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Adil Boughida; Mohamed Nadjib Kouahla; Yacine Lafifi – Education and Information Technologies, 2024
In e-learning environments, most adaptive systems do not consider the learner's emotional state when recommending activities for learning difficulties, blockages, or demotivation. In this paper, we propose a new approach of emotion-based adaptation in e-learning environments. The system will allow recommendation resources/activities to motivate…
Descriptors: Psychological Patterns, Electronic Learning, Educational Environment, Models
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Carina Büscher – International Journal of Science and Mathematics Education, 2025
Computational thinking (CT) is becoming increasingly important as a learning content. Subject-integrated approaches aim to develop CT within other subjects like mathematics. The question is how exactly CT can be integrated and learned in mathematics classrooms. In a case study involving 12 sixth-grade learners, CT activities were explored that…
Descriptors: Mathematics Instruction, Thinking Skills, Teaching Methods, Computer Science Education
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Monika Mladenovic; Lucija Medak; Divna Krpan – ACM Transactions on Computing Education, 2025
Computer Science (CS) Unplugged activities are designed to engage students with CS concepts. It is an active learning approach combining physical interaction with visual representation. This research article investigates the impact of CS Unplugged on students' understanding of the bubble sort algorithm. Algorithm visualization, traditionally…
Descriptors: Computer Science Education, Learning Activities, Active Learning, Algorithms
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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
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Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
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Sohail Ahmed Soomro; Halar Haleem; Bertrand Schneider; Georgi V. Georgiev – IEEE Transactions on Learning Technologies, 2025
This study presents a monocular approach for capturing students' prototyping activities and interactions in digital-fabrication-based makerspaces. The proposed method uses images from a single camera and applies object reidentification, tracking, and depth estimation algorithms to track and uniquely label participants in the space, extracting both…
Descriptors: Learning Activities, Shared Resources and Services, Manufacturing, Photography
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M. P. R. I. R. Silva; R. A. H. M. Rupasingha; B. T. G. S. Kumara – Technology, Pedagogy and Education, 2024
Today, in every academic institution as well as the university system assessing students' performance, identifying the uniqueness of each student and finding solutions to performance problems have become challenging issues. The main purpose of the study is to predict how student performance changes as a result of their behaviours, hobbies,…
Descriptors: Artificial Intelligence, Student Evaluation, Prediction, Recreational Activities
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Yangyang Luo; Xibin Han; Chaoyang Zhang – Asia Pacific Education Review, 2024
Learning outcomes can be predicted with machine learning algorithms that assess students' online behavior data. However, there have been few generalized predictive models for a large number of blended courses in different disciplines and in different cohorts. In this study, we examined learning outcomes in terms of learning data in all of the…
Descriptors: Prediction, Learning Management Systems, Blended Learning, Classification
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Mohammed Jebbari; Bouchaib Cherradi; Soufiane Hamida; Abdelhadi Raihani – Education and Information Technologies, 2024
With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…
Descriptors: MOOCs, Algorithms, Computer Simulation, COVID-19
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Jeff Ford; Rachel Erickson; Ha Le; Kaylee Vick; Jillian Downey – PRIMUS, 2024
In this study, we analyzed student participation and success in a college-level Calculus I course that utilized standards-based grading. By measuring the level to which students participate in this class structure, we were able to use a clustering algorithm that revealed multiple groupings of students that were distinct based on activity…
Descriptors: Calculus, Mathematics Instruction, Mathematics Achievement, Grades (Scholastic)
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Jeffery Buckley – Journal of Technology Education, 2024
The use of adaptive comparative judgement (ACJ) for assessment in technology education has been topical since its introduction to the field through the e-scape project coordinated by the Technology Education Research Unit in the United Kingdom. In the last decade, however, there has been an increasing volume of research examining how ACJ can and…
Descriptors: Foreign Countries, Technology Uses in Education, Open Source Technology, Computer Oriented Programs
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Changhao Liang; Rwitajit Majumdar; Yuta Nakamizo; Brendan Flanagan; Hiroaki Ogata – Interactive Learning Environments, 2024
In-class group work activities are found to promote the interpersonal skills of learners. To support the teachers in facilitating such activities, we designed a learning analytics-enhanced technology framework, Group Learning Orchestration Based on Evidence (GLOBE) using data-driven approaches. In this study, we implemented the algorithmic group…
Descriptors: Algorithms, Group Dynamics, Group Activities, Learning Analytics