Technology-based solutions for behavior monitoring: lessons learned

Pandria, Niki; Bamidis, Panagiotis D.

doi:10.3389/feduc.2023.1150239

Cited by 1 publication

(1 citation statement)

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“…It utilizes a five-level Likert scale, with “1” representing “very sad” and “5” representing “very happy,” using emoticons for visual representation ( Antoniou et al, 2017 ; Siouli et al, 2020 ). Originally developed to monitor students’ moods before and after university or classroom lectures, AffectLecture has also been applied to monitor emotional changes in smokers undergoing biofeedback and neurofeedback training, among other developmental/educational protocols ( Pandria and Bamidis, 2023 ). Access to specific sessions is restricted to users attending the session, requiring a 4-digit PIN provided by the instructor who registers the session on the app.…”

Section: Methodsmentioning

confidence: 99%

Masked emotions: does children’s affective state influence emotion recognition?

Mastorogianni,

Konstanti,

Dratsiou

et al. 2024

Front. Psychol.

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IntroductionFacial emotion recognition abilities of children have been the focus of attention across various fields, with implications for communication, social interaction, and human behavior. In response to the COVID-19 pandemic, wearing a face mask in public became mandatory in many countries, hindering social information perception and emotion recognition. Given the importance of visual communication for children’s social-emotional development, concerns have been raised on whether face masks could impair their ability to recognize emotions and thereby possibly impact their social-emotional development.MethodsTo this extent, a quasiexperimental study was designed with a two-fold objective: firstly, to identify children’s accuracy in recognizing basic emotions (anger, happiness, fear, disgust, sadness) and emotional neutrality when presented with faces under two conditions: one with no-masks and another with faces partially covered by various types of masks (medical, nonmedical, surgical, or cloth); secondly, to explore any correlation between children’s emotion recognition accuracy and their affective state. Sixty-nine (69) elementary school students aged 6-7 years old from Greece were recruited for this purpose. Following specific requirements of the second phase of the experiment students were assigned to one of three (3) distinct affective condition groups: Group A-Happiness, Group B-Sadness, and Group C-Emotional Neutrality. Image stimuli were drawn from the FACES Dataset, and students’ affective state was registered using the self-reporting emotions-registration tool, AffectLecture app.ResultsThe study’s findings indicate that children can accurately recognize emotions even with masks, although recognizing disgust is more challenging. Additionally, following both positive and negative affective state priming promoted systematic inaccuracies in emotion recognition. Most significantly, results showed a negative bias for children in negative affective state and a positive bias for those in positive affective state.DiscussionChildren’s affective state significantly influenced their emotion recognition abilities; sad affective states led to lower recognition overall and a bias toward recognizing sad expressions, while happy affective states resulted in a positive bias, improving recognition of happiness, and affecting how emotional neutrality and sadness were actually perceived. In conclusion, this study sheds light on the intriguing dynamics of how face masks affect children’s emotion recognition, but also underlines the profound influence of their affective state.

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Section: Methodsmentioning

confidence: 99%