Researching affective computing techniques for intelligent tutoring systems

Ivanova, Malinka

doi:10.1109/icl.2013.6644661

Cited by 8 publications

(8 citation statements)

References 42 publications

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“…This minimum number of emotions could be taken into consideration when it could be designed a new ATS for mathematics. In a survey for affective computing techniques for ITS, there are systems that recognize between six and seven emotions (Ivanova, 2013). Also, there is a group of emotions, which follows OCC method, which could be into consideration when it is designed an ATS for mathematical concepts.…”

Section: Discussionmentioning

confidence: 99%

“…The Easy with Eve is an ATS for teaching mathematics suitable for primary school students (Sarrafzadeh et al., 2008). It is mentioned as the first fully functioning ATS (Ivanova, 2013). Initially, the system was designed as an automated face expression analysis system (S. Alexander, 2005; Sarrafzadeh et al., 2004) and gesture analysis (S. Alexander, 2005), but it ultimately uses real-time face expression analysis (Sarrafzadeh, Fourie, Alexander, Overmyer, & Shanbehzadeh, 2014) for mathematics.…”

Section: Analysis Of Five Atssmentioning

confidence: 99%

“…Furthermore, one of the main aims of an ATS is to change the student’s emotional state from negative to positive (Zatarain-Cabada, Barrón-Estrada, Alor-Hernández, & Reyes-García, 2014). Emotions are very important in learning, and thus positive emotions enhance learning while negative emotions could weaken the process of learning (Ivanova, 2013; Kort, Reilly, & Picard, 2001).…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Five Atssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Studying Affective Tutoring Systems for Mathematical Concepts

Mastorodimos

Chatzichristofis

2019

Journal of Educational Technology Systems

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“…A good ITS requires adaptability and as close to a human response as possible such that the student’s emotions and behavior are quantified and the learning adjusted accordingly. The feedback systems such as AutoTutor demonstrated by Graesser et al [110], and the GnuTutor-based feedback system described by Ivanova [111] are built upon the ideas of these adaptable chat systems and are capable of assessing student mood to adjust the output and teaching style accordingly.…”

Section: Modern Intelligent Tutoring Systemsmentioning

confidence: 99%

Comparison and Efficacy of Synergistic Intelligent Tutoring Systems with Human Physiological Response

Alqahtani

Ramzan

2019

Sensors

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The analysis of physiological signals is ubiquitous in health and medical diagnosis as a primary tool for investigation and inquiry. Physiological signals are now being widely used for psychological and social fields. They have found promising application in the field of computer-based learning and tutoring. Intelligent Tutoring Systems (ITS) is a fast-paced growing field which deals with the design and implementation of customized computer-based instruction and feedback methods without human intervention. This paper introduces the key concepts and motivations behind the use of physiological signals. It presents a detailed discussion and experimental comparison of ITS. The synergism of ITS and physiological signals in automated tutoring systems adapted to the learner’s emotions and mental states are presented and compared. The insights are developed, and details are presented. The accuracy and classification methods of existing systems are highlighted as key areas of improvement. High-precision measurement systems and neural networks for machine-learning classification are deemed prospective directions for future improvements to existing systems.

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“…In the year 2013, Ivanova. M [42] proposed the concept of facial and gesture recognition method for an ITS system. If one applies these techniques in their system, it will act something like human tutor.…”

Section: Different Expert Systems For Assisting and Improving Teachinmentioning

confidence: 99%

Survey of Expert Systems and the Cognitive Approaches towards an Effective Tutoring System

Chaturvedi¹,

Prajapati²

2015

IJCA

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This paper presents a survey of Expert Tutoring System (ETS), designed for the improvement of teaching pedagogy. It talks about the flaws and designing issues that may occur in designing the expert tutoring system, and also suggests the cognitive approach for building a robust tutoring system. It describes the ill defined domains, case based reasoning, and the system approach for the designing of a cognitive tutoring system.

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Researching affective computing techniques for intelligent tutoring systems

Cited by 8 publications

References 42 publications

Studying Affective Tutoring Systems for Mathematical Concepts

Studying Affective Tutoring Systems for Mathematical Concepts

Comparison and Efficacy of Synergistic Intelligent Tutoring Systems with Human Physiological Response

Survey of Expert Systems and the Cognitive Approaches towards an Effective Tutoring System

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