A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System

被引：3

作者：

Pian, Yang ^{[1
]}

Lu, Yu ^{[1
,2
]}

Huang, Yuqi ^{[1
]}

Bittencourt, Ig Ibert ^{[3
]}

机构：

[1] Beijing Normal Univ, Fac Educ, Adv Innovat Ctr Future Educ, Beijing, Peoples R China

[2] China Mobile Commun Corp, Joint Lab Mobile Learning, Minist Educ, Beijing, Peoples R China

[3] Univ Fed Alagoas, Maceio, Alagoas, Brazil

来源：

ARTIFICIAL INTELLIGENCE IN EDUCATION (AIED 2020), PT II | 2020年 / 12164卷

基金：

中国国家自然科学基金;

关键词：

Intelligent tutoring system; Cold start; Gamification;

D O I：

10.1007/978-3-030-52240-7_68

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Today's intelligent tutoring systems provide more intelligent but complex services to learners. These systems encounter two critical issues: 1) the initial lack of new learner's information for running complex services, and 2) new learners failing to actively interact with these complex services due to the initial unfamiliarity. We define such issues as the "cold-start" problem in today's intelligent tutoring systems, and propose a gamified solution to tackle it. By leveraging on the established MDA model, a three-layer framework with narrative elements and task-oriented elements is designed and implemented in an ITS for mathematics. The preliminary evaluations show its effectiveness, and the proposed solution is generally applicable to other ITS systems.

引用

页码：376 / 381

页数：6

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