I learn from you, you learn from me: How to make iList learn from students

被引：7

作者：

Fossati, Davide ^{[1
]}

Di Eugenio, Barbara ^{[1
]}

Ohlsson, Stellan ^{[2
]}

Brown, Christopher ^{[3
]}

Chen, Lin ^{[1
,3
]}

Cosejo, David ^{[2
]}

机构：

[1] Univ Illinois, Dept Comp Sci, Chicago, IL USA

[2] Univ Illinois, Dept Psychol, Chicago, IL 60680 USA

[3] US Naval Acad, Dept Comp Sci, Annapolis, MD 21402 USA

来源：

ARTIFICIAL INTELLIGENCE IN EDUCATION: BUILDING LEARNING SYSTEMS THAT CARE: FROM KNOWLEDGE REPRESENTATION TO AFFECTIVE MODELLING | 2009年 / 200卷

基金：

美国国家科学基金会;

关键词：

Knowledge Representation; Student Modeling; Feedback Generation;

D O I：

10.3233/978-1-60750-028-5-491

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We developed a new model for iList, our system that helps students learn linked list. The model is automatically extracted from past student data, and allows iList to track students' problem-solving behavior in order to provide targeted feedback. We evaluated the new model both intrinsically and extrinsically. We show that the model can match most student actions after a relatively small sequence of observations, and that iList can effectively use the new student tracker to provide feedback and help students learn.

引用

页码：491 / +

页数：2

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