Deep learning, education and the final stage of automation
Bibliographic Data
| ID | 8856572 |
|---|---|
| Authors | Michael A Peters (0000-0002-1482-2975, University of Waikato, corresponding author) |
| Year | 2017 |
| Volume | 50 |
| Issue | 6-7 |
| Pages | 549-553 |
| Publication date | 2017-07-25 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Educational Philosophy and Theory (JOURNAL) |
| Journal identifiers | ISSN: 0013-1857 • E-ISSN: 1469-5812 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/00131857.2017.1348928 |
| OpenAlex | W2736800185 |
| Language | EN |
| Citations received | 11 |
| References cited | 4 |
Credit Neuroscape Labevery aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.– J. McCarthy, M. L. Minsky
Automation · Higher education · Mathematics education · Pedagogy · Philosophy of education · Political science · Sociology · Stage (stratigraphy · Engineering · Labor market dynamics and wage inequality · Law · Psychology
Application and theory gaps during the rise of Artificial Intelligence in Education
Challenges and Future Directions of Big Data and Artificial Intelligence in Education
Machine behaviourism
In the trading zone
AI, Concepts of Intelligence, and Chatbots
The why, what and how of deep learning
Conceptual challenges for interpretable machine learning
Intelligent capitalism’ and the disappearance of labour
Trade wars, technology transfer, and the future Chinese techno-state
Fostering Graduate Employability
Out of the box
| Unique citing works | 11 |
|---|---|
| Citations per year | 1.38 |
| Citation span | 2018 - 2023 (6) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 11 |