درخت حوزه‌های تخصصی

The evaluation of students' writings and the allocation of scores are traditionally time-intensive and inherently subjective, often resulting in inconsistencies among human raters. Automated essay scoring systems were introduced to address these issues; however, their development has historically been resource-intensive, restricting their application to standardized tests such as TOEFL and IELTS. Consequently, these systems were not readily accessible to educators and learners. Recent advancements in Artificial Intelligence (AI) have expanded the potential of automated scoring systems, enabling them to analyze written texts and assign scores with increased efficiency and versatility. This study aimed to compare the efficacy of an AI-based scoring system, DeepAI, with human evaluators. A quantitative approach, grounded in Corder's (1974) Error Analysis framework, was used to analyze approximately 200 essays written by Persian-speaking EFL learners. Paired sample t-tests and Pearson correlation coefficients were employed to assess the congruence between errors identified and scores assigned by the two methods. The findings revealed a moderate correlation between human and AI scores, with AI diagnosing a greater number of errors than human raters. These results underscore the potential of AI in augmenting writing assessment practices while highlighting its pedagogical implications for language instructors and learners, particularly in evaluating the essays of EFL students.

Background: Throughout history, humans have consistently developed groundbreaking technologies, from fire and the wheel to modern computing, showcasing their ability to innovate and control their creations. The rise of artificial intelligence has sparked renewed concerns about whether machines might eventually surpass human intelligence and autonomy.Aims: This study aims to critically assess AI’s role in human society, particularly addressing concerns that it may surpass human control and agency. It seeks to demonstrate that while AI is a powerful tool, it lacks autonomy, self-augmentation, and intentionality, making it unlikely to replace human decision-making. Additionally, the paper examines historical technological advancements, showing how humans have always adapted and controlled new innovations.Methodology: Employing a historical-comparative methodology, this study traces the evolution of computing technologies from early tally systems to quantum computing. It incorporates philosophical analysis through the works of Hubert Dreyfus, John Searle, and Michael Tomasello, assessing AI’s limitations in replicating human cognition.Findings: The study finds that despite AI’s rapid advancements, it remains fundamentally dependent on human input, lacks true understanding, and is incapable of independent self-enhancement. The historical trajectory of technological progress demonstrates that while new technologies can disrupt societies, humans have consistently adapted and maintained control. Philosophical critiques of AI further reinforce the argument that intelligence is not solely computational but deeply rooted in embodiment, intuition, and shared intentionality—qualities that AI lacks.Conclusions: Concerns about AI overwhelming human agency are largely misplaced. Just as humanity has managed previous technological revolutions—including writing, mechanization, and computing—AI will be integrated and regulated according to human needs and ethical considerations. While vigilance is necessary, the myth of AI autonomy is exaggerated.

Background: With the rapid digital transformation across the African continent, ensuring the protection of personal data through effective regulatory frameworks is crucial. Key regulations, including Nigeria’s Data Protection Regulation (NDPR) and the African Union’s Convention on Cyber Security and Personal Data Protection, have been enacted to address growing concerns about data privacy and cybersecurity.Aims: This literature review critically examines the impact of data privacy regulations on cybersecurity practices in Nigeria and across Africa, focusing on empirical studies that highlight the interplay between regulation enforcement and cybersecurity outcomes.Methodology: This review synthesizes empirical studies that explore the effectiveness of these regulations in improving cybersecurity practices in both public and private sectors.Results: Empirical research from Nigeria indicates that while the NDPR has led to some positive changes in organizational data protection strategies, challenges in enforcement, resource allocation, and awareness continue to hinder its full impact. Studies reveal that small to medium enterprises (SMEs) face difficulties in complying with the regulations due to a lack of capacity and knowledge. Similarly, research across several African countries shows a significant gap in both the implementation of data privacy laws and the cybersecurity measures required to mitigate emerging threats, such as ransomware and data breaches. Furthermore, empirical evidence highlights that varying levels of regulatory enforcement across the continent result in inconsistent cybersecurity practices, leading to vulnerabilities in the digital infrastructure. The review also explores empirical findings on the socio-economic and political barriers that affect the successful enforcement of data privacy regulations, with particular focus on limited technical expertise, political instability, and insufficient resources for regulatory bodies. Additionally, studies suggest that there is a growing need for cross-border collaboration and capacity building to bridge the regulatory gaps and improve overall cybersecurity resilience.Conclusion: Empirical evidence underscores the need for stronger regulatory frameworks and greater cooperation across African nations to enhance the protection of personal data and fortify cybersecurity practices across the region. Recommendations for future policy development are provided, based on the insights gained from existing empirical studies.