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This chapter discusses Decentralized Learning Management Systems (DLMS) as a novel method of contemporary education by combining blockchain, federated learning, and distributed technologies. It analyzes the architectural design, scalability issues, and implementation obstacles of DLMS, and stresses their benefits over...
The development of smart classroom technology hastened the implementation of data-driven and personalized learning systems, with the significant concern of data privacy, security, and trust. In this chapter, the author introduces a combined system of Federated Learning (FL) and blockchain to implement decentralized and...
The AI-based learning analytics is revolutionizing STEAM learning by facilitating adaptable, information-based, and individualised learning space. The chapter discusses the application of machine learning, natural language processing and predictive analytics to multimodal data on learners to create dynamic learner prof...
Neurodivergent factors that commonly have their effect on learning, behavior and social participation are sensory hypersensitivity, emotional dysregulation and cognitive overload. It is on this chapter, where the Emotionally Adaptive IoT Ecosystem is proposed and it takes a step beyond the simple identification of emot...
The chapter introduces the Cognitive Drift Mapping that is a longitudinal and entropy-based approach to detecting preclinical neurodegeneration using ambient micro-behavioral IoT signals. The methodology is the description of gradual changes in daily activities in behavioral patterns such as gait speed, speech response...
As ESG principles and cutting-edge digital innovations intersect in the creative economy, strategic leadership is changing in ways never before imaginable. This chapter discusses the role of Explainable Artificial Intelligence (XAI) in supporting ESG-driven decision intelligence by allowing a leader to make transparent...
The current world economies are in a highly volatile framework characterized by thick interdependencies, and quick changing risk factors. The classical econometric models with their assumption of the stasis and restrictive data granularity cannot predict systemic shocks and timely interventions. This chapter provides a...
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