Artificial Intelligence-Enabled Game-Based Learning and Quality of Experience: A Novel and Secure Framework (B-AIQoE)

【Author】 Wagan, Asif Ali; Khan, Abdullah Ayub; Chen, Yen-Lin; Yee, Por Lip; Yang, Jing; Laghari, Asif Ali

【Source】SUSTAINABILITY

【影响因子】3.889

【Abstract】Game-based learning in schools and colleges, with the help of AI-enabled augmented intelligence techniques, is reported to improve children's neurodevelopment, intellectual sensing, and specific learning abilities, according to US officials. There is currently a huge transformation from traditional assisted learning to augmented reality-enabled computer-based learning. Globally, there has been a dramatic increase in the use of game-based augmented learning in most schools and colleges. A few problems arise that create concern, such as the emerging effects of gaming on institutional premises, the disordering of children's involvement after game-learning, the rate of learning and attendance, adaptation, and teachers' experience. To address these individual aspects, we proposed a blockchain Ethereum-enabled, secure AI-based augmented game learning environment, called B-AIQoE, in which protected on-chain and off-chain channels are designed to handle all the transactions and exchanges among students before analysis in terms of color transition, redundancy, unethical transmission, and related vulnerabilities. On the other hand, the proposed system examines and analyzes the Quality of experience (QoE) and improves accessibility as it receives feedback from the students and teachers. For the purpose of automating game-based transactions, three different aspects are discussed, such as verifying and validating student-teacher registration, creating content for game-based learning and privacy, and updating students' records and exchanges. Finally, this paper separates, analyzes, and discusses a list of emerging challenges and limitations and their possible solutions involved in creating the proposed system.

【Keywords】blockchain Ethereum; artificial intelligence (AI); augmented intelligence; Internet of things (IoT); Quality of experience (QoE); game-based learning

【发表时间】2023 MAR

【收录时间】2023-05-10

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-教育领域