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Big data assisted eco-learning environment framework for inclusive education Soon, JosephNg Poh; Lanlan, Pan; Ji, Yuehua; Luo, Jinxia; Yuen, Phan Koo; Donghui, Xie
International Journal of Advances in Applied Sciences Vol 14, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v14.i1.pp200-208

Abstract

Big data is profoundly changing education under inclusive education. Classroom interaction, a vital component in education, is gaining increased emphasis, driving research into learning environments that better meet interaction needs. Therefore, exploring the construction of a big data-assisted eco-learning environment for classroom interaction is a prospective study. This research focuses on constructing a big data-assisted ecological learning environment based on affordance theory. It examines the relationship among learning environment, classroom interaction, and learning outcomes, using SmartPLS for validation. Through controlled experiments, surveys, teacher-student interaction analysis, and interviews, the study explores learner behavior data. Findings show the big data-assisted eco-learning environment enhances English classroom interaction, thereby further improving learning outcomes, across dimensions like learning space, resource accessibility, technical support, and emotional support. Integrating big data with ecological theory offers insights into educational digitization, supporting flexible classroom interaction, and promoting education equity, inclusivity, and sustainable education through data-driven resource management.
User perceptions of artificial intelligence powered phishing attacks on Facebook's resilient infrastructure Soon, JosephNg Poh; Chan, Rou Qian; Lee, Qian Hui; Loke, Dick En; Chun, Stevenson Ling Heng; Yuen, Phan Koo
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp878-886

Abstract

This study focuses on examining the user perceptions of a cybersecurity certificate transparency (CT) monitoring tool in the context of artificial intelligence (AI) powered phishing attacks on the Facebook platform. Implementing CT monitoring tools is one strategy for preventing these attacks. It reveals a significant level of concern among respondents regarding the potential risks associated with phishing attacks, indicating a growing awareness of the severity of such threats for future resilient infrastructure development. Users' knowledge and understanding of AI-driven phishing threats were found to vary, emphasizing the need for awareness campaigns towards sustainable development education. The study also highlights varying levels of confidence among users in effectively identifying and thwarting phishing efforts, suggesting the importance of user empowerment through improved training, tools, and technologies as responsive institutions. These findings underscore the significance of addressing user concerns, enhancing security awareness, and providing users with the necessary resources to protect themselves against sophisticated phishing attacks. The research contributes to the understanding of user perceptions and lays the groundwork for further improvements in security measures and user education in the fight against phishing threats on Facebook's inclusive growth.
Quantum computing impact of cybersecurity identity verification measures on WhatsApp resilient infrastructure Soon, JosephNg Poh; Preeta, Nair; Praveen, Kumar; Yew, Kok Peng; Yuen, Phan Koo
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp840-849

Abstract

This study investigates the impact and implications of implementing cybersecurity identity verification on the popular instant messaging platform, WhatsApp. Specifically, it focuses on the effects of such a measure on resilient infrastructure, user perceptions of the platform's branding and trustworthiness, and the cost-effectiveness of this approach in preventing scams, phishing, fraud, and cybercrime. Empirical data collected from a diverse group of WhatsApp users highlight that the introduction of identity verification could potentially enhance transaction efficiency, foster trust, and boost user satisfaction, particularly regarding the platform's security. However, the cost and complexity of implementation pose significant challenges. Despite these hurdles, most users perceive the potential benefits to outweigh the associated costs, pointing to a broad acceptance of such security measures. The study provides practical and theoretical contributions, offering valuable insights for managers and decision-makers at WhatsApp, as well as contributing to academic discussions on digital platform management and security. The research also underscores the societal implications of such a measure, suggesting an increase in trust in digital communication platforms and supporting safer financial transactions on social media. The integration of identity verification on WhatsApp being a responsive institution emerges as a valuable but complex endeavor, demanding careful planning to ensure maximum value creation for all stakeholders.