Blockchain Papers

Chamath Liyanage, U. A. D. S. Kavinda, Dinuka Dasanayaka, P. G. J. Shehara · 5 authors

In many cases, children between this age are using smartphones and other technology devices, to play games, watch cartoons, take photos and sometimes the chance is getting higher than we think that children access unnecessary contents due to lack of guidance and unawareness of parents. This interactive mobile application is used as an adaptive learning tool for the primary school students. Utilizing children’s comfort with technology allows for the development of their talents. In math skills development, some attractively designed gamified activities to solve basic math questions are given according to the skill level the child is currently in. The accuracy was much higher in the Convolutional Neural Network approach as it recorded a value of 0.9919. In environmental skills development component, the app will ask child to identify the surroundings according to a flow, starting from the house and towards the garden using object detection and the results were detected with a higher accuracy level around 0.9-0.99 after training the Machine Learning model. And in the language skills development component the child is given activities to develop pronunciation skills using audio processing and finally the verification of online achievements of a child by Non-Fungible Token technology, is fulfilled via the app.

Om P. Sharma

Financial literacy among Generation Z is alarmingly low, especially around compound interest and credit. This paper presents an innovative, Web3-based gamified learning system that uses low-cost 3-D avatars and visual narratives to teach compounding concepts. By integrating NFTs for identity, interactive missions, and real-time compounding simulation within a metaverse environment, the platform aims to engage 18–24-year-olds intuitively and enhance knowledge retention. A prototype was implemented and evaluated with a randomized controlled trial (N = 100) comparing it to traditional text-based instruction. The Web3 gamified group outperformed the control group significantly (75 % vs 55 %, p < 0.01), with higher engagement scores and intent to apply concepts. Qualitative feedback highlighted the motivational effect of avatar growth and NFT rewards. Results show that Web3 gamification can meaningfully improve compound interest learning while remaining low-cost and scalable. Limitations include gas-cost friction and novelty bias. Future work includes deploying advanced financial topics, refining UX to mitigate over-gamification, and evaluating long-term retention and cross-cultural adoption.

Alba González-Moreira, Camino Ferreira, Javier Vidal

<p style="text-align:justify">The educational transition between early childhood education and primary education is a complex moment of change with repercussions throughout the academic life of the students. For this reason, it is important to seek continuity between both educational stages. A successful transition produces for the social, cognitive and emotional well-being of the student. The aim of this study is to find out how transition-related factors apply in ten European Union (EU) countries. The factors analyzed are the age of onset of transition, the teacher–student ratio, types of clustering, financing of the stage, responsibility, and both initial and in-service teacher training. The methodology followed in this study is documentary analysis and the main source of data search has been the European Commission's Eurydice portal. The results show differences in stage change within each country, especially in the explicit consideration of a transition period. The main conclusion is that there is a great difference between the northern and southern countries. The main differences between countries in the transitions from early childhood education to primary education in the EU are in the years of compulsory education, the teacher/student/unit ratio, the initial teacher training, and the decentralization of education.</p>

Md. Abdur Rahman, Elham Hassanain, Md. Mamunur Rashid, Stuart J. Barnes · 5 authors

In this paper, we present a novel method, process, and system for calculating dyslexic symptoms, generating metric data for an individual user, community, or group in general. We present a mobile multimedia Internet of Things (IoT)-based environment that can capture multimodal smartphone or tab-based user interaction data during dyslexia testing and share it via a mobile edge network, which employs auto-grading algorithms to find dyslexia symptoms. In addition to algorithm-based auto-grading, the captured mobile multimedia payload is stored in a decentralized repository that can be shared with a medical practitioner for replay and further manual analysis purposes. Since the framework is language-independent and based on Blockchain and a decentralized big data repository, dyslexic patterns and a massive amount of captured multimedia IoT test data can be shared for further clinical research, statistical analysis, and quality assurance. Notwithstanding, our proposed Blockchain and off-chain-based decentralized and secure dyslexia data storage, management, and sharing framework will allow security, anonymity, and multimodal visualization of the captured test data for mobile users. This paper presents the detailed design, implementation, and test results, which demonstrate the strong potential for wider adoption of the dyslexia mobile health management globally.