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用于高级心脏生命支持的智能学习环境。

An intelligent learning environment for advanced cardiac life support.

作者信息

Eliot C R, Williams K A, Woolf B P

机构信息

University of Massachusetts Amherst, USA. eliot/

出版信息

Proc AMIA Annu Fall Symp. 1996:7-11.

Abstract

Resuscitation from clinical cardiac arrest is complex and often takes several years to learn. This paper describes an intelligent simulation-based tutor for ACLS which increases students' opportunity to practice before, during and after the ACLS course, thus bridging the gap between studying theory and didactic textbook material and working with patients. Sophisticated reasoning about student performance, compared to an expert model, distinguishes this system from other computerized instruction systems. Intelligence in the tutor allows the system to make the simulation dynamically adaptive to focus on areas where the student's learning needs are greatest. A formative evaluation with two classes of fourth year medical students suggested that the tutor was helpful, realistic and effective. Positive reactions and strong student involvement with the simulation suggest that this simulation-based tutor may improve learning and retention while decreasing anxiety for most students.

摘要

临床心脏骤停复苏术很复杂,通常需要数年时间才能学会。本文介绍了一种基于智能模拟的高级心血管生命支持(ACLS)辅导工具,它增加了学生在ACLS课程之前、期间和之后的练习机会,从而弥合了学习理论和教科书材料与接触患者之间的差距。与专家模型相比,该系统对学生表现进行的复杂推理使其有别于其他计算机化教学系统。辅导工具中的智能特性使系统能够动态调整模拟,以聚焦于学生学习需求最大的领域。对两个班级的四年级医学生进行的形成性评估表明,该辅导工具是有用的、逼真的且有效的。积极的反馈以及学生对模拟的高度参与表明,这种基于模拟的辅导工具可能会提高学习效果和知识留存率,同时减轻大多数学生的焦虑。

相似文献

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Problem-based ACLS instruction: a model approach for undergraduate emergency medical education.
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