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Showing 1 to 15 of 82 results Save | Export
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Mirjam Sophia Glessmer; Rachel Forsyth – Teaching & Learning Inquiry, 2025
Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…
Descriptors: Artificial Intelligence, Research Methodology, Data Analysis, Scholarship
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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
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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
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Normandeau, Magdalen; Kolomitro, Klodiana; Maher, Patrick T. – Canadian Journal for the Scholarship of Teaching and Learning, 2020
The path to publication is often long, emotional, and bewildering. We share key insights from our experience as authors, educators, and members of the editorial board with The Canadian Journal for the Scholarship of Teaching and Learning that we hope will help authors better understand and navigate the path to publication. In writing a compelling…
Descriptors: Writing for Publication, Scholarship, Instruction, Learning
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Jørnø, Rasmus Leth; Gynther, Karsten – Journal of Learning Analytics, 2018
The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term "actionable insight" means. This selective literature review provides a look into…
Descriptors: Data Analysis, Learning, Educational Research, Definitions
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Muslim, Arham; Chatti, Mohamed Amine; Bashir, Muhammad Bassim; Barrios Varela, Oscar Eduardo; Schroeder, Ulrik – Journal of Learning Analytics, 2018
Open Learning Analytics (OLA) is an emerging concept in the field of Learning Analytics (LA). It deals with learning data collected from multiple environments and contexts, analyzed with a wide range of analytics methods to address the requirements of different stakeholders. Due to this diversity in different dimensions of OLA, the LA developers…
Descriptors: Data Analysis, Learning, Models, Design
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Knox, Jeremy – International Review of Education, 2018
This article examines how algorithms are shaping student learning in massive open online courses (MOOCs). Following the dramatic rise of MOOC platform organisations in 2012, over 4,500 MOOCs have been offered to date, in increasingly diverse languages, and with a growing requirement for fees. However, discussions of "learning" in MOOCs…
Descriptors: Online Courses, Mathematics, Learning, Data Collection
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Knox, Jeremy; Williamson, Ben; Bayne, Sian – Learning, Media and Technology, 2020
This paper examines visions of 'learning' across humans and machines in a near-future of intensive data analytics. Building upon the concept of 'learnification', practices of 'learning' in emerging big data-driven environments are discussed in two significant ways: the "training" of machines, and the "nudging" of human…
Descriptors: Data Collection, Data Analysis, Artificial Intelligence, Man Machine Systems
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Kelly, Anthony E. – Journal of Learning Analytics, 2017
In this short thought-piece, I attempt to capture the type of freewheeling discussions I had with our late colleague, Mika Seppälä, a research mathematician from Helsinki. Mika, not being a psychometrician or learning scientist, was blissfully free from the design constraints that experts sometimes ingest, unwittingly. I also draw on delightful…
Descriptors: Data, Learning, Data Analysis, Numbers
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Chen, Bodong; Knight, Simon; Wise, Alyssa Friend – Journal of Learning Analytics, 2018
The importance of temporality in learning has been long established, but it is only recently that serious attention has begun to be paid to the precise identification, measurement, and analysis of the temporal features of learning. From 2009 to 2016, a series of temporality workshops explored temporal concepts and data types, analysis methods for…
Descriptors: Time Factors (Learning), Data Analysis, Learning, Experience
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Klašnja-Milicevic, Aleksandra; Ivanovic, Mirjana – Informatics in Education, 2018
Amount of educational data has been constantly increasing for years in all domains and kinds of education (formal or informal) and educational activities (teaching, learning, assessment, use of social media and collaboration and so on). Accordingly, Learning Analytics (LA) become a powerful mechanism for supporting learners, instructors, teachers,…
Descriptors: Data Analysis, Learning, Technology Uses in Education, Higher Education
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Tsai, Yi-Shan; Moreno-Marcos, Pedro Manuel; Jivet, Ioana; Scheffel, Maren; Tammets, Kairit; Kollom, Kaire; Gaševic, Dragan – Journal of Learning Analytics, 2018
This paper introduces a learning analytics policy and strategy framework developed by a cross-European research project team -- SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed adapting…
Descriptors: Data Analysis, Learning, Educational Policy, Higher Education
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Ifenthaler, Dirk – TechTrends: Linking Research and Practice to Improve Learning, 2017
Higher education institutions and involved stakeholders can derive multiple benefits from learning analytics by using different data analytics strategies to produce summative, real-time, and predictive insights and recommendations. However, are institutions and academic as well as administrative staff prepared for learning analytics? A learning…
Descriptors: Higher Education, Learning, Data Analysis, Technology Uses in Education
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Bronnimann, Jurg; West, Deborah; Huijser, Henk; Heath, David – Innovative Higher Education, 2018
In this article we report on the findings of a project funded by the Australian Office for Learning and Teaching and entitled "Learning Analytics: Assisting Universities with Student Retention." While this project was primarily focused on retention as a potential outcome of learning analytics, its application could be related to the…
Descriptors: Scholarship, Instruction, Learning, Foreign Countries
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Mahzoon, Mohammad Javad; Maher, Mary Lou; Eltayeby, Omar; Dou, Wenwen; Grace, Kazjon – Journal of Learning Analytics, 2018
Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a model based on temporal relationships of heterogeneous data as the basis for building predictive models. We show how within- and between-semester temporal patterns can provide insight into the…
Descriptors: Data Analysis, Learning, Models, Time
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