discusses how Orff's music education system is combined with the localized teaching mode under the background of globalization, especially with the support of big data analysis to realize the innovation of music education. Orff's music education has attracted worldwide attention for its openness, diversity and innovation. In China, its…
Descriptors: Music Education, Teaching Methods, Foreign Countries, Learning Analytics
Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
Rozita Tsoni; Georgia Garani; Vassilios S. Verykios – Interactive Learning Environments, 2024
New challenges in education demand effective solutions. Although Learning Analytics (LA), Educational Data Mining (EDM) and the use of Big Data are often presented as a panacea, there is a lot of ground to be covered in order for the EDM to answer the real questions of educators. An important step toward this goal is to implement holistic…
Descriptors: Data Use, Distance Education, Learning Analytics, Educational Research
Paul Prinsloo; Mohammad Khalil; Sharon Slade – British Journal of Educational Technology, 2024
Students' physical and digital lives are increasingly entangled. It is difficult to separate students' "digital" well-being from their offline well-being given that artificial intelligence increasingly shapes both. Within the context of education's fiduciary and moral duty to ensure safe, appropriate and effective digital learning spaces…
Descriptors: Educational Technology, Technology Uses in Education, Well Being, Artificial Intelligence
Fabio Dovigo – Prospects, 2024
The 2021 UNESCO report "Reimagining Our Futures Together" presented a compelling case for establishing a new social contract on education that addresses the persistent exclusion of vulnerable individuals and ensures that knowledge and learning contribute to a more sustainable future. Research literature highlights a global trend towards…
Descriptors: Governance, Global Education, Early Childhood Education, Child Care
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