Moradiavargani, Leila (2025) Evaluation of the influence of an adaptive instructional system on participants’ performance in a ship’s bridge simulator. Masters thesis, Memorial University of Newfoundland.
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Abstract
Effective ice management training is necessary for safe and efficient operations in sea ice environments, especially for offshore energy industries that experience seasonal incursions of pack and multi-year ice. Traditional training methods in sea ice management are predominantly through classroom courses, simulator-based training, and experiential learning on-the-job. However, traditional forms of training are non-adaptive, have limited scalability, and lack consistency in skill acquisition. This study evaluates the effectiveness of an Adaptive Instructional System (AIS) as a potential solution for improving ice management performance in simulation-based training, addressing a gap by providing adaptive, tailored feedback for learners. The AIS in this study incorporates a learner model using Decision Trees and an instructor model that integrates feedback from experienced seafarers with the goal of enhancing skill acquisition in a simulated environment. The study compares the performance of participants trained with AIS to those trained without it. Participants completed three training scenarios and one test scenario in a simulator, with key performance metrics used to assess training effectiveness, such as the changes in ice concentration for a specified zone. Statistical analyses, including normality assessments and independent samples t-tests at a significance level of p < 0.05, were conducted to assess performance differences. The findings demonstrate AIS's transformative potential to enhance ice management performance.
| Item Type: | Thesis (Masters) |
|---|---|
| URI: | http://research.library.mun.ca/id/eprint/16914 |
| Item ID: | 16914 |
| Additional Information: | Includes bibliographical references (pages 109-114) -- Restricted until February 28, 2026 |
| Keywords: | AIS, tailored feedback, ice management performance, decision tree |
| Department(s): | Engineering and Applied Science, Faculty of |
| Date: | May 2025 |
| Date Type: | Submission |
| Library of Congress Subject Heading: | Ice navigation--Training administrators; Ship simulators; Computer-assisted instruction |
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