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Biedermann, Daniel; Ciordas-Hertel, George-Petru; Winter, Marc; Mordel, Julia; Drachsler, Hendrik – Journal of Learning Analytics, 2023
Learners use digital media during learning for a variety of reasons. Sometimes media use can be considered "on-task," e.g., to perform research or to collaborate with peers. In other cases, media use is "off-task," meaning that learners use content unrelated to their current learning task. Given the well-known problems with…
Descriptors: Learning Processes, Learning Analytics, Information Technology, Behavior Patterns
Xinyu Li; Yizhou Fan; Tongguang Li; Mladen Rakovic; Shaveen Singh; Joep van der Graaf; Lyn Lim; Johanna Moore; Inge Molenaar; Maria Bannert; Dragan Gaševic – Journal of Learning Analytics, 2025
The focus of education is increasingly on learners' ability to regulate their own learning within technology-enhanced learning environments. Prior research has shown that self-regulated learning (SRL) leads to better learning performance. However, many learners struggle to productively self-regulate their learning, as they typically need to…
Descriptors: Learning Analytics, Metacognition, Independent Study, Skill Development
Zilong Pan; Lauren Biegley; Allen Taylor; Hua Zheng – Journal of Learning Analytics, 2024
The learning management system (LMS) is widely used in educational settings to support teaching and learning practices. The usage log data, generated by both learners and instructors, enables the development and implementation of learning analytics (LA) interventions aimed at facilitating teaching and learning activities. To examine the current…
Descriptors: Learning Analytics, Learning Management Systems, Intervention, Teacher Improvement
Rotelli, Daniela; Monreale, Anna – Journal of Learning Analytics, 2023
The increased adoption of online learning environments has resulted in the availability of vast amounts of educational log data, which raises questions that could be answered by a thorough and accurate examination of students' online learning behaviours. Event logs describe something that occurred on a platform and provide multiple dimensions that…
Descriptors: Learning Analytics, Learning Management Systems, Time on Task, Student Behavior
Hongwen Guo; Matthew S. Johnson; Kadriye Ercikan; Luis Saldivia; Michelle Worthington – Journal of Learning Analytics, 2024
Large-scale assessments play a key role in education: educators and stakeholders need to know what students know and can do, so that they can be prepared for education policies and interventions in teaching and learning. However, a score from the assessment may not be enough--educators need to know why students got low scores, how students engaged…
Descriptors: Artificial Intelligence, Learning Analytics, Learning Management Systems, Measurement
Marcel R. Haas; Colin Caprani; Benji T. van Beurden – Journal of Learning Analytics, 2023
We present an innovative modelling technique that simultaneously constrains student performance, course difficulty, and the sensitivity with which a course can differentiate between students by means of grades. Grade lists are the only necessary ingredient. Networks of courses will be constructed where the edges are populations of students that…
Descriptors: Bayesian Statistics, Computer Software, Learning Analytics, Grades (Scholastic)
Riordan Alfredo; Vanessa Echeverria; Linxuan Zhao; LuEttaMae Lawrence; Jie Xiang Fan; Lixiang Yan; Xinyu Li; Zachari Swiecki; Dragan Gaševic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Despite growing interest in applying human-centred design methods to create learning analytics (LA) systems, most efforts have concentrated on initial design phases, with limited exploration of how LA tools and practices can coevolve during the actual learning and teaching activities. This paper examines how a human-centred LA dashboard can be…
Descriptors: Learning Analytics, Learning Management Systems, Artificial Intelligence, Computer Software
Hai Li; Wanli Xing; Chenglu Li; Wangda Zhu; Simon Woodhead – Journal of Learning Analytics, 2025
Knowledge tracing (KT) is a method to evaluate a student's knowledge state (KS) based on their historical problem-solving records by predicting the next answer's binary correctness. Although widely applied to closed-ended questions, it lacks a detailed option tracing (OT) method for assessing multiple-choice questions (MCQs). This paper introduces…
Descriptors: Mathematics Tests, Multiple Choice Tests, Computer Assisted Testing, Problem Solving
Owen Henkel; Hannah Horne-Robinson; Maria Dyshel; Greg Thompson; Ralph Abboud; Nabil Al Nahin Ch; Baptiste Moreau-Pernet; Kirk Vanacore – Journal of Learning Analytics, 2025
This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a mathematics learning platform used by middle and high school students in several African countries. Using this dataset, we conducted two experiments to evaluate the use of large language models (LLM) for grading particularly challenging…
Descriptors: Learning Analytics, Learning Management Systems, Mathematics Instruction, Middle School Students
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
Mohd Fazil; Angelica Rísquez; Claire Halpin – Journal of Learning Analytics, 2024
Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…
Descriptors: Learning Analytics, Learning Management Systems, Learning Processes, Decision Making
Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
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
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
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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