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Showing 1 to 15 of 24 results Save | Export
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Greenhalgh, Spencer P.; DiGiacomo, Daniela K.; Barriage, Sarah – Information and Learning Sciences, 2023
Purpose: The purpose of this paper is to examine how higher education students think about educational technologies they have previously used -- and the implications of this understanding for their awareness of datafication and privacy issues in a postsecondary context. Design/methodology/approach: The authors conducted two surveys about students'…
Descriptors: Ethics, Privacy, Learning Management Systems, Learning Analytics
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Matthieu Tenzing Cisel – International Review of Research in Open and Distributed Learning, 2023
Due notably to the emergence of massive open online courses (MOOCs), stakeholders in online education have amassed extensive databases on learners throughout the past decade. Administrators of online course platforms, for instance, possess a broad spectrum of information about their users. This information spans from users' areas of interest to…
Descriptors: MOOCs, Ethics, Risk, Databases
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Plintz, Nicolai; Ifenthaler, Dirk – International Association for Development of the Information Society, 2023
Emotions are vital to learning success, especially in online learning environments. They make the difference between learning success and failure. Unfortunately, learners' emotional state is still rarely considered in online learning and teaching, although it is an important driver of learning success. This paper reports a work-in-progress…
Descriptors: Online Courses, Academic Achievement, Emotional Experience, Measurement
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West, Paige; Paige, Frederick; Lee, Walter; Watts, Natasha; Scales, Glenda – Journal of Civil Engineering Education, 2022
The expansion of online learning in higher education has both contributed to researchers exploring innovative ways to develop learning environments and created challenges in identifying student interactions with course material. Learning analytics is an emerging field that can identify student interactions and help make data-informed course design…
Descriptors: Learning Analytics, Student Attitudes, Electronic Learning, Construction Management
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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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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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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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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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Flora Ji-Yoon Jin; Bhagya Maheshi; Roberto Martinez-Maldonado; Dragan Gasevic; Yi-Shan Tsai – Journal of Learning Analytics, 2024
Feedback is essential in learning. The emerging concept of feedback literacy underscores the skills students require for effective use of feedback. This highlights students' responsibilities in the feedback process. Yet, there is currently a lack of mechanisms to understand how students make sense of feedback and whether they act on it. This gap…
Descriptors: Scaffolding (Teaching Technique), Feedback (Response), Learning Analytics, Literacy
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Karmijn van de Oudeweetering; Jeremy Knox; Mathias Decuypere – Learning, Media and Technology, 2024
This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and 'messy', the paper problematizes the model of the feedback loop that assumes that analytics dashboards 'feed back' data to instructors and/or learners…
Descriptors: MOOCs, Learning Analytics, Instructional Design, Student Role
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Namrata Srivastava; Sadia Nawaz; Yi-Shan Tsai; Dragan Gaševic – Journal of Learning Analytics, 2024
In a higher education context, students are expected to take charge of their learning by deciding "what" to learn and "how" to learn. While the learning analytics (LA) community has seen increasing research on the "how" to learn part (i.e., researching methods for supporting students in their learning journey), the…
Descriptors: Learning Analytics, Decision Making, Elective Courses, Undergraduate Students
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Lars de Vreugd; Anouschka van Leeuwen; Renée Jansen; Marieke van der Schaaf – Journal of Learning Analytics, 2024
For university students, self-regulation of study behaviour is important. However, students are not always capable of effective self-regulation. Providing study behaviour information via a learning analytics dashboard (LAD) may support phases within self-regulated learning (SRL). However, it is unclear what information a LAD should provide, how to…
Descriptors: Learning Management Systems, Learning Analytics, Student Behavior, Behavior Patterns
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Arjan J. F. Kok; Lex Bijlsma; Cornelis Huizing; Ruurd Kuiper; Harrie Passier – Informatics in Education, 2024
This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…
Descriptors: Programming Languages, Computer Science Education, Open Source Technology, Teaching Methods
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Jin, Yuxi; Li, Ping; Wang, Wenxiao; Zhang, Suiyun; Lin, Di; Yin, Chengjiu – Interactive Learning Environments, 2023
We design a generative adversarial network (GAN)-based pencil drawing learning system for art education on large image datasets to help students study how to draw pencil drawings for images and scenes. The system generates a pencil drawing result for a natural image based on GAN. The GAN network is trained on pencil drawing big datasets containing…
Descriptors: Art Education, Learning Analytics, Learning Management Systems, Homework
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