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Conference Paper: Methods for training an AI for Higher Education
Title | Methods for training an AI for Higher Education |
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Authors | |
Issue Date | 2019 |
Publisher | Faculty of Education, the University of Hong Kong. |
Citation | Centre for Information Technology in Education (CITE) Research Symposium 2019: Learning Design and Learning Environment: Innovation and Interactions, Hong Kong, 31 May- 1 June 2019 How to Cite? |
Abstract | Artificial intelligence (AI) has many potential applications to the field of education but from the perspective of the educator, the workings of AI can appear to be an intellectual black box. This presents a significant problem in the creation of feasible AI projects in education. Educators may not directly be involved in the training of an AI, but it may be helpful for them to understand the different options available in order to evaluate what kinds of data they might need for its training. This presentation describes a review of methods used together with a sharing of our experience in training an AI for health sciences education. |
Description | Poster Session: Learning Design and Learning Analytics - paper ID 13 |
Persistent Identifier | http://hdl.handle.net/10722/271386 |
DC Field | Value | Language |
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dc.contributor.author | See, CYH | - |
dc.contributor.author | Lam, CSN | - |
dc.contributor.author | Li, YS | - |
dc.contributor.author | Chan, LK | - |
dc.date.accessioned | 2019-06-24T01:08:52Z | - |
dc.date.available | 2019-06-24T01:08:52Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Centre for Information Technology in Education (CITE) Research Symposium 2019: Learning Design and Learning Environment: Innovation and Interactions, Hong Kong, 31 May- 1 June 2019 | - |
dc.identifier.uri | http://hdl.handle.net/10722/271386 | - |
dc.description | Poster Session: Learning Design and Learning Analytics - paper ID 13 | - |
dc.description.abstract | Artificial intelligence (AI) has many potential applications to the field of education but from the perspective of the educator, the workings of AI can appear to be an intellectual black box. This presents a significant problem in the creation of feasible AI projects in education. Educators may not directly be involved in the training of an AI, but it may be helpful for them to understand the different options available in order to evaluate what kinds of data they might need for its training. This presentation describes a review of methods used together with a sharing of our experience in training an AI for health sciences education. | - |
dc.language | eng | - |
dc.publisher | Faculty of Education, the University of Hong Kong. | - |
dc.relation.ispartof | CITE Research Symposium, CITERS 2019, Faculty of Education, the University of Hong Kong | - |
dc.title | Methods for training an AI for Higher Education | - |
dc.type | Conference_Paper | - |
dc.identifier.email | See, CYH: drsee2@hku.hk | - |
dc.identifier.email | Chan, LK: lapki@hku.hk | - |
dc.identifier.authority | Chan, LK=rp00536 | - |
dc.identifier.hkuros | 298047 | - |
dc.publisher.place | Hong Kong | - |