Adaptive learning 2007 thesis
From: M'endozaa J.
Category: essay joseph
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Even before the pandemic-related closures, schools around the world had been experimenting with personalized and adaptive learning. And since the pandemic, the demand for online learning platforms has only intensified. Launching a personalized learning initiative is a big undertaking. And while the benefits are significant, the risks of a failed initiative are enormous. Personalized learning requires an investment of both time and money. And teachers who have been burned once by technology will be doubly resistant to future initiatives.
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About Smart Sparrow
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The controller collects data from each lap to learn a control invariant terminal set and a value function approximation. The goal of this project is to use the LMPC framework to build an adaptive controller which learns the vehicle model parameters. This would allow to reduce model mismatch between the true car dynamics and the controller model and consequqntly to increase the performance of the closed loop system increases. The video shows the results of two experiments. In the first experiment the controller uses a simple kinematic bicycle model to predict the motion of the car. After an initial path following lap the LMPC controller starts the learning successfully reducing the lap time at each iteration. During the second experiment the proposed adaptive controller model was used.
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One-on-one instruction is highly effective in corporate training, as the instructor can individualize material. Current e-learning tools often cannot provide this type of individualization. With adaptive learning, technology uses inference algorithms to adapt content to the learning needs of students based on their responses to tasks and questions. In this way, adaptive learning emulates one-on-one instruction.