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Critical data studies, abstraction and learning analytics: Editorial to Selwyn’s LAK keynote and invited commentaries [PDF]

open access: yes, 2020
© 2019, UTS ePRESS. All rights reserved. This editorial introduces a special section of the Journal of Learning Analytics, for which Neil Selwyn’s keynote address to LAK ’18 has been written up as an article, “What’s the problem with learning analytics?”
Shum SJB
core   +1 more source

Learning Analytics: A Survey [PDF]

open access: yesInternational Journal of Computer Trends and Technology, 2014
Learning analytics is a research topic that is gaining increasing popularity in recent time. It analyzes the learning data available in order to make aware or improvise the process itself and/or the outcome such as student performance. In this survey paper, we look at the recent research work that has been conducted around learning analytics, framework
Usha Keshavamurthy, H. S. Guruprasad
openaire   +2 more sources

Learning Analytics

open access: yesProceedings of the Fifth International Conference on Learning Analytics And Knowledge, 2015
Since the emergence of learning analytics in North America, researchers and practitioners have worked to develop an international community. The organization of events such as SoLAR Flares and LASI Locals, as well as the move of LAK in 2013 from North America to Europe, has supported this aim.
Rebecca Ferguson   +6 more
openaire   +3 more sources

Towards a Convergent Development of Learning Analytics [PDF]

open access: yes, 2017
In the last 7 years, since the first LAK conference, Learning Analytics has grown rapidly as a field from a small group of interested scholars and practitioners to one of the most scientifically successful and institutionally accepted areas of Learning ...
Hershkovitz, A   +7 more
core   +1 more source

Supporting Student Agency with a Student-Facing Learning Analytics Dashboard [PDF]

open access: yes, 2023
Learning analytics dashboard (LAD) development has been criticized for being too data-driven and for developers lacking an understanding of the nontechnical aspects of learning analytics (LA).
Muukkonen, Hanni   +5 more
core   +1 more source

Time for Change: Why Learning Analytics Needs Temporal Analysis [PDF]

open access: yes, 2017
Learning is a process that occurs over time: We build understanding, change perspectives, and develop skills over the course of extended experiences. As a field, learning analytics aims to generate understanding of, and support for, such processes of ...
Bodong Chen   +5 more
core   +1 more source

Synergies of Learning Analytics and Learning Design: A Systematic Review of Student Outcomes

open access: yes, 2022
The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD).
Blumenstein, Marion
core   +1 more source

Learning analytics @ UC3M

open access: yes2013 IEEE Global Engineering Education Conference (EDUCON), 2013
Feedback is important for any activity, and learning is no exception. Whereas assessment can give summative feedback about the proficiency of the learning, learning analytics can give a much finer level of feedback about the learning process. Learning analytics can help in identifying the effectiveness of learning elements, can help in engaging ...
Carlos Delgado Kloos   +4 more
openaire   +2 more sources

Game Learning Analytics: Learning Analytics for Serious Games [PDF]

open access: yes, 2016
Video games have become one of the largest entertainment industries, and their power to capture the attention of players worldwide soon prompted the idea of using games to improve education. However, these educational games, commonly referred to as serious games, face different challenges when brought into the classroom, ranging from pragmatic issues ...
Freire, Manuel   +5 more
openaire   +2 more sources

Learning with Analytical Models [PDF]

open access: yes2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2019
To understand and predict the performance of scientific applications, several analytical and machine learning approaches have been proposed, each having its advantages and disadvantages. In this paper, we propose and validate a hybrid approach for performance modeling and prediction, which combines analytical and machine learning models.
Huda Ibeid   +4 more
openaire   +2 more sources

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