Model-based simulation systems for adaptive training in time-critical decision making

Kushal Abhyankar, Raghavendra Polakonda, Subhashini Ganapathy, Kristen Barrerra
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引用次数: 1

Abstract

The fundamental goal of education and training is to provide capabilities that can help humans improve performance and accelerate decision-making. Advances in mobile computing (e.g., sensor technology, context aware computing, and cloud computing) allow for the design of systems that goes beyond the traditional methods of simulation training to support adaptive learning. The focus of this paper will be to present a human performance model, using mobile devices, for analysis of time-critical decision making through sensor-based information.
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基于模型的时间关键决策自适应训练仿真系统
教育和培训的根本目标是提供帮助人类提高绩效和加速决策的能力。移动计算的进步(例如,传感器技术、上下文感知计算和云计算)允许设计超越传统模拟训练方法的系统,以支持自适应学习。本文的重点将是提出一个人类绩效模型,使用移动设备,通过基于传感器的信息来分析时间关键型决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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