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Austin C. Megli; Dayra Fallad-Mendoza; Monica Etsitty-Dorame; Jasmine Desiderio; Yan Chen; Damian Sanchez; Nick Flor; Charlotte N. Gunawardena – American Journal of Distance Education, 2024
Analyzing how participants learn from each other during online forums on discussion boards or social media platforms is often challenging. One of the predominant methods of analyzing such learning is through qualitative content analysis or interaction analysis. The Interaction Analysis Model (IAM), developed by Gunawardena, Lowe and Anderson which…
Descriptors: Learning Processes, Distance Education, Computer Mediated Communication, Social Media
Tran, Tuan M.; Hasegawa, Shinobu – International Association for Development of the Information Society, 2022
A learner model reflects learning patterns and characteristics of a learner. A learner model with learning history and its effectiveness plays a significant role in supporting a learner's understanding of their strengths and weaknesses of their way of learning in order to make proper adjustments for improvement. Nowadays, learners have been…
Descriptors: Markov Processes, Learning Processes, Models, Scores
Herodotou, Christothea; Hlosta, Martin; Boroowa, Avinash; Rienties, Bart; Zdrahal, Zdenek; Mangafa, Chrysoula – British Journal of Educational Technology, 2019
This study presents an advanced predictive learning analytics system, OU Analyse (OUA), and evidence from its evaluation with online teachers at a distance learning university. OUA is a predictive system that uses machine learning methods for the early identification of students at risk of not submitting (or failing) their next assignment.…
Descriptors: Learning Analytics, Teacher Empowerment, Distance Education, College Faculty
Bezerra, Luis Naito Mendes; Silva, Márcia Terra – International Journal of Distance Education Technologies, 2020
In the current context of distance learning, learning management systems (LMSs) make it possible to store large volumes of data on web browsing and completed assignments. To understand student behavior patterns in this type of environment, educators and managers must rethink conventional approaches to the analysis of these data and use appropriate…
Descriptors: Learning Analytics, Data Collection, Class Size, Online Courses
Herodotou, Christothea; Rienties, Bart; Boroowa, Avinash; Zdrahal, Zdenek; Hlosta, Martin – Educational Technology Research and Development, 2019
By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction.…
Descriptors: Prediction, Learning Analytics, Teacher Role, Teacher Attitudes
Roux, Lisa; Dagorret, Pantxika; Etcheverry, Patrick; Nodenot, Thierry; Marquesuzaa, Christophe; Lopisteguy, Philippe – International Association for Development of the Information Society, 2021
Distance computer-assisted learning is increasingly common, owing largely to the expansion and development of e-technology. Nevertheless, the available tools of the learning platforms have demonstrated their limits during the pandemic context, since many students, who were used to "face-to-face" education, got discouraged and dropped out…
Descriptors: Distance Education, Computer Software, Teacher Student Relationship, Supervision
Herodotou, Christothea; Rienties, Bart; Verdin, Barry; Boroowa, Avinash – Journal of Learning Analytics, 2019
Predictive Learning Analytics (PLA) aim to improve learning by identifying students at risk of failing their studies. Yet, little is known about how best to integrate and scaffold PLA initiatives into higher education institutions. Towards this end, it becomes essential to capture and analyze the perceptions of relevant educational stakeholders…
Descriptors: Prediction, Data Analysis, Higher Education, Distance Education
Miguel Baptista Nunes Ed.; Pedro Isaias Ed. – International Association for Development of the Information Society, 2022
These proceedings contain the papers of the 16th International Conference on e-Learning (EL 2022), which was organised by the International Association for Development of the Information Society, 19-21 July, 2022. This conference is part of the 16th Multi Conference on Computer Science and Information Systems 2022, 19-22 July, which had a total of…
Descriptors: Electronic Learning, Online Courses, Educational Technology, COVID-19