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Lee, Hakeoung Hannah; Gargroetzi, Emma C. – Journal of Learning Analytics, 2023
Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection and uses of learner data. Considerations of potential harm and ethical implications have not kept pace, raising concerns about ethical and privacy issues (Holstein & Doroudi, 2019; Prinsloo & Slade,…
Descriptors: Learning Analytics, Mentors, Ethics, Responsibility
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Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
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Aleksandra Maslennikova; Daniela Rotelli; Anna Monreale – Journal of Learning Analytics, 2023
Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable…
Descriptors: Learning Analytics, Online Courses, Time Management, Self Management
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Montse Guitert Catasús; Teresa Romeu Fontanillas; Juliana E. Raffaghelli; Juan Pedro Cerro Martínez – Journal of Learning Analytics, 2025
This article systematically reviews the role of learning analytics (LA) in collaborative learning, particularly exploring how it can empower both teachers and students. Based on the analysis of 87 articles, selected by adopting the PRISMA workflow, the study discusses the intersection of LA with collaborative learning (CL), emphasizing the…
Descriptors: Learning Analytics, Teacher Empowerment, Student Empowerment, Cooperative Learning
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Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
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Stanislav Pozdniakov; Roberto Martinez-Maldonado; Yi-Shan Tsai; Vanessa Echeverria; Zachari Swiecki; Dragan Gaševic – Journal of Learning Analytics, 2025
Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…
Descriptors: Visual Aids, Learning Analytics, Technological Literacy, Pedagogical Content Knowledge
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Rushkin, Ilia; Chuang, Isaac; Tingley, Dustin – Journal of Learning Analytics, 2019
Each time a learner in a self-paced online course seeks to answer an assessment question, it takes some time for the student to read the question and arrive at an answer to submit. If multiple attempts are allowed, and the first answer is incorrect, it takes some time to provide a second answer. Here we study the distribution of such…
Descriptors: Online Courses, Response Style (Tests), Models, Learner Engagement
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Nguyen, Quan; Rienties, Bart; Whitelock, Denise – Journal of Learning Analytics, 2020
The use of analytical methods from learning analytics (LA) research combined with visualizations of learning activities using learning design (LD) tools and frameworks has provided important insight into how instructors design for learning. Nonetheless, there are many subtle nuances in instructors' design decisions that might not easily be…
Descriptors: Instructional Design, Online Courses, Distance Education, Electronic Learning
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Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content
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Victor Manuel Corza-Vargas; Roberto Martinez-Maldonado; Boris Escalante-Ramirez; Jimena Olveres – Journal of Learning Analytics, 2024
While teachers often monitor and adjust their learning design based on students' emotional states in physical classrooms, synchronous online environments often limit their ability to perceive the emotional climate of the class. Drawing from the concept of social translucence, it is suggested that making students' emotional states…
Descriptors: Foreign Countries, Undergraduate Students, Privacy, Cultural Awareness
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Boroujeni, Mina Shirvani; Dillenbourg, Pierre – Journal of Learning Analytics, 2019
The large-scale and granular interaction data collected in online learning platforms such as massive open online courses (MOOCs) provide unique opportunities to better understand individuals' learning processes and could facilitate the design of personalized and more effective support mechanisms for learners. In this paper, we present two…
Descriptors: Online Courses, Large Group Instruction, Learning Processes, Study Habits
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Hadavand, Aboozar; Muschelli, John; Leek, Jeffrey – Journal of Learning Analytics, 2019
Due to the fundamental differences between traditional education and massive open online courses (MOOCs), and because of the ever-increasing popularity of the latter, more research is needed to understand current and future trends in MOOCs. Although research in the field has grown rapidly in recent years, one of the main challenges facing…
Descriptors: Learning Analytics, Student Behavior, Online Courses, Large Group Instruction
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Iraj, Hamideh; Fudge, Anthea; Khan, Huda; Faulkner, Margaret; Pardo, Abelardo; Kovanovic, Vitomir – Journal of Learning Analytics, 2021
One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…
Descriptors: Learner Engagement, Learning Analytics, Feedback (Response), Class Size
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Blumenstein, Marion – Journal of Learning Analytics, 2020
The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…
Descriptors: Learning Analytics, Instructional Design, Effect Size, Higher Education
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Matcha, Wannisa; Gasevic, Dragan; Uzir, Nora'ayu Ahmad; Jovanovic, Jelena; Pardo, Abelardo; Lim, Lisa; Maldonado-Mahauad, Jorge; Gentili, Sheridan; Perez-Sanagustin, Mar; Tsai, Yi-Shan – Journal of Learning Analytics, 2020
Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning…
Descriptors: Learning Analytics, Learning Strategies, Instructional Design, Delivery Systems