Titlebook: Artificial Intelligence in Education; 16th International C H. Chad Lane,Kalina Yacef,Philip Pavlik Conference proceedings 2013 Springer-Ver

N斯巴達(dá)人

陰謀

情愛(ài)

A Learning Environment That Combines Problem-Posing and Problem-Solving Activities performed two practices for evaluation. The results showed that the participants successfully posed more advanced problems in the second round of problem posing as compared to the first. The empirical data gathered from the two practices indicated a significant relationship between problem-solving and problem-posing abilities.

MOAT

Overthrow

From a Customizable ITS to an Adaptive ITSic system enabling the definition of a personalization strategy and its application to an external ITS. In this article we present how this tool provides real assistance to an ITS designer wishing to make his/her system adaptive.

糾纏,纏繞

Individualized Bayesian Knowledge Tracing Models a larger scale. We show that student-specific parameters lead to a tangible improvement when predicting the data of unseen students, and that parameterizing students’ speed of learning is more beneficial than parameterizing a priori knowledge.

Eructation

ORE

Intellectual

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162444.jpg

對(duì)待

Artificial Intelligence in Education978-3-642-39112-5Series ISSN 0302-9743 Series E-ISSN 1611-3349