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Showing 1 to 15 of 47 results Save | Export
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Krieter, Philipp – IEEE Transactions on Learning Technologies, 2022
The time students spend in a learning management system (LMS) is an important measurement in learning analytics (LA). One of the most common data sources is log files from LMS, which do not directly reveal the online time, the duration of which needs to be estimated. As this measurement has a great impact on the results of statistical models in…
Descriptors: Integrated Learning Systems, Learning Analytics, Electronic Learning, Students
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Pérez Sánchez, Carlos Javier; Calle-Alonso, Fernando; Vega-Rodríguez, Miguel A. – Education and Information Technologies, 2022
In this work, 29 features were defined and implemented to be automatically extracted and analysed in the context of NeuroK, a learning platform within the neurodidactics paradigm. Neurodidactics is an educational paradigm that addresses optimization of the learning and teaching process from the perspective of how the brain functions. In this…
Descriptors: Learning Analytics, Grade Prediction, Academic Achievement, Cooperative Learning
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da Silva, Lidia M.; Dias, Lucas P. S.; Barbosa, Jorge L. V.; Rigo, Sandro J.; dos Anjos, Julio C. S.; Geyer, Claudio F. R.; Leithardt, Valderi R. Q. – Informatics in Education, 2022
Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist…
Descriptors: Learning Analytics, Cooperative Learning, Distance Education, Electronic Learning
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Keskin, Sinan; Yurdugül, Halil – Journal of Educational Technology and Online Learning, 2022
This study aims to examine e-learning experiences of the learners by using learner system interaction metrics. In this context, an e-learning environment has been structured within the scope of a course. Learners interacted with learning activities and leave various traces when they interact with others, contents, and assessment tasks. Log data…
Descriptors: Electronic Learning, Learning Experience, Models, Learning Activities
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Hellings, Jan; Haelermans, Carla – Higher Education: The International Journal of Higher Education Research, 2022
We use a randomised experiment to study the effect of offering half of 556 freshman students a learning analytics dashboard and a weekly email with a link to their dashboard, on student behaviour in the online environment and final exam performance. The dashboard shows their online progress in the learning management systems, their predicted…
Descriptors: Learning Analytics, College Freshmen, Student Behavior, Electronic Learning
González, Carlos; López, Dany; Calle-Arango, Lina; Montenegro, Helena; Clasing, Paula – ECNU Review of Education, 2022
Purpose: This study aims to explore Chilean students' digital technology usage patterns and approaches to learning. Design/Approach/Methods: We conducted this study in two stages. We worked with one semester learning management systems (LMS), library, and students' records data in the first one. We performed a k-means cluster analysis to identify…
Descriptors: Foreign Countries, Electronic Learning, Technology Uses in Education, Use Studies
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Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
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Edson, Alden J.; Phillips, Elizabeth Difanis – ZDM: Mathematics Education, 2021
Teacher dashboards in mathematics classrooms tend to provide teachers with information on student performance that are often linked to classroom management systems, online course systems, or peer-tutoring software. Teacher dashboards also tend to emphasize features that support teachers using a "transition" or "direct…
Descriptors: Cooperative Learning, Electronic Learning, Problem Based Learning, Curriculum Implementation
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Safsouf, Yassine; Mansouri, Khalifa; Poirier, Franck – Journal of Information Technology Education: Research, 2021
Aim/Purpose: Since the beginning of the COVID-19 pandemic, many countries have adopted online education as an alternative to face-to-face courses. This has increased awareness of the importance of analyzing learning data left by students to improve and evaluate the learning process. This article presents a new tool, named TaBAT, created to work…
Descriptors: Learning Analytics, Integrated Learning Systems, Visual Aids, Electronic Learning
Araka, Eric; Maina, Elizaphan; Gitonga, Rhoda; Oboko, Robert – Research and Practice in Technology Enhanced Learning, 2020
For the last one decade, research in self-regulated learning (SRL) and educational psychology has proliferated. Researchers and educators have focused on how to support leaners grow their SRL skills on both face-to-face and e-learning environments. In addition, recent studies and meta-analysis have greatly contributed to the domain knowledge on…
Descriptors: Educational Trends, Educational Research, Independent Study, Electronic Learning
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Ayyanathan, N. – Shanlax International Journal of Education, 2022
Effective engagement and monitoring of students' online self-learning capacity and application of their acquired knowledge in the final year project is a challenging task for the educators worldwide. The author builds an evaluation framework to assess the stage-wise performance of students in this undertaken project. The primary objective of this…
Descriptors: Learning Analytics, Taxonomy, Student Projects, Active Learning
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Kokoç, Mehmet; Akçapinar, Gökhan; Hasnine, Mohammad Nehal – Educational Technology & Society, 2021
This study analyzed students' online assignment submission behaviors from the perspectives of temporal learning analytics. This study aimed to model the time-dependent changes in the assignment submission behavior of university students by employing various machine learning methods. Precisely, clustering, Markov Chains, and association rule mining…
Descriptors: Electronic Learning, Assignments, Behavior Patterns, Learning Analytics
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Zhang, Ling; Jackson, Haidee A.; Hunt, Tiffany L.; Carter, Richard Allen; Yang, Sohyun; Emerling, Christopher R. – TEACHING Exceptional Children, 2022
Mathematical problem solving is a complex cognitive activity, which poses difficulties for students with and without disabilities in inclusive learning environments. With a variety of functions, Learning Management Systems (LMSs) have the potential to enhance personalized learning to meet the diverse needs of all students. This paper provides…
Descriptors: Integrated Learning Systems, Mathematics Skills, Problem Solving, Evidence Based Practice
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Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Innovations in Education and Teaching International, 2021
In this research, the effect of the use of learning analytics (LA) based feedback as a metacognitive tool on the learners' transactional distance and motivation was examined. The research was carried out according to experimental design and was carried out on 81 university students. The students were randomly assigned to the experimental and…
Descriptors: Learning Analytics, Metacognition, Student Motivation, College Freshmen
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Charitopoulos, Angelos; Rangoussi, Maria; Koulouriotis, Dimitrios – International Journal of Artificial Intelligence in Education, 2020
The aim of this paper is to survey recent research publications that use Soft Computing methods to answer education-related problems based on the analysis of educational data 'mined' mainly from interactive/e-learning systems. Such systems are known to generate and store large volumes of data that can be exploited to assess the learner, the system…
Descriptors: Data Collection, Learning Analytics, Educational Research, Artificial Intelligence
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