Collaborative Dialog While Studying Worked-out Examples

被引:3
|
作者
Hausmann, Robert G. M. [1 ]
Nokes, Timothy J. [1 ]
Vanlehn, Kurt [2 ]
Van De Sande, Brett [2 ]
机构
[1] Univ Pittsburgh, Ctr Learning Res & Dev, Pittsburgh Sci Learning Ctr, Pittsburgh, PA 15260 USA
[2] Arizona State Univ, Sch Comp & Informat, Ira A Fulton Sch Engn, Tempe, AZ 85287 USA
关键词
Self-explanation; peer collaboration; prior knowledge; physics; SELF-EXPLANATIONS;
D O I
10.3233/978-1-60750-028-5-596
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Self-explaining is a beneficial learning strategy for studying worked-out examples because it either supplies missing information through the generation of inferences or because it provides a mechanism for repairing flawed mental models. Although self-explanation is generated with the purpose of helping the individual, is it also helpful to produce explanations in a collaborative setting? Can individuals help each other infer missing information or repair their flawed mental models collaboratively? To find out, we coded the dialog front dyads collaboratively studying examples and contrasted it with individuals studying examples alone. The results Suggest that dyads were more likely to attempt to reconcile the examples with their attempted solutions, and avoid shallow processing of examples through paraphrasing,
引用
收藏
页码:596 / +
页数:2
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