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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
Tytler, Russell; Ferguson, Joseph; White, Peta – Learning: Research and Practice, 2020
Increasingly, learning in science and mathematics is considered in terms of induction into the multimodal language practices of the disciplinary community. A strong strand of research in this tradition has involved students being challenged to invent multimodal language forms, and their ideas refined through structured guidance. Often, however,…
Descriptors: Science Instruction, Mathematics Instruction, Inquiry, Teaching Methods
Wright, Suzie; Fitzallen, Noleine; Shelley, Becky; Lang, Megan – Teaching Science, 2019
Inspiring children to pursue a career in science is a worthy pursuit for many reasons. One way to achieve this is to actively engage children in science, technology, engineering, and mathematics (STEM) learning from an early age. However, it is not always possible to integrate all the STEM fields in one activity. Rather, careful consideration of…
Descriptors: STEM Education, Vocational Interests, Elementary School Students, Student Research
Kennedy-Clark, Shannon; Galstaun, Vilma; Reimann, Peter – Teachers and Teaching: Theory and Practice, 2021
In this paper, we put forward the OTTO Model as a means for developing data literacy in pre-service teacher education. The OTTO Model was developed using a combination of quantitative and qualitative data drawn from a three-year study investigating the nature and development of pre-service teachers' data literacy. The aim of the study was to…
Descriptors: Preservice Teachers, Teacher Effectiveness, Teacher Evaluation, Models
Polak, Julia; Cook, Dianne – Journal of Statistics and Data Science Education, 2021
Kaggle is a data modeling competition service, where participants compete to build a model with lower predictive error than other participants. Several years ago they released a simplified service that is ideal for instructors to run competitions in a classroom setting. This article describes the results of an experiment to determine if…
Descriptors: Artificial Intelligence, Data Analysis, Models, Competition
Millei, Zsuzsa; Gallagher, Jannelle – Early Child Development and Care, 2017
Australian early childhood education still labours with the achievement of universal access and the production of comprehensive and consistent data to underpin a national evidence base. In this article, we attend to the processes led by numbers whereby new practices of quantification, rationalization and reporting are introduced and mastered in a…
Descriptors: Foreign Countries, Early Childhood Education, Preschool Education, Access to Education
Shum, Simon Buckingham; Sándor, Ágnes; Goldsmith, Rosalie; Bass, Randall; McWilliams, Mindy – Journal of Learning Analytics, 2017
When used effectively, reflective writing tasks can deepen learners' understanding of key concepts, help them critically appraise their developing professional identity, and build qualities for lifelong learning. As such, reflective writing is attracting substantial interest from universities concerned with experiential learning, reflective…
Descriptors: Reflection, Writing Assignments, Educational Research, Data Collection
Sha, Lele; Rakovic, Mladen; Li, Yuheng; Whitelock-Wainwright, Alexander; Carroll, David; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2021
Classifying educational forum posts is a longstanding task in the research of Learning Analytics and Educational Data Mining. Though this task has been tackled by applying both traditional Machine Learning (ML) approaches (e.g., Logistics Regression and Random Forest) and up-to-date Deep Learning (DL) approaches, there lacks a systematic…
Descriptors: Classification, Computer Mediated Communication, Learning Analytics, Data Analysis
Wilson, Mark; Gochyyev, Perman; Scalise, Kathleen – Online Learning, 2016
This paper summarizes initial field-test results from data analytics used in the work of the Assessment and Teaching of 21st Century Skills (ATC21S) project, on the "ICT Literacy--Learning in digital networks" learning progression. This project, sponsored by Cisco, Intel and Microsoft, aims to help educators around the world enable…
Descriptors: Data Collection, Data Analysis, Technological Literacy, Social Networks
West, Deborah; Heath, David; Huijser, Henk – Online Learning, 2016
This paper presents a dialogical tool for the advancement of learning analytics implementation for student retention in Higher Education institutions. The framework was developed as an outcome of a project commissioned and funded by the Australian Government's "Office for Learning and Teaching". The project took a mixed-method approach…
Descriptors: School Holding Power, Models, Higher Education, Mixed Methods Research
Harvey, Marina; Kosman, Bronwyn – Journal of Higher Education Policy and Management, 2014
The development of a standards-based assessment policy represented a significant cultural shift in assessment practice at one university. Concurrently, the implementation of a policy framework represented a significant procedural shift in policy development and review. The assessment policy was the first policy scheduled to be reviewed through the…
Descriptors: Educational Assessment, Educational Policy, Higher Education, Models
Sharrock, Geoff – Journal of Higher Education Policy and Management, 2015
This article considers recent public debates about massive open online courses (MOOCs) and their potential to transform higher education. Drawing on reports and media commentary, it probes the claims and counterclaims of MOOC proponents and MOOC sceptics. It considers the implications for students, governments, institutions and scholars…
Descriptors: Foreign Countries, Online Courses, Higher Education, Blended Learning
Chung, Kon Shing Kenneth; Paredes, Walter Christian – Educational Technology & Society, 2015
In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…
Descriptors: Social Networks, Online Courses, Educational Technology, Electronic Learning
Ambrosetti, Angelina; Dekkers, John; Knight, Bruce Allen – Mentoring & Tutoring: Partnership in Learning, 2017
Within many preservice teacher education programs in Australia, mentoring is used as the overarching methodology for the professional placement. The professional placement is considered to be a key component of learning to teach, and typically a dyad mentoring model is utilized. However, it is reported that many preservice teachers experience a…
Descriptors: Mentors, Models, Preservice Teacher Education, Preservice Teachers
Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models