Macro-adaptation in Conversational Intelligent Tutoring Matters

被引：0
|
作者：
Rus, Vasile [1 ]
Stefanescu, Dan [1 ]
Baggett, William [1 ]
Niraula, Nobal [1 ]
Franceschetti, Don [1 ]
Graesser, Arthur C. [1 ]
机构：
[1] Univ Memphis, Memphis, TN 38152 USA
来源：
INTELLIGENT TUTORING SYSTEMS, ITS 2014 | 2014年 / 8474卷
关键词：
macro-adaptation; intelligent tutoring systems; assessment; SYSTEMS; FORCE;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We present in this paper the findings of a study on the role of macro-adaptation in conversational intelligent tutoring. Macro-adaptivity refers to a system's capability to select appropriate instructional tasks for the learner to work on. Micro-adaptivity refers to a system's capability to adapt its scaffolding while the learner is working on a particular task. We compared an intelligent tutoring system that offers both macro-and micro-adaptivity (fully-adaptive) with an intelligent tutoring system that offers only micro-adaptivity. Experimental data analysis revealed that learning gains were significantly higher for students randomly assigned to the fully-adaptive intelligent tutor condition compared to the micro-adaptive-only condition.
引用
收藏
页码：242 / 247
页数：6
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