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Davies, Randall; Allen, Gove; Albrecht, Conan; Bakir, Nesrin; Ball, Nick – Education Sciences, 2021
Analyzing the learning analytics from a course provides insights that can impact instructional design decisions. This study used educational data mining techniques, specifically a longitudinal k-means cluster analysis, to identify the strategies students used when completing the online portion of an online flipped spreadsheet course. An analysis…
Descriptors: Data Analysis, Identification, Learning Strategies, Electronic Learning
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Emma R. Dear; Bryce D. McLeod; Nicole M. Peterson; Kevin S. Sutherland; Michael D. Broda; Alex R. Dopp; Aaron R. Lyon – Grantee Submission, 2024
Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the…
Descriptors: Measures (Individuals), Data Collection, Observation, Learning Analytics
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Korah Wiley; Yannis Dimitriadis; Marcia Linn – British Journal of Educational Technology, 2024
This paper describes a Human-Centred Learning Analytics (HCLA) design approach for developing learning analytics (LA) dashboards for K-12 classrooms that maintain both contextual relevance and scalability--two goals that are often in competition. Using mixed methods, we collected observational and interview data from teacher partners and…
Descriptors: Learning Analytics, Learning Management Systems, Kindergarten, Elementary Secondary Education
Pallavi Singh – ProQuest LLC, 2024
As the engineering education system continuously evolves to meet the demands of modern industry and society, there is a need for a methodology that would manage and resolve the complexities inherent in engineering educational systems. Model-based Systems Engineering (MBSE) is a structured approach to system design that utilizes models across all…
Descriptors: Engineering Education, Models, Learning Analytics, Higher Education
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Umar Bin Qushem; Solomon Sunday Oyelere; Gökhan Akçapinar; Rogers Kaliisa; Mikko-Jussi Laakso – Technology, Knowledge and Learning, 2024
Predicting academic performance for students majoring in computer science has long been a significant field of research in computing education. Previous studies described that accurate prediction of students' early-stage performance could identify low-performing students and take corrective action to improve performance. Besides, adopting machine…
Descriptors: Predictor Variables, Learning Analytics, At Risk Students, Computer Science
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Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
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Linxuan Zhao; Dragan Gaševic; Zachari Swiecki; Yuheng Li; Jionghao Lin; Lele Sha; Lixiang Yan; Riordan Alfredo; Xinyu Li; Roberto Martinez-Maldonado – British Journal of Educational Technology, 2024
Effective collaboration and teamwork skills are critical in high-risk sectors, as deficiencies in these areas can result in injuries and risk of death. To foster the growth of these vital skills, immersive learning spaces have been created to simulate real-world scenarios, enabling students to safely improve their teamwork abilities. In such…
Descriptors: Automation, Transcripts (Written Records), Coding, Teamwork
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Olga Agatova; Alexander Popov; Suad Abdalkareem Alwaely – Interactive Learning Environments, 2024
The paper examines the special aspects of using Big Data technology in education. The population was made up of 356 third-year university students. To study Big Data technology, a questionnaire was used where respondents rated: cloud technology; apps; Massive Open Online Courses (MOOCs) and digital learning platforms. The study suggested that the…
Descriptors: Data Use, Learning Processes, Technology Uses in Education, Information Storage
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John Jerrim; Alex Jones – School Effectiveness and School Improvement, 2024
School inspections are a common feature of many education systems. These may be informed by quantitative background data about schools. It is recognised that there are pros and cons of using such quantitative information as part of the inspection process, though these have rarely been succinctly set out. This paper seeks to fill this gap by…
Descriptors: Inspection, Foreign Countries, Statistical Analysis, Educational Quality
Phillip Scott Moses – ProQuest LLC, 2024
The Society for Learning Analytics Research (SoLAR) defines learning analytics as "the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs" (SoLAR, n.d.). To fully realize the potential of learning…
Descriptors: Learning Analytics, Change Strategies, Learning Processes, Higher Education
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Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
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Matthew Mauntel; Michelle Zandieh – International Journal of Research in Undergraduate Mathematics Education, 2024
In this article we analyze how students reason about linear combinations across multiple digital environments. We present the work of three groups of undergraduate students in the Southeast United States (US) who were considered ready to take linear algebra. The students played the game "Vector Unknown," reflected upon aspects of their…
Descriptors: Video Games, Algebra, Mathematics Instruction, Teaching Methods
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Ishteyaaq Ahmad; Sonal Sharma; Rajesh Singh; Anita Gehlot; Lovi Raj Gupta; Amit Kumar Thakur; Neeraj Priyadarshi; Bhekisipho Twala – Cogent Education, 2024
This study explores the potential benefits of integrating Industry 4.0 technologies into educational settings, focusing on Artificial Intelligence/Machine Learning, Augmented Reality, Big Data, Blockchain, Cloud Computing, Internet of Things, Metaverse, Robotics, and Virtual Reality. The aim is to develop learning environments that are more…
Descriptors: Student Diversity, Inclusion, Technology Uses in Education, Educational Technology
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Nesra Yannier; Scott E. Hudson; Henry Chang; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2024
Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…
Descriptors: Artificial Intelligence, Computer Software, Feedback (Response), Outcomes of Education
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Yung-Hsiang Hu; Bo-Kai Liao; Chieh-Lun Hsieh – Interactive Learning Environments, 2024
It is known that teachers commonly utilize learning platforms equipped with Learning Analytics Dashboards (LAD) to support students in their Self-Regulated Learning (SRL) endeavors. However, students may struggle to effectively employ LAD due to a lack of sufficient metacognitive skills. Co-regulation of learning (CoRL) has been proven to…
Descriptors: Program Effectiveness, Gamification, Learning Analytics, Educational Technology
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