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Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
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Mary Francis; Mejai Bola Mike Avoseh; Karen Card; Lisa Newland; Kevin Streff – Journal of Learning Analytics, 2023
This single-site case study will seek to answer the following question: how is the concept of privacy addressed in relation to a student success information system within a small, public institution of higher education? Three themes were found within the inductive coding process, which used interviews, documentation, and videos as data resources.…
Descriptors: Privacy, Online Systems, Small Colleges, Public Colleges
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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
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Khajonmote, Withamon; Chinsook, Kittipong; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jansawang, Natchanok; Jantakoon, Thada – Journal of Education and Learning, 2022
The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…
Descriptors: MOOCs, Data Collection, Student Behavior, Computer Software
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Jones, Kyle M. L.; Goben, Abigail; Perry, Michael R.; Regalado, Mariana; Salo, Dorothea; Asher, Andrew D.; Smale, Maura A.; Briney, Kristin A. – portal: Libraries and the Academy, 2023
Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…
Descriptors: College Students, Student Attitudes, Data Collection, Learning Analytics
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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
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Taolin Zhang; Shuwen Jia; Charoula Angeli – International Journal of Web-Based Learning and Teaching Technologies, 2024
Considering the shortcomings of large evaluation errors, long time, human, and material resources in the evaluation process of the current college teaching mode to improve the accuracy of the evaluation of college teaching mode and reduce the cost of the evaluation, this study proposes an evaluation method for college teaching methods based on…
Descriptors: Evaluation Methods, Educational Change, Learning Analytics, Educational Technology
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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
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Hussain, Sadiq; Gaftandzhieva, Silvia; Maniruzzaman, Md.; Doneva, Rositsa; Muhsin, Zahraa Fadhil – Education and Information Technologies, 2021
Educational data mining helps the educational institutions to perform effectively and efficiently by exploiting the data related to all its stakeholders. It can help the at-risk students, develop recommendation systems and alert the students at different levels. It is beneficial to the students, educators and authorities as a whole. Deep learning…
Descriptors: Regression (Statistics), Academic Achievement, Learning Analytics, Models
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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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Matthieu Cisel – Canadian Journal of Education, 2024
Over the last decade, teachers in France have been increasingly pressured to use digital learning environments, and to shift from grade-based to skill-based assessment. Educational dashboards, which measure student input electronically, could foster such a transition by providing insights into learners' performances. However, such dashboards could…
Descriptors: Foreign Countries, Computer Assisted Testing, Summative Evaluation, Elementary School Students
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Gaftandzhieva, Silvia; Docheva, Mariya; Doneva, Rositsa – Education and Information Technologies, 2021
Many educational institutions use a large number of information systems to automate their activities for different stakeholders' groups -- learning management systems, student diary, library system, digital repositories, management system, etc. This leads to a significant increase in the volume and variety of data that can be captured, stored, and…
Descriptors: Foreign Countries, Learning Analytics, Secondary Education, Stakeholders
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Borchers, Conrad; Rosenberg, Joshua M.; Swartzentruber, Rita M. – Educational Technology Research and Development, 2023
Facebook is widely used and researched. However, though the data generated by educational technology tools and social media platforms other than Facebook have been used for research purposes, very little research has used Facebook posts as a data source--with most studies relying on self-report studies. While it has historically been impractical…
Descriptors: Educational Research, Social Media, Computer Mediated Communication, Written Language
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Elena Drugova; Irina Zhuravleva; Ulyana Zakharova; Adel Latipov – Journal of Computer Assisted Learning, 2024
Background: Driven by the ongoing need to provide high-quality learning and teaching, universities recently have shown an increased interest in using learning analytics (LA) for improving learning design (LD). However, the evidence of such improvements is scarce, and the maturity of such research is unclear. Objectives: This study is aimed to…
Descriptors: Learning Analytics, Instructional Design, Higher Education, Instructional Improvement
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Ignacio Villagrán; Rocio Hernández; Gregory Schuit; Andrés Neyem; Javiera Fuentes; Loreto Larrondo; Elisa Margozzini; María T. Hurtado; Zoe Iriarte; Constanza Miranda; Julián Varas; Isabel Hilliger – Journal of Learning Analytics, 2024
Remote technology has been widely incorporated into health professions education. For procedural skills training, effective feedback and reflection processes are required. Consequently, supporting a self-regulated learning (SRL) approach with learning analytics dashboards (LADs) has proven beneficial in online environments. Despite the potential…
Descriptors: Feedback (Response), Independent Study, Skill Development, Learning Analytics
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