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Chen Zhan; Srecko Joksimovic; Djazia Ladjal; Thierry Rakotoarivelo; Ruth Marshall; Abelardo Pardo – IEEE Transactions on Learning Technologies, 2024
Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide,…
Descriptors: Privacy, Learning Analytics, Ethics, Data Use
Knight, Simon; Shibani, Antonette; Buckingham Shum, Simon – British Journal of Educational Technology, 2023
A burgeoning literature, policy landscape, and set of practice resources and guidelines have emerged around ethical educational technology development and implementation, particularly in the context of data or artificial intelligence informed tools. However, while these resources provide valuable tools to support navigation of the ethical…
Descriptors: Ethics, Learning Analytics, Educational Technology, Case Studies
Paraskevi Topali; Ruth Cobos; Unai Agirre-Uribarren; Alejandra Martínez-Monés; Sara Villagrá-Sobrino – Journal of Computer Assisted Learning, 2024
Background: Personalised and timely feedback in massive open online courses (MOOCs) is hindered due to the large scale and diverse needs of learners. Learning analytics (LA) can support scalable interventions, however they often lack pedagogical and contextual grounding. Previous research claimed that a human-centred approach in the design of LA…
Descriptors: Learning Analytics, MOOCs, Feedback (Response), Intervention
Mark Nichols – Open Learning, 2024
Learning analytics promise significant benefit to online education providers through improved, better-targeted student services. Much has been written about the potential of analytics and how they might be technically implemented, and various ethical considerations are published highlighting the significant potential risk of gathering,…
Descriptors: Learning Analytics, Ethics, Guidelines, Policy Formation
Pargman, Teresa Cerratto; McGrath, Cormac; Viberg, Olga; Knight, Simon – Journal of Learning Analytics, 2023
The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners…
Descriptors: Learning Analytics, Responsibility, Feminism, Ethics
Meijuan Li; Hongyun Liu; Mengfei Cai; Jianlin Yuan – Education and Information Technologies, 2024
In the human-to-human Collaborative Problem Solving (CPS) test, students' problem-solving process reflects the interdependency among partners. The high interdependency in CPS makes it very sensitive to group composition. For example, the group outcome might be driven by a highly competent group member, so it does not reflect all the individual…
Descriptors: Problem Solving, Computer Assisted Testing, Cooperative Learning, Task Analysis
Enes Küçük; Fidaye Cincil; Yasemin Karal – Journal of Theoretical Educational Science, 2025
AI technology, which is becoming more widespread day by day, also affects education and training processes. The use of AI tools in educational environments provides many benefits to teachers and students. However, the use of AI in education also raises some ethical concerns. The aim of this study was to reveal the ethical issues arising from the…
Descriptors: Ethics, Teaching Methods, Learning Analytics, Internet
Dimitrios Tzimas; Stavros Demetriadis – TechTrends: Linking Research and Practice to Improve Learning, 2025
Learning analytics (LA) is an educational innovation that enhances teaching practices and facilitates student learning. However, the degree of LA adoption across schools remains limited, and teachers who adopt LA do not engage with it consistently. Based on the unified theory of acceptance and use of technology (UTAUT) as a framework, we conducted…
Descriptors: Learning Analytics, Kindergarten, Elementary Secondary Education, Teacher Attitudes
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Victoria L. Bernhardt – Eye on Education, 2025
With the 5th Edition of Data Analysis for Continuous School Improvement, best-selling Victoria Bernhardt has written the go-to-resource for data analysis in your school! By incorporating collaborative structures to implement, monitor, and evaluate the vision and continuous improvement plan, this book provides a framework to show learning…
Descriptors: Learning Analytics, Data Analysis, Educational Improvement, Evaluation Methods
Rets, Irina; Herodotou, Christothea; Gillespie, Anna – Journal of Learning Analytics, 2023
The progressive move of higher education institutions (HEIs) towards blended and online environments, accelerated by COVID-19, and their access to a greater variety of student data has heightened the need for ethical learning analytics (LA). This need is particularly salient in light of a lack of comprehensive, evidence-based guidelines on ethics…
Descriptors: Ethics, Learning Analytics, Evidence Based Practice, Guidelines
Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
Sa Li; Jingjing Dong – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to deeply analyze and evaluate the changes in the comprehensive quality of college students' sports dance, the overall idea of systematically evaluating the changes in the comprehensive quality of college students' sports dance was established. Firstly, this article uses the triangular fuzzy number method to measure the evaluation…
Descriptors: Dance Education, Teaching Methods, Evaluation Methods, Programming Languages
Broos, Tom; Hilliger, Isabel; Pérez-Sanagustín, Mar; Htun, Nyi-Nyi; Millecamp, Martijn; Pesántez-Cabrera, Paola; Solano-Quinde, Lizandro; Siguenza-Guzman, Lorena; Zuñiga-Prieto, Miguel; Verbert, Katrien; De Laet, Tinne – British Journal of Educational Technology, 2020
Many Latin-American institutions recognise the potential of learning analytics (LA). However, the number of actual LA implementations at scale remains limited, notwithstanding considerable effort made to formulate guidelines and frameworks to support the LA policy development. Guidance on how to coordinate the interaction between the LA…
Descriptors: Learning Analytics, Policy Formation, Educational Policy, Guidelines
Xiuyu Lin; Zehui Zhan; Xuebo Zhang; Jiayi Xiong – IEEE Transactions on Learning Technologies, 2024
The attribution of learning success or failure is crucial for students' learning and motivation. Effective attribution of their learning success or failure in the context of a small private online course (SPOC) could generate students' motivation toward learning success while an incorrect attribution would lead to a sense of helplessness. Based on…
Descriptors: Learning Analytics, Learning Processes, Learning Motivation, Attribution Theory