A reinforcement learning approach to adaptive remediation in online training
| Autor: | Randall D. Spain, Robert Pokorny, James C. Lester, Benjamin Goldberg, Andy Smith, Bradford W. Mott, Jonathan P. Rowe |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
05 social sciences 050301 education 02 engineering and technology Training (civil) Human–computer interaction 020204 information systems Modeling and Simulation Component (UML) 0202 electrical engineering electronic engineering information engineering Key (cryptography) Reinforcement learning 0503 education Engineering (miscellaneous) |
| Zdroj: | The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology. 19:173-193 |
| ISSN: | 1557-380X 1548-5129 |
| DOI: | 10.1177/15485129211028317 |
| Popis: | Advances in artificial intelligence (AI) and machine learning can be leveraged to tailor training based on the goals, learning needs, and preferences of learners. A key component of adaptive training systems is tutorial planning, which controls how scaffolding is structured and delivered to learners to create dynamically personalized learning experiences. The goal of this study was to induce data-driven policies for tutorial planning using reinforcement learning (RL) to provide adaptive scaffolding based on the Interactive, Constructive, Active, Passive framework for cognitive engagement. We describe a dataset that was collected to induce RL-based scaffolding policies, and we present the results of our policy analyses. Results showed that the best performing policies optimized learning gains by inducing an adaptive fading approach in which learners received less cognitively engaging forms of remediation as they advanced through the training course. This policy was consistent with preliminary analyses that showed constructive remediation became less effective as learners progressed through the training session. Results also showed that learners’ prior knowledge impacted the type of scaffold that was recommended, thus showing evidence of an aptitude–treatment interaction. We conclude with a discussion of how AI-based training can be leveraged to enhance training effectiveness as well as directions for future research. |
| Databáze: | OpenAIRE |
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