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Showing 46 to 60 of 172 results Save | Export
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Haruna Abe; Kay Colthorpe; Pedro Isaias – Discover Education, 2025
To improve the online learning experience, adaptive learning technologies are being used to personalise learning content to suit individual learning needs, with learning analytics being integrated to collect data about the student usage behaviour on the platform. Research indicates that the adaptive learning platforms promote a supportive learning…
Descriptors: Physiology, Science Instruction, Instructional Design, Learning Management Systems
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Li, Warren; Sun, Kaiwen; Schaub, Florian; Brooks, Christopher – International Journal of Artificial Intelligence in Education, 2022
Use of university students' educational data for learning analytics has spurred a debate about whether and how to provide students with agency regarding data collection and use. A concern is that students opting out of learning analytics may skew predictive models, in particular if certain student populations disproportionately opt out and biases…
Descriptors: College Students, Learning Analytics, Student Attitudes, Informed Consent
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Daisy Das; Masum Ahmed – E-Learning and Digital Media, 2024
Many educational institutions lack well-defined, targeted policies to address problems relating to student smartphone use on campus. In this study, we analyse the patterns of student smartphone use on academic campuses and propose a range of policy measures to address the problems arising from such use. Our research, which draws on primary data…
Descriptors: Student Attitudes, Telecommunications, Handheld Devices, Technology Uses in Education
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Grace Leah Akinyi; Robert Oboko; Lawrence Muchemi – Electronic Journal of e-Learning, 2024
The future of university learning in Sub-Saharan Africa has become increasingly digitally transformed by both e-Learning, and learning analytics, post-COVID-19 pandemic. Learning analytics intervention is critical for effective support of socially-shared regulated learning skills, which are crucial for twenty-first-century e-Learners.…
Descriptors: Electronic Learning, Student Attitudes, Learning Analytics, Feedback (Response)
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Paul Joseph-Richard; James Uhomoibhi – INFORMS Transactions on Education, 2024
Scholarly interests in developing personalized learning analytics dashboards (LADs) in universities have been increasing. LADs are data visualization tools for both teachers and learners that allow them to support student success and improve teaching and learning. In most LADs, however, a teacher-centric, institutional view drives their designs,…
Descriptors: Learning Analytics, Learning Management Systems, Independent Study, Undergraduate Students
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Marek Hatala; Sina Nazeri – Journal of Learning Analytics, 2024
An essential part of making dashboards more effective in motivating students and leading to desirable behavioural change is knowing what information to communicate to the student and how to frame and present it. Most of the research studying dashboards' impact on learning analyzes learning indicators of students as a group. Understanding how a…
Descriptors: Educational Technology, Information Dissemination, Learning Processes, Algorithms
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Esnaashari, Shadi; Gardner, Lesley A.; Arthanari, Tiru S.; Rehm, Michael – Journal of Computer Assisted Learning, 2023
Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…
Descriptors: Metacognition, Student Attitudes, Learning Strategies, Questionnaires
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Gomathy Ramaswami; Teo Susnjak; Anuradha Mathrani – Journal of Learning Analytics, 2023
Learning Analytics Dashboards (LADs) are gaining popularity as a platform for providing students with insights into their learning behaviour patterns in online environments. Existing LAD studies are mainly centred on displaying students' online behaviours with simplistic descriptive insights. Only a few studies have integrated predictive…
Descriptors: Learner Engagement, Learning Analytics, Electronic Learning, Student Behavior
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Tanjun Liu; Dana Gablasova – Computer Assisted Language Learning, 2025
Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…
Descriptors: Phrase Structure, Learning Analytics, English (Second Language), Second Language Instruction
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Mahmoud, Mai; Dafoulas, Georgios; Abd ElAziz, Rasha; Saleeb, Noha – International Journal of Information and Learning Technology, 2021
Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…
Descriptors: Learning Analytics, Stakeholders, Expectation, Higher Education
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Mutimukwe, Chantal; Viberg, Olga; Oberg, Lena-Maria; Cerratto-Pargman, Teresa – British Journal of Educational Technology, 2022
Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…
Descriptors: Privacy, Learning Analytics, Student Attitudes, College Students
Barry J. Bailey – ProQuest LLC, 2021
Learning analytics systems are software designed to aggregate student data to be analyzed for the purpose of delivering information to students, with the goal of increasing student success, academic goal completion, and retention. Despite being identified as stakeholders and beneficiaries of learning analytics, student perceptions make up a small…
Descriptors: Community College Students, Student Attitudes, Learning Analytics, Ethics
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Al-Shaikhli, Dhuha – Education and Information Technologies, 2023
This research examines the effect of having a tracking technology in a learning management system (LMS) that reports the effect of perceiving other students' interactions on a learner's intention to keep using LMS in the future. The main underlying theory is herd behaviour theory which argues that crowd behaviour affects the perceptions of the…
Descriptors: Learning Management Systems, Educational Technology, Learning Analytics, Independent Study
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Amaya, Edna Johanna Chaparro; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2023
Aim/Purpose: This article proposes a framework based on a sequential explanatory mixed-methods design in the learning analytics domain to enhance the models used to support the success of the learning process and the learner. The framework consists of three main phases: (1) quantitative data analysis; (2) qualitative data analysis; and (3)…
Descriptors: Learning Analytics, Guidelines, Student Attitudes, Learning Processes
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Tzeng, Jian-Wei; Lee, Chia-An; Huang, Nen-Fu; Huang, Hao-Hsuan; Lai, Chin-Feng – International Review of Research in Open and Distributed Learning, 2022
Massive open online courses (MOOCs) are open access, Web-based courses that enroll thousands of students. MOOCs deliver content through recorded video lectures, online readings, assessments, and both student-student and student-instructor interactions. Course designers have attempted to evaluate the experiences of MOOC participants, though due to…
Descriptors: Online Courses, Models, Learning Analytics, Artificial Intelligence
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