Publication Date
| In 2026 | 0 |
| Since 2025 | 2 |
| Since 2022 (last 5 years) | 7 |
| Since 2017 (last 10 years) | 8 |
| Since 2007 (last 20 years) | 8 |
Descriptor
| Intervention | 8 |
| Learning Analytics | 8 |
| Models | 8 |
| Prediction | 5 |
| Foreign Countries | 3 |
| Learning Processes | 3 |
| Teaching Methods | 3 |
| Academic Achievement | 2 |
| Algorithms | 2 |
| Artificial Intelligence | 2 |
| At Risk Students | 2 |
| More ▼ | |
Source
Author
| Alan Cadwallader | 1 |
| Alison Harrison | 1 |
| Ayub, Muhammad Adnan | 1 |
| Cano García, Elena | 1 |
| Chenglong Wang | 1 |
| Danielle S. McNamara | 1 |
| Davis, Jeffrey | 1 |
| Dragos-Georgian Corlatescu | 1 |
| Du, Xiaoming | 1 |
| Ge, Shilun | 1 |
| Ian Renner | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 8 |
| Reports - Research | 7 |
| Reports - Descriptive | 1 |
Education Level
| Higher Education | 5 |
| Postsecondary Education | 5 |
Audience
Location
| New Zealand | 1 |
| Pakistan | 1 |
| Spain (Barcelona) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Du, Xiaoming; Ge, Shilun; Wang, Nianxin – International Journal of Information and Communication Technology Education, 2022
In the context of education big data, it uses data mining and learning analysis technology to accurately predict and effectively intervene in learning. It is helpful to realize individualized teaching and individualized teaching. This research analyzes student life behavior data and learning behavior data. A model of student behavior…
Descriptors: Prediction, Data, Student Behavior, Academic Achievement
Construction and Analysis of a Decision Tree-Based Predictive Model for Learning Intervention Advice
Chenglong Wang – Turkish Online Journal of Educational Technology - TOJET, 2024
The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…
Descriptors: Decision Making, Prediction, Models, Intervention
Lynnette Brice; Alison Harrison; Alan Cadwallader – Journal of Open, Flexible and Distance Learning, 2023
The purpose of this paper is to share insights gained from the discovery, design, and delivery phases of creating a three-tiered model of non-academic learning support in open, distance, and flexible learning (ODFL): "Learner Engagement and Success Services (LESS)", at Open Polytechnic | Te Pukenga, New Zealand. Presented as a case…
Descriptors: Ethics, Learning Analytics, Intervention, Foreign Countries
Lluch Molins, Laia; Cano García, Elena – Journal of New Approaches in Educational Research, 2023
One of the main generic competencies in Higher Education is "Learning to Learn". The key component of this competence is the capacity for self-regulated learning (SRL). For this competence to be developed, peer feedback seems useful because it fosters evaluative judgement. Following the principles of peer feedback processes, an online…
Descriptors: Learning Analytics, Learning Management Systems, Peer Evaluation, Higher Education
Shabbir, Shahzad; Ayub, Muhammad Adnan; Khan, Farman Ali; Davis, Jeffrey – Interactive Technology and Smart Education, 2021
Purpose: Short-term motivation encompasses specific, challenging and attainable goals that develop in the limited timespan. On the other hand, long-term motivation indicates a sort of continuing commitment that is required to complete assigned task. As short-term motivational problems span for a limited period of time, such as a session,…
Descriptors: Learning Motivation, Electronic Learning, Time Factors (Learning), Learning Processes

Peer reviewed
Direct link
