Empowering AI with experiential learning
Implications from analysing user-generated content
Bibliographic Data
| ID | 21403669 |
|---|---|
| Authors | Ashutosh Singh (0000-0002-6691-9568, University of Leeds), Reeti Agarwal (0000-0003-3627-2182, Jaipuria Institute of Management, corresponding author), Rsha Alghafes (0000-0001-9517-7463, Princess Nourah bint Abdulrahman University), Armando Papa (0000-0001-7084-6763, National Research University Higher School of Economics) |
| Year | 2025 |
| Volume | 219 |
| Pages | 124261 |
| Publication date | 2025-10-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Technological Forecasting and Social Change (JOURNAL) |
| Journal identifiers | ISSN: 0040-1625 • E-ISSN: 1873-5509 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.techfore.2025.124261 |
| OpenAlex | W4412022708 |
| Language | EN |
| Citations received | 1 |
| References cited | 36 |
Content (measure theory) · Experiential learning · Human–computer interaction · Knowledge management · Mathematics education · Multimedia · User-generated content · World Wide Web · AI in Service Interactions · Computer Science · Educational Games and Gamification · Mathematics · Online Learning and Analytics · Psychology
Experiential learning – a systematic review and revision of Kolb’s model
Technology identification from patent texts
An intelligent patent recommender adopting machine learning approach for natural language processing
Will artificial intelligence drive the advancements in higher education? A tri-phased exploration
Converting consumer-generated content into an innovation resource
Developing a supervised learning model for anticipating potential technology convergence between technology topics
Forecasting AI progress
Innovation Analytics and Digital Innovation Experimentation
A review of data analytics in technological forecasting
Understanding the long-term emergence of autonomous vehicles technologies
A topic models based framework for detecting and forecasting emerging technologies
Early detection of valuable patents using a deep learning model
Machine-learning-based deep semantic analysis approach for forecasting new technology convergence
A text-embedding-based approach to measuring patent-to-patent technological similarity
Getting more resources for better performance
The impact of forum content on data science open innovation performance
Technological forecasting based on estimation of word embedding matrix using LSTM networks
Profiling academic-industrial collaborations in bibliometric-enhanced topic networks
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |