Publication Date
In 2025 | 1 |
Since 2024 | 4 |
Since 2021 (last 5 years) | 8 |
Since 2016 (last 10 years) | 8 |
Since 2006 (last 20 years) | 8 |
Descriptor
Algorithms | 8 |
Foreign Countries | 8 |
Student Behavior | 8 |
College Students | 5 |
Artificial Intelligence | 3 |
Learning Management Systems | 3 |
Learning Processes | 3 |
Prediction | 3 |
Teaching Methods | 3 |
Academic Achievement | 2 |
Data Analysis | 2 |
More ▼ |
Source
Author
Abdulkadir Palanci | 1 |
Adjei, Laurene | 1 |
Agbesi, Victor Kwaku | 1 |
Ankora, Carlos | 1 |
B. T. G. S. Kumara | 1 |
Bensah, Lily | 1 |
Bert Jonsson | 1 |
Bouchet, François | 1 |
Chaoyang Zhang | 1 |
Christopoulos, Athanasios | 1 |
Johan Lithner | 1 |
More ▼ |
Publication Type
Reports - Research | 8 |
Journal Articles | 7 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 7 |
Postsecondary Education | 7 |
Secondary Education | 1 |
Audience
Location
China | 3 |
Finland | 1 |
Ghana | 1 |
Spain | 1 |
Sri Lanka | 1 |
Sweden | 1 |
United Kingdom | 1 |
United States | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Mathias Norqvist; Bert Jonsson; Johan Lithner – Educational Studies in Mathematics, 2025
In mathematics classrooms, it is common practice to work through a series of comparable tasks provided in a textbook. A central question in mathematics education is if tasks should be accompanied with solution methods, or if students should construct the solutions themselves. To explore the impact of these two task designs on student behavior…
Descriptors: Attention, Algorithms, Creativity, Mathematics Education
Kuadey, Noble Arden; Mahama, Francois; Ankora, Carlos; Bensah, Lily; Maale, Gerald Tietaa; Agbesi, Victor Kwaku; Kuadey, Anthony Mawuena; Adjei, Laurene – Interactive Technology and Smart Education, 2023
Purpose: This study aims to investigate factors that could predict the continued usage of e-learning systems, such as the learning management systems (LMS) at a Technical University in Ghana using machine learning algorithms. Design/methodology/approach: The proposed model for this study adopted a unified theory of acceptance and use of technology…
Descriptors: Foreign Countries, College Students, Learning Management Systems, Student Behavior
Xia, Xiaona – Interactive Learning Environments, 2023
Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…
Descriptors: Interaction, Intervention, Student Behavior, Educational Environment
Verger, Mélina; Lallé, Sébastien; Bouchet, François; Luengo, Vanda – International Educational Data Mining Society, 2023
Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against some students and possible harmful long-term…
Descriptors: Prediction, Models, Student Behavior, Academic Achievement
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
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
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals