Facial Emotion Analysis in Down's syndrome children in classroom

Torres-Carrión, Pablo; González-González, Carina S.; Carreño, Alberto Mora

doi:10.1145/2829875.2829882

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…Therefore, it is concluded that different section of learning process could employ different data source to analyze SDA to enhance cognitive ability. Similar to sentiment analysis in classrooms, Torres-Carrión, González-González, and Carreño (2015) identified the sentiments by facial expression. In the detailed research (Hao et al, 2013;Kim & André, 2008), Electroencephalographic (EEG) signals were viewed as an input of identifying students' sentiments.…”

Section: Classroommentioning

confidence: 99%

A review on sentiment discovery and analysis of educational big‐data

Han

Wu²,

Huang

et al. 2019

WIREs Data Min & Knowl

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Sentiment discovery and analysis (SDA) aims to automatically identify the underlying attitudes, sentiments, and subjectivity towards a certain entity such as learners and learning resources. Due to its enormous potential for smart education, SDA has been deemed as a powerful technique for identifying and classifying sentiments from multimodal and multisource data over the whole process of education. For big educational data streams, SDA faces challenges in unimodal feature selection, sentiment classification, and multimodal fusion. As such, a large body of studies in the literature explores diverse approaches to SDA for educational applications. This paper provides a self‐contained, uniform overview of the SDA techniques for education. In particular, we focus on prominent studies in unimodal sentiment features and classifications (e.g., text, audio, and visual). In addition, we present a novel SDA framework of multimodal fusions, together with description of their crucial components. Based on this framework, we review different approaches to SDA on education from the perspectives of approaches and applications. After comprehensively reviewing the SDA techniques on education, we present the trends and prospectives of the future SDA research under ubiquitous education contexts. This article is categorized under: Application Areas > Education and Learning

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Section: Classroommentioning

confidence: 99%

A review on sentiment discovery and analysis of educational big‐data

Han

Wu²,

Huang

et al. 2019

WIREs Data Min & Knowl

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“…Regarding the assessment of emotions in educational settings, researchers from the Human Computer Interaction area recognize the importance of the student's emotional state in the learning process [50], [51]. As the main goal, researchers want to know how a student is feeling in the classroom in order to produce significant learning [52]. González et al [53] propose different methods and techniques to evaluate the emotional state of children, such as facial expressions, and subjective measures of sentiment through questionnaires, interviews, and self-reports, using a multidimensional categorical approach.…”

Section: Overviewmentioning

confidence: 99%

“…The EMODIANA can measure not only the emotion, but also its intensity. In particular, we used an EMODIANA adapted for DS that allows the observer to register the different emotions of a student during a session ( Figure 1) [52]. This instrument can be used directly during the session or to analyze recorded videos of a session [55].…”

Section: Overviewmentioning

confidence: 99%

Computational Thinking and Down Syndrome: An Exploratory Study Using the KIBO Robot

et al. 2019

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Computational thinking and coding are key competencies in the 21st century. People with Down syndrome need to be part of this new literacy. For this reason, in this work, we present an exploratory study carried out with students with Down syndrome with cognitive ages of 3-6 years old using a tangible robot We applied the observational method during the sessions to analyze the participants' emotional states, engagement, and comprehension of the programming sequences. Results show that people with cognitive disabilities can acquire basic programming and computational skills using tangible robots such as KIBO.Informatics 2019, 6, 25 2 of 20 using the fundamental concepts of computing" [9]. The interest in this term continues to grow, as does the number of initiatives to promote its effective introduction in schools [10][11][12][13][14].Coding, programming, and computational thinking constitute a way for people to express and share their ideas [15]. In this sense, these skills can be integrated into almost any class activity, with or without technology, as a new literacy and a new way of thinking, integrated with other parts of the curriculum.Furthermore, educational robotics is a didactic approach that can be integrated into different educational environments [16]. This integration can be done through the use of programmable robotic devices and the application of project-based learning methodologies. The acquisition knowledge process can be improved through research and experimentation [17]. Robots can be used as physical tools for the development of cognitive skills through play, creativity, and the resolution of challenges [8]. Interaction with robots occurs physically when children manipulate the tool itself, play with it, and observe its movements [18]. Robots have appealing features and functions for children that able to maintain children's attention for a longer period of time, improving their performance, their ability to concentrate, and their cognitive flexibility, but it has also been found that a robot alone is not motivational enough [19]. The motivation for the use of the tool emerges from the activity, the problem or challenge to be solved, or from the story that the children represent using the robot [20]. For example, converting a robot into a character with a mission to fulfill or a role to embody engages children in different types of activities, offering them the opportunity to explore the possibilities of the environment [21].If the motivation for children to use a robotic tool is born of the challenge to achieve, it is possible to take advantage of this great opportunity to create learning environments and situations with clear curricular objectives, through which children feel strongly attracted and committed, encouraging their curiosity, creativity, and active participation, and in which they have an opportunity to build their own learning, enriching the experience while gaining digital and computational skills [4]. Furthermore, robots can also be very helpful in the teaching-learning of prog...

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“…Emotions have also been used as a way to inform the behaviour of robots in a multitude of CRI/CCI scenario. For example, with children suffering from Down syndrome [68] or Autism Spectrum Disorder (ASD) [19,66]. The researchers captured the emotions of children and used them to transfer the emotions to their peers [66,68], to display them on a robot [6,31,41] or to inform the decision making processes in the intelligent tutors [62,69,71].…”

Section: Related Work Children and Affectmentioning

confidence: 99%

“…For example, with children suffering from Down syndrome [68] or Autism Spectrum Disorder (ASD) [19,66]. The researchers captured the emotions of children and used them to transfer the emotions to their peers [66,68], to display them on a robot [6,31,41] or to inform the decision making processes in the intelligent tutors [62,69,71]. These efforts have shown to support social interaction [19,47,64], increase the engagement [6,7,32], enjoyment [30,41], motivation [69] and provided the ability to sustain interaction over long periods of time [30,31,49,69].…”

Section: Related Work Children and Affectmentioning

confidence: 99%

Joint Emotional State of Children and Perceived Collaborative Experience in Coding Activities

Sharma

Papavlasopoulou

Giannakos

2019

Proceedings of the 18th ACM International Conference on Interaction Design and Children

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This paper employs facial features to recognize emotions during a coding activity with 50 children. Extracting group-level emotional states via facial features, allows us to understand how emotions of a group affect collaboration. To do so, we captured joint emotional state using videos and collaborative experience using questionnaires, from collaborative coding sessions. We define groups' emotional state using a method inspired from dynamic systems, utilizing a measure called cross-recurrence. We also define a collaborative emotional profile using the different measurements from facial features of children. The results show that the emotional cross recurrence (coming from the videos) is positively related with the collaborative experience (coming from the surveys). We also show that the groups with better experience than the others showcase more positive and a consistent set of emotions during the coding activity. The results inform the design of an emotion-aware collaborative support system. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

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Facial Emotion Analysis in Down's syndrome children in classroom

Cited by 8 publications

References 9 publications

A review on sentiment discovery and analysis of educational big‐data

A review on sentiment discovery and analysis of educational big‐data

Computational Thinking and Down Syndrome: An Exploratory Study Using the KIBO Robot

Joint Emotional State of Children and Perceived Collaborative Experience in Coding Activities

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