On the Effects of a Nomadic Multisensory Solution for Children's Playful Learning

Gelsomini, Mirko; Rotondaro, Annalisa; Cosentino, Giulia; Gianotti, Mattia; Riccardi, Fabiano; Garzotto, Franca

doi:10.1145/3279778.3279790

Cited by 9 publications

(6 citation statements)

References 34 publications

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“…Commenting video recordings, teachers pinpointed that children in IMAGINE changed their roles: those who were usually more introverted and less active were the ones who shot out joy and motivated their mates. We deduce IMAGINE was the role changer of these dynamics as also happened in other on-the-field studies [32].…”

Section: Insightssupporting

confidence: 84%

Embodied Learning in Immersive Smart Spaces

Gelsomini

Leonardi

Garzotto

2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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This paper presents the design and evaluation of IMAGINE, a novel interactive immersive smart space for embodied learning. In IMAGINE children use full-body movements and gestures to interact with multimedia educational contents projected on the wall and on the floor, while synchronized light effects enhance immersivity. A controlled study performed at a primary school with 48 children aged 6-8 highlights the educational potential of an immersive embodied solution, also compared to traditional teaching methods, and draws some implications for smart-space technology adoption in educational contexts.

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Section: Insightssupporting

confidence: 84%

Embodied Learning in Immersive Smart Spaces

Gelsomini

Leonardi

Garzotto

2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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“…All the identified systems provide visual stimuli, usually conveyed through images and written texts [49], [52], [60]. Some technologies also support video and lighting [19], [71]; for example, Gelsomini et al developed a collaborative game with portable lights in which children learned colors by associating them to a particular element [48]. Most of the technologies are also equipped with auditory stimuli with sounds or music, which can also represent feedback (correct or incorrect sounds) or even distractions (e.g., audio distractors to increase the difficulty level [13]).…”

Section: Physical-touchmentioning

confidence: 99%

“…Therefore, the Several studies used sensor-based analytics to enrich the interaction modality, but those analytics were not used further (e.g., to detect learners' progress or behaviour). In particular, most of the studies utilized (but did not collect) sensor data from the users (how users move and their skeleton points), with the systems processing these data 'on-the-fly' to enable motion-based interaction and mid-air gestures, resulting in increased immersion [48], [63], [60]. The majority of the articles used self-reports with Likert scales, coding videos, and focus groups with experts and instructors to detect learners' behavior and emotions during the learning process.…”

Section: Physical-touchmentioning

confidence: 99%

“…Articles that studied children with intellectual disabilities worked mostly to improve the cognitive skills of the subjects with therapy interventions [60], [51], memory skills, and emotions [13] but also to increase collaboration and inclusion between peers [65], [48]. One of the papers included academic performance improvements (mostly in mathematics) [14].…”

Section: Physical-touchmentioning

confidence: 99%

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Multisensory Interaction and Analytics to Enhance Smart Learning Environments: A Systematic Literature Review

Cosentino

Giannakos

2023

IEEE Trans. Learning Technol.

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Smart learning environments (SLEs) leverage technological developments to enable effective, engaging and personalized learning. SLEs rely on sensor and advanced interconnectivity capabilities to infer and reason. A natural set of affordances for SLEs are those of Multisensory Environments (MSEs). MSEs enable humans to make full use of their senses and equip learning systems with new information, methods of information exchange, and intelligent capabilities. In addition to novel forms of interaction, MSEs also offer novel forms of "learner traces" through Multimodal Learning Analytics (MMLA). This paper presents the results of a systematic literature review on how multisensory interactions and the respective analytics can support the use and design of SLEs. The findings from the analysis of 33 papers synthesize and clarify the latest advancements in the intersection of interactions and analytics in MSEs, discuss how those advancements can support SLEs' affordances and uses, and pave the way for improving our understanding of how various interaction modalities can support learning and under what conditions.

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“…With the rapid development of human‐computer interaction, children's user interfaces have been widely used in many fields, such as preschool education, children's educational games, and game‐based learning software. Therefore, color design in children's interfaces has become a very important research topic 17‐19 …”

Section: Introductionmentioning

confidence: 99%

Color design in application interfaces for children

Lyu

Liu

2021

Color Research & Application

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This study investigated the effect of age and application type on the color design of user interfaces for children's applications. We collected 223 popular children's applications from the Apple App Store, focusing on children of three age groups (3‐5, 6‐8, and 9‐11 years old). There were two types of applications: educational applications and game applications. To explore further and compare the differences between children and adults, we also collected color data on 58 adult applications (29 educational applications and 29 game applications). Due to the characteristics of the specific model, this article selects the HSB (Hue, Saturate, Bright) color model—which is composed of hue, saturation, and brightness, with a high degree of matching with the color vision of the human eye—to analyze the color of the application interfaces. According to the statistics, in terms of hue, different types of application interfaces use different frequencies of colors. Multicolor educational application interfaces use cool colors, such as blue; multicolor game application interfaces use warm colors, such as red and orange; and so on. In terms of saturation, the frequency of high saturation in children's user interfaces is higher than that in adult user interfaces. In terms of brightness, children's application interfaces often use brighter colors. We also compared the statistical results with traditional color cognitive conclusions and discussed the possible reasons.

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On the Effects of a Nomadic Multisensory Solution for Children's Playful Learning

Cited by 9 publications

References 34 publications

Embodied Learning in Immersive Smart Spaces

Embodied Learning in Immersive Smart Spaces

Multisensory Interaction and Analytics to Enhance Smart Learning Environments: A Systematic Literature Review

Color design in application interfaces for children

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