ReviewNPJ science of learning2017
Towards AI-powered personalization in MOOC learning.
Review in NPJ science of learning, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Where do we go from here? Evaluating the effectiveness of a nursing MOOC over six years.BMC medical education · 2026Article
- Does English proficiency matter? Testing its moderating role in the TAM for AI-enhanced MOOC adoption in vocational education.Frontiers in psychology · 2026Article
- Analyzing the network structure of students' motivation to learn AI: a self-determination theory perspective.NPJ science of learning · 2025Article
- Development of an AI predictive model to categorize and predict online learning behaviors of students in Thailand.Heliyon · 2024Review
- Improving undergraduate education of occupational health and occupational medicine appling massive open online courses & problem-based learning.BMC medical education · 2024Article
- Can AI teach me employability? A multi-national study in three countries.Frontiers in artificial intelligence · 2024Article
- Analysis of social metrics on scientific production in the field of emotion-aware education through artificial intelligence.Frontiers in artificial intelligence · 2024Article
- Generative AI in Higher Education: Balancing Innovation and Integrity.British journal of biomedical science · 2024Review
- Article
- PlantInfoCMS: Scalable Plant Disease Information Collection and Management System for Training AI Models.Sensors (Basel, Switzerland) · 2023Article
- The Impact of Artificial Intelligence on Radiology Education in the Wake of Coronavirus Disease 2019.Korean journal of radiology · 2023Article
- A federated graph neural network framework for privacy-preserving personalization.Nature communications · 2022Article
- Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021.AI and ethics · 2022Article
- Individualized learning potential in stressful times: How to leverage intensive longitudinal data to inform online learning.Computers in human behavior · 2021Article
- Graph Representation Forecasting of Patient's Medical Conditions: Toward a Digital Twin.Frontiers in genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Massive Open Online Courses (MOOCs) represent a form of large-scale learning that is changing the landscape of higher education. In this paper, we offer a perspective on how advances in artificial intelligence (AI) may enhance learning and research on MOOCs. We focus on emerging AI techniques including how knowledge representation tools can enable students to adjust the sequence of learning to fit their own needs; how optimization techniques can efficiently match community teaching assistants to MOOC mediation tasks to offer personal attention to learners; and how virtual learning companions with human traits such as curiosity and emotions can enhance learning experience on a large scale. These new capabilities will also bring opportunities for educational researchers to analyse students' learning skills and uncover points along learning paths where students with different backgrounds may require different help. Ethical considerations related to the application of AI in MOOC education research are also discussed.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.