An Instructional Strategy Selection Model Based on Agent and Ontology for an Intelligent Tutoring System

Kim, Jae-Soo; Shinn, Yun Ho

doi:10.1109/waina.2010.147

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…In the fourth test FUNPRO was validated using an algorithm based on (Kim & Shinn, 2010). The algorithm is labeled as A2 for the representation of results.…”

Section: Processmentioning

confidence: 99%

A Formal Model for Metacognitive Reasoning in Intelligent Systems

Piñeres

Josyula

Jiménez

2014

International Journal of Cognitive Informatics and Natural Intelligence

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This paper presents a formal model of metacognitive reasoning in intelligent systems (IS). The proposed model was named fM 2 and uses predicate logic to represent a cycle of reasoning about failures generated in reasoning tasks in an IS. fM 2 has mechanisms such as introspective monitoring and meta-level control to perform metacognitive reasoning. fM 2 was implemented and validated on an intelligent tutoring system named FUNPRO. The performance metrics of FUNPRO indicate the capacity of fM 2 to drastically decrease the reasoning failures produced in the recommendations of FUNPRO. Thus, this paper demonstrates the efficacy of fM 2 as a valid tool to improve the performance of the reasoning processes of IS.

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“…In the fourth test FUNPRO was validated using an algorithm based on (Kim & Shinn, 2010). The algorithm is labeled as A2 for the representation of results.…”

Section: Processmentioning

confidence: 99%

A Formal Model for Metacognitive Reasoning in Intelligent Systems

Piñeres

Josyula

Jiménez

2014

International Journal of Cognitive Informatics and Natural Intelligence

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“…The application of ITS spans a wide spectrum of domains, including algebra and geometry education [1], medical education [2], music education [3], and nursing education. The key feature [4] of ITS is the ability to provide a student self-adapted presentation of the teaching material by using AI methods to represent the pedagogical decisions and the information about each student.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Verb Phase Based on Concept Model for Nature Language Understanding

Zhao

et al. 2011

AMM

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The traditional intelligent tutoring system as a web-based education tools used for adaptive learning can’t solve the encountered question in time while the student is learning with the absence of nature language understanding system. In this paper, a web-based intelligent tutoring system is firstly introduced to solve the encountered question in real time. Secondly, a concept model representing the concept connotation, the extension and the relation between them is presented to support the nature language understanding system in order to extract the question’s meaning. Furthermore, a knowledge representation of verb and noun in impersonal mature domain is involved. Thirdly, the semantic processing arithmetic of the verb phase is given. Finally, the result of experiment and application of arithmetic are shown.

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