Abstract
Quality education is the systematic learning and execution road map that build confidence among the learners and develop employability skills. Innovative techniques are the central facilitators of providing quality education for the younger generation. The economists, scientists, management experts, and research initiators are putting their efforts to develop a certain sustainable system in quality education through innovative technology. This is about digital equity, customized education, activity-based classroom, where the young mind is to be in synchronizing with the technology to explore new possibilities of learning and accomplishment. The research initiative reveals the system of implementing the innovative technology for quality education that has a direct impact on smart society development. The principal outcomes of the research initiative include the innovative ideas that transform the traditional education system into a dynamic education framework. The framework includes the integration of tools and techniques for standard mode of operations that reflects the productive and realistic education system. The researchers gracefully interconnected the concepts, methods, and applications of a quality education system that will open up new vistas for future research initiatives in the area of digital education, industry-institution collaboration, developing smart society, and economy of a nation at large. There is significant level of impact of innovative technology on quality education that leads to independent employability skills, creative, and innovative projects for facilitating future generation. All the influencing factors of resourceful intelligence together have great impact on smart society development that leads to provide modern facilities for the residents of smart society and create favorable environment for the future generations.
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Kanti Podder, S., Thomas, B., Samanta, D. (2022). Impact of Innovative Technology on Quality Education: The Resourceful Intelligence for Smart Society Development. In: Skala, V., Singh, T.P., Choudhury, T., Tomar, R., Abul Bashar, M. (eds) Machine Intelligence and Data Science Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 132. Springer, Singapore. https://doi.org/10.1007/978-981-19-2347-0_22
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DOI: https://doi.org/10.1007/978-981-19-2347-0_22
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