TY - JOUR
T1 - Intelligent gesture interfaces in immersive education
AU - Masapanta-Carrión, Susana
AU - Guaña-Moya, Javier
AU - Arteaga-Alcívar, Yamileth
N1 - Publisher Copyright:
© 2025; Los autores.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Introduction: intelligent gesture interfaces are transforming immersive education by enabling more intuitive and efficient interactions between students and digital content through bodily movements, especially facial and manual gestures. When integrated with technologies such as augmented reality and virtual reality, these interfaces enhance body perception, information retention, and the understanding of complex concepts, promoting a more active and personalized learning experience. Method: this study employed a Systematic Literature Review (SLR) based on Kitchenham’s methodology, structured in planning, execution, and presentation phases. Academic and empirical studies published since 2019 were selected, focusing on the integration of gesture interfaces with artificial intelligence in educational contexts and assessing their effectiveness, applicability, and associated challenges. Results: the findings revealed that these interfaces support student engagement, adapt to individual needs, and strengthen multimodal learning. Technologies such as depth sensors, neural networks, and multimodal systems were identified as enabling more fluid and natural interaction. Despite their potential, technical challenges were noted, including gesture variability, real-time processing demands, and lack of standardization, as well as pedagogical barriers such as curricular integration and learning assessment. Conclusions: it is concluded that intelligent gesture interfaces, when complemented by artificial intelligence, hold strong potential to enrich educational experiences, support personalized and student-centered learning environments, and align pedagogical practice with participatory and constructivist models of education.
AB - Introduction: intelligent gesture interfaces are transforming immersive education by enabling more intuitive and efficient interactions between students and digital content through bodily movements, especially facial and manual gestures. When integrated with technologies such as augmented reality and virtual reality, these interfaces enhance body perception, information retention, and the understanding of complex concepts, promoting a more active and personalized learning experience. Method: this study employed a Systematic Literature Review (SLR) based on Kitchenham’s methodology, structured in planning, execution, and presentation phases. Academic and empirical studies published since 2019 were selected, focusing on the integration of gesture interfaces with artificial intelligence in educational contexts and assessing their effectiveness, applicability, and associated challenges. Results: the findings revealed that these interfaces support student engagement, adapt to individual needs, and strengthen multimodal learning. Technologies such as depth sensors, neural networks, and multimodal systems were identified as enabling more fluid and natural interaction. Despite their potential, technical challenges were noted, including gesture variability, real-time processing demands, and lack of standardization, as well as pedagogical barriers such as curricular integration and learning assessment. Conclusions: it is concluded that intelligent gesture interfaces, when complemented by artificial intelligence, hold strong potential to enrich educational experiences, support personalized and student-centered learning environments, and align pedagogical practice with participatory and constructivist models of education.
KW - Artificial Intelligence
KW - Experiential Learning
KW - Gesture Interfaces
KW - Immersive Education
KW - Virtual Reality
UR - https://www.scopus.com/pages/publications/105010113714
U2 - 10.56294/saludcyt20251810
DO - 10.56294/saludcyt20251810
M3 - Review article
AN - SCOPUS:105010113714
SN - 2796-9711
VL - 5
JO - Salud, Ciencia y Tecnologia
JF - Salud, Ciencia y Tecnologia
M1 - 1810
ER -