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Journal ArticleDOI

The Artificial Intelligence Applications to Learning Programme

Noel Williams
- 15 Jan 1992 - 
- Vol. 18, Iss: 1, pp 101-107
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TLDR
The Artificial Intelligence Applications to Learning Programme has been funded since 1987 by what is now known as the Training, Enterprise and Education Directorate (TEED), and one profitable line of development was to use AI to enrich training systems.
Abstract
The Artificial Intelligence Applications to Learning Programme has been funded since 1987 by what is now known as the Training, Enterprise and Education Directorate (TEED). The Programme aimed to explore and accelerate the use of AI technologies in learning, in both the educational and industrial sectors. The ten demonstrator projects were evaluated for their impact on industry and on further and higher education, while the project was in progress and later during its dissemination phase. The most useful outcomes of evaluation emerged during the latter phase, when the innovations had had an opportunity to become established and brought to market. There were issues related to technology-drive and the need to find problems for which the solution existed through group collaboration. One profitable line of development was to use AI to enrich training systems. An ideal training system must feel “good” to the client, should go beyond existing adaptive training systems, offer a high rate of training, be cost effective, have visual appeal, give sophisticated feedback, should fit closely with the user's current practice, and should have a shele life of more than 3 years.

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Computers and Writing

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Understanding the past—illuminating the future

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AI in training (1980–2000): Foundation for the future or misplaced optimism?

TL;DR: This paper reviews the early initiatives and suggests reasons why the potential for the use of AI in education and training has never been truly fulfilled.

Predicting Learning Outputs and Retention through Neural Network Artificial Intelligence in Photosynthesis, Transpiration and Translocation.

TL;DR: The study aimed to assess the effects of neural network artificial intelligence approach on the achievement and retention in science learning and found that input layer and first hidden layer were related with the output of the artificial intelligence.
References
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Journal ArticleDOI

Evaluation of the Further and Higher Education (FHE) Section of the Training Agency's ‘AI Applications to Learning’ Programme

TL;DR: The external evaluation is divided into two sections, one for the evaluation of the impact on the FHE sector and the second to assess the industrial impact of the AI application to learning as discussed by the authors.
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