Toward a real-time model-based training system
Toward a real-time model-based training system
复制标题
迈向基于模型的实时培训系统
DOI：
10.1016/j.intcom.2006.07.011
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
John R. Anderson
中科院分区：
文献类型：
--
作者：
W. Fu;Daniel Bothell;Scott Douglass;Craig Haimson;Myeong;John R. Anderson
本文描述了一种基于实时模型的训练系统的开发，该系统在学员学习执行防空作战协调员（AAWC）任务时，为他们提供自适应的“过肩”（OTS）指令。长期目标是开发一个系统，根据学习者的行为提供实时的教学材料，以便最终在训练的不同阶段加强、补充或覆盖任务的初始指导集。该培训系统基于ACT-R架构，该架构为监控学员学习过程的认知模型提供了理论背景。本实验旨在研究OTS教学对学习的影响。结果表明，虽然OTS指令有助于短期学习，但(a)它们占用了处理当前信息的时间，(b)它们的效果在训练的初始阶段倾向于迅速衰减，(c)它们对训练的影响在训练的后期阶段随着OTS指令的程序化而减弱。创建了一个从前期和OTS指令中学习的认知模型，该模型与从人类参与者那里收集的学习和性能数据非常吻合。我们的研究结果表明，为了充分捕捉人类与智能训练系统之间的共生表现，密切监测受训者的学习过程非常重要，这样才能在训练的不同阶段有效地提供教学干预。我们提出，这样一个灵活的系统可以基于自适应认知模型来开发，该模型可以提供对学习和表现的实时预测。
This article describes the development of a real-time model-based training system that provides adaptive “over-the-shoulder” (OTS) instructions to trainees as they learn to perform an Anti-Air Warfare Coordinator (AAWC) task. The long-term goal is to develop a system that will provide real-time instructional materials based on learners’ actions, so that eventually the initial set of instructions on a task can be strengthened, complemented, or overridden at different stages of training. The training system is based on the ACT-R architecture, which serves as the theoretical background for the cognitive model that monitors the learning process of the trainee. An experiment was designed to study the impact of OTS instructions on learning. Results showed that while OTS instructions facilitated short-term learning, (a) they took time away from the processing of current information, (b) their effects tended to decay rapidly in initial stages of training, and (c) their effects on training diminished when the OTS instructions were proceduralized in later stages of training. A cognitive model that learned from both the upfront and OTS instructions was created and provided good fits to the learning and performance data collected from human participants. Our results suggest that to fully capture the symbiotic performance between humans and intelligent training systems, it is important to closely monitor the learning process of the trainee so that instructional interventions can be delivered effectively at different stages of training. We proposed that such a flexible system can be developed based on an adaptive cognitive model that provides real-time predictions on learning and performance.
影响因子：
4.1
作者：
Engle, RW;Tuholski, SW;Conway, ARA
通讯作者：
Conway, ARA
影响因子：
5.4
作者：
KINTSCH, W
通讯作者：
KINTSCH, W