| Download | - View final version: AI-based adaptive instructional systems for maritime safety training: a systematic literature review (PDF, 1.2 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1007/s44163-024-00153-0 |
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| Author | Search for: Karimi, Elham; Search for: Smith, Jennifer1ORCID identifier: https://orcid.org/0000-0001-8423-0572; Search for: Billard, RandyORCID identifier: https://orcid.org/0000-0002-1029-3615; Search for: Veitch, BrianORCID identifier: https://orcid.org/0000-0001-5450-4587 |
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| Affiliation | - National Research Council of Canada. Ocean, Coastal and River Engineering
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| Format | Text, Article |
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| Subject | adaptive instructional systems; intelligence tutoring systems; decision tree; Bayesian networks; maritime education and training; AI techniques |
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| Abstract | Adaptive instructional systems (AISs) refer to educational interventions designed to accommodate individual learner differences. These systems employ various approaches, such as artificial intelligence (AI), machine learning (ML), and data analytics, to analyze student performance and personalize the learning experience. This article presents a review of the current state-of-the-art of AI methods used in the development of AISs for maritime safety training. The main objective of this systematic literature review is to determine the use of AI/ML techniques in AIS and how they can contribute to the development of AIS for maritime education and training (MET) applications in addressing small data problems. Answering the research questions of the review identifies the fundamental purposes of using AI/ML techniques in developing AIS for MET. Further, the review highlights several crucial research areas, including AI techniques for modelling student and instructor knowledge, as well as ML algorithms for predicting student performance in situations with limited datasets. |
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| Publication date | 2024-07-26 |
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| Publisher | Springer Science and Business Media LLC |
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| Licence | |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | d38071e6-1463-4e65-b474-f6831119844a |
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| Record created | 2024-08-19 |
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| Record modified | 2024-08-19 |
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