Integrating Learning Styles and Affect with an Intelligent Tutoring System

Zataraín-Cabada, Ramón; Barrón-Estrada, María Lucia; Camacho, José; Reyes-García, Carlos A.

doi:10.1109/micai.2013.36

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…It is challenging for the agents to generate individualised support for each student who might perform various learning activities on daily basis (Zatarain-Cabada et. Al, 2013).…”

Section: 0mentioning

confidence: 99%

The Future Direction of Cyberology

Azizan¹,

Tan²,

Ismail³

et al. 2014

ijcfh

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AbstrakObjektif untuk kertas kajian ini ialah untuk membincangkan hala tuju masa depan dunia siberologi.Ianya terdiri daripada tujuh kunci utama iaitu: 1) memfokuskan pada hala tuju masa depan infografik.2) menerangkan kajian masa hadapan tentang kejuruteraan perisian. 3) Menerokai “storytelling” digitaluntuk masa akan datang. 4) Menerangkan trend masa hadapan dalam pengimejan berkomputer. 5)membongkarkan potensi permainan mobil di masa hadapan. 6) mendedahkan pembangunan masadepan sistem tutor pintar. Akhir sekali, 7) membincangkan tentang kajian masa depan tentang interaksicomputer insan. Abstract The objective of this review paper is to discuss the future direction of cyberology. It consists of seven mainparts. Part 1 of this review focused on future direction of infographics. Part 2 of this review presents thefuture study of software engineering. Part 3 explores the future of digital storytelling. Part 4 shows thefuture trends in computer generated imagery. Part 5 discovers future potential of mobile games. Part 6reveals the future development of intelligent tutoring systems. Lastly, Part 7 discusses the future researchof human computer interaction.

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“…It is challenging for the agents to generate individualised support for each student who might perform various learning activities on daily basis (Zatarain-Cabada et. Al, 2013).…”

Section: 0mentioning

confidence: 99%

The Future Direction of Cyberology

Azizan¹,

Tan²,

Ismail³

et al. 2014

ijcfh

View full text Add to dashboard Cite

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Facial Expression Recognition for Intelligent Tutoring Systems in Remote Laboratories Platform

Khalfallah

Slama

2015

Procedia Computer Science

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Studying Affective Tutoring Systems for Mathematical Concepts

Mastorodimos

Chatzichristofis

2019

Journal of Educational Technology Systems

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Students face difficulties in learning mathematical processes. As a result, they have negative emotions toward mathematics. The use of technology is employed to change the student’s attitude toward mathematics. Some methods utilize intelligent tutoring systems to recognize student’s emotional state and adapt the learning process accordingly. These systems, known as affective tutoring systems (ATSs), sense the emotional state of a student and then intelligently attempt to suggest appropriate strategies that can guide the learning process and ultimately shift the negative attitude of students toward mathematical learning. This article presents a survey of ATSs, which teach mathematic content, and tries to find common elements among them. It examines the kind and the number of student’s emotions that can be recognized and the strategies and methods that these ATSs use to recognize student’s emotional state. There are findings that agree with other studies about the recognized emotions and the methods that are used.

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Integrating Learning Styles and Affect with an Intelligent Tutoring System

Cited by 3 publications

References 15 publications

The Future Direction of Cyberology

The Future Direction of Cyberology

Facial Expression Recognition for Intelligent Tutoring Systems in Remote Laboratories Platform

Studying Affective Tutoring Systems for Mathematical Concepts

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