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Xavier Ochoa; Xiaomeng Huang; Adam Charlton – Journal of Learning Analytics, 2024
Even before the inception of the term "learning analytics," researchers globally had been investigating the use of various feedback systems to support the self-regulation of participation and promote equitable contributions during collaborative learning activities. While some studies indicate positive effects for distinct subgroups of…
Descriptors: Learning Analytics, Feedback (Response), Independent Study, Cooperative Learning
Lars de Vreugd; Anouschka van Leeuwen; Marieke van der Schaaf – Journal of Computer Assisted Learning, 2025
Background: University students need to self-regulate but are sometimes incapable of doing so. Learning Analytics Dashboards (LADs) can support students' appraisal of study behaviour, from which goals can be set and performed. However, it is unclear how goal-setting and self-motivation within self-regulated learning elicits behaviour when using an…
Descriptors: Learning Analytics, Educational Technology, Goal Orientation, Learning Motivation
Nuo Cheng; Wei Zhao; Xiaoqing Xu; Hongxia Liu; Jinhong Tao – Education and Information Technologies, 2024
Learning analytics dashboards are becoming increasingly common tools for providing feedback to learners. However, there is limited empirical evidence regarding the effects of learning analytics dashboard design features on learners' cognitive load, particularly in digital learning environments. To address this gap, we developed goal-based,…
Descriptors: Learning Analytics, Learning Management Systems, Cognitive Ability, Online Courses
Lucía Márquez; Valeria Henríquez; Henrique Chevreux; Eliana Scheihing; Julio Guerra – British Journal of Educational Technology, 2024
Learning analytics (LA) is an emerging area that has had extensive development in higher education in recent years, focused both on the learning process of students within subjects and on monitoring their trajectories in training programmes. However, most of the developments remain in the pilot phase without reaching institutional adoption. This…
Descriptors: Higher Education, Learning Analytics, Ethics, Leadership
MOOC Performance Prediction and Analysis via Bayesian Network and Maslow's Hierarchical Needs Theory
Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
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
Eva Expósito-Casas; Ana González-Benito; Esther López-Martín – International Journal for Educational and Vocational Guidance, 2024
The purpose of this work is to identify contextual variables that help to explain the occupational aspirations of Spanish 15-year-old students. This is done by performing a secondary analysis of the PISA2018 test. Data have been analysed using decision trees introducing the students' expected occupational status as a dependent variable (DV), and…
Descriptors: Occupational Aspiration, Secondary School Students, Foreign Countries, Self Concept
Natalie Brezack; Wynnie Chan; Mingyu Feng – Grantee Submission, 2024
This paper explores how learning analytics data provided by a math problem-solving educational technology platform informed 5th and 6th grade teachers' instructional decisions around socioemotional learning (SEL). MathSpring is an educational technology tool that provides teachers with data on students' effort, progress, and emotions while…
Descriptors: Social Emotional Learning, Mathematics Instruction, Teacher Attitudes, Comparative Analysis