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Showing 1 to 15 of 19 results Save | Export
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Ean Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
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Susnjak, Teo; Ramaswami, Gomathy Suganya; Mathrani, Anuradha – International Journal of Educational Technology in Higher Education, 2022
This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…
Descriptors: Learning Analytics, Computer Interfaces, Artificial Intelligence, Prediction
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HaeJin Lee; Nigel Bosch – International Journal of STEM Education, 2024
Self-regulated learning (SRL) strategies can be domain specific. However, it remains unclear whether this specificity extends to different subtopics within a single subject domain. In this study, we collected data from 210 college students engaged in a computer-based learning environment to examine the heterogeneous manifestations of learning…
Descriptors: Computer Assisted Instruction, Self Management, Intellectual Disciplines, College Students
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Caitlin Mills, Editor; Giora Alexandron, Editor; Davide Taibi, Editor; Giosuè Lo Bosco, Editor; Luc Paquette, Editor – International Educational Data Mining Society, 2025
The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…
Descriptors: Artificial Intelligence, Data Analysis, Computer Science Education, Technology Uses in Education
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Kai Li – International Association for Development of the Information Society, 2023
Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…
Descriptors: Student Evaluation, Online Courses, Electronic Learning, Computer Literacy
Bronson Nichols – ProQuest LLC, 2021
Access to the Internet has increased connectivity between people across large distances. It has also amplified the desire of college students to engage in the illegal sharing and distribution of data. The purpose of this quantitative research study was to analyze the behaviors that motivate Michigan college students to engage in digital piracy.…
Descriptors: College Students, Intellectual Property, Copyrights, Information Technology
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Brann, Kristy L.; Naser, Shereen C.; Clough, Mac – Journal of Educational and Psychological Consultation, 2023
The current study describes the process of a participatory consultation framework, the Participatory Culture Specific Intervention Model (PCSIM), to plan and implement a data-based decision-making framework. The framework integrates proactive and systematic identification of emotional and behavioral needs as well as cognitive psychology techniques…
Descriptors: Consultation Programs, Data Use, Decision Making, Intervention
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C. Roch Turner, Editor – IGI Global, 2024
In the aftermath of the COVID-19 upheaval, special education professionals grapple with a seismic surge in student behavioral issues. The challenges are formidable, and the interventions available often fall short of making a meaningful impact. "Best Practices for Behavior Intervention in Special Education" steps in to assist the urgent…
Descriptors: Student Behavior, Intervention, Special Education, Best Practices
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Chinsook, Kittipong; Khajonmote, Withamon; Klintawon, Sununta; Sakulthai, Chaiyan; Leamsakul, Wicha; Jantakoon, Thada – Higher Education Studies, 2022
Big data is an important part of innovation that has recently attracted a lot of interest from academics and practitioners alike. Given the importance of the education industry, there is a growing trend to investigate the role of big data in this field. Much research has been undertaken to date in order to better understand the use of big data in…
Descriptors: Student Behavior, Learning Analytics, Computer Software, Rating Scales
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Ninasivincha-Apfata, Jhon Edwar; Quispe-Figueroa, Ricardo Carlos; Valderrama-Solis, Manuel Alejandro; Maraza-Quispe, Benjamin – World Journal on Educational Technology: Current Issues, 2021
The objective of the research is to develop a methodology to analyse a set of data extracted from a learning management system, in order to implement a dashboard, which can be used by teachers to make timely and relevant decisions to improve the teaching-learning processes. The methodology used consisted of analysing 9,257 records extracted…
Descriptors: Learning Analytics, Integrated Learning Systems, Visual Aids, Technology Uses in Education
Varun Mandalapu – ProQuest LLC, 2021
Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…
Descriptors: Models, Student Behavior, Learning Management Systems, Data Use
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Huang, Anna Y. Q.; Lu, Owen H. T.; Huang, Jeff C. H.; Yin, C. J.; Yang, Stephen J. H. – Interactive Learning Environments, 2020
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…
Descriptors: Academic Achievement, Data Use, Learning Analytics, Classification
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Jill Lawrence; Alice Brown; Petrea Redmond; Marita Basson – Student Success, 2019
Universities increasingly implement online delivery to strengthen students' access and flexibility. However, they often do so with limited understanding of the impact of online pedagogy on student engagement. To explore these issues, a research project was conducted investigating the use of course-specific learning analytics to 'nudge' students…
Descriptors: Learner Engagement, Learning Analytics, Data Use, Electronic Learning
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Naujokaitiene, Justina; Tamoliune, Giedre; Volungeviciene, Airina; Duart, Josep M. – Journal of New Approaches in Educational Research, 2020
Student engagement is one of the most relevant topics within the academic and research community nowadays. Higher education curriculum, teaching and learning integrate new technology- supported learning solutions. New methods and tools enhance teacher and learner interactions and influence learner engagement positively. This research addresses the…
Descriptors: Learning Analytics, Learner Engagement, Instructional Improvement, Interaction
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Orchard, Ryan K. – Journal of Educational Technology Systems, 2019
Learning management systems (LMS) allow for a variety of ways in which online multiple-choice assessments ("tests") can be configured, including the ability to allow for multiple attempts and options for which of and how the attempts will count. These options are usually chosen according to the instinct of the instructor; however, LMS…
Descriptors: Integrated Learning Systems, Data Use, Electronic Learning, Assignments
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