https://repository.cuk.ac.ke/handle/123456789/569 DCSIT 2026-07-20T23:19:21Z https://repository.cuk.ac.ke/handle/123456789/1978 Economic constraints and parenting in single-parent families.The case of Kaptembwa ward, Nakuru county, Kenya. Awuor, Euphemia.; Chesikaw, Lilian.; Wambu, Charles Parenting requires more than child conception and birth, it needs behavior development individually and working together to influence the child physical, social, emotional and cognitive outcome. Increased change in family structure and pattern in Kenya and other countries across the world affects the child’s wellbeing. Kaptembwa area is characterized by high poverty rates and limited economic opportunities, presents significant challenges for single-parent households in meeting their children's basic needs and ensuring positive developmental outcomes. Using a mixed-methods approach, the research explored how income levels influence parenting practices, access to education, emotional support, and overall child well-being. A mixed-methods research design was employed, integrating both quantitative and qualitative approaches. Data were collected from 121 respondents. Data was collected through structured questionnaires and Key Informants interviews to single parents, educators, and community leaders. Findings reveal that low income severely limits parental capacity to provide adequate nutrition, education, healthcare, and emotional support, often resulting in compromised parenting and adverse effects on children’s academic performance and social behavior. The study underscores the need for targeted economic empowerment programs, improved access to social services, and community-based support systems to alleviate the pressures on single parents. Recommendations are offered to inform policy and intervention strategies aimed at improving the livelihoods of single-parent families in resource-constrained urban settings. An article published in the International Journal of Social Sciences and Information Technology 2025-08-01T00:00:00Z https://repository.cuk.ac.ke/handle/123456789/1974 An intelligent curriculum alignment model for digital skills integration in higher education: a data-driven approach to bridge academia- industry gaps Nyale, Duncan; Karume, Simon; Kipkebut, Andrew; Mukudi, Fidelis; Sharafat, Abrar The rapid evolution of digital technologies has created significant misalignment between academic curricula and labor market demands for digital skills. This misalignment is especially critical in rapidly digitizing regions such as East Africa, where workforce readiness is critical for economic development. This study presents the development and validation of an intelligent curriculum alignment model that systematically analyzes university curricula, identifies digital competencies, and maps them to labor market requirements. The research employed a hybrid artificial intelligence approach combining web scraping, Natural Language Processing (NLP), and a Decision Tree classification algorithm to create a comprehensive solution. The skillset database was built from over 46,000 real-time job postings (focused on Nairobi, Kenya) and supports continuous updates to capture emerging trends. We evaluated the model using k-fold cross-validation and expert review to ensure robustness. The model achieved an overall accuracy of 88% in classifying curriculum skills as high- or low-demand, demonstrating strong performance with an exceptional recall (0.99) for high-frequency, in-demand skills. Receiver Operating Characteristic (ROC) analysis yielded an area under the curve of 0.94, and narrow 95% confidence intervals confirmed the stability of these metrics. The study utilized data from 46,514 job postings across 27 occupations, resulting in a skillset database of 9,077 unique digital skills categorized by market demand. The intelligent model generates three key outputs: a Curriculum Analysis Report, a Digital Skills Index (DSI) scoring curriculum alignment on a 0–100 scale, and a Prescriptive Analytics Report providing data-driven recommendations for curriculum improvement. Key recommendations derived from this work include the continuous integration of high-demand digital skills, promotion of interdisciplinary digital literacy, active industry participation in curriculum design, and the formulation of comprehensive national digital skills strategies. The model’s inherent capacity for continuous adaptation positions it as a vital tool for preparing a workforce that is not only ready for current demands but also resilient and adaptable to future technological shifts. This research addresses critical gaps in educational responsiveness to technological change and provides a scalable framework for continuous curriculum optimization in the digital era. A research article published in the discover education press. 2026-01-30T00:00:00Z https://repository.cuk.ac.ke/handle/123456789/1936 Hybrid Encryption Model for Secure Token Distribution Scheme Ayuma, Michael Juma; Angolo, Shem Mbandu; Kasyoka, Philemon Nthenge Encryption is essential for safeguarding sensitive data by transforming it into a secret code, which can only be decrypted by authorized parties. This ensures privacy and protects data from unauthorized access. While various encryption algorithms exist, relying on a single method may not provide sufficient security, particularly in the context of token transmission. Common threats such as brute force attacks, man-in-the-middle (MITM) attacks, token modification, and replay attacks are prevalent in adversarial attempts to breach the security of tokens during transmission. When these vulnerabilities are not addressed, they can compromise token integrity and the security of the entire authentication process. This study aims to design an efficient cryptographic protocol for the secure transmission of tokens by investigating existing encryption techniques and developing a hybrid cryptographic scheme. Unlike traditional encryption methods, hybrid cryptography combines multiple encryption algorithms to enhance security, making it more resilient against various types of attacks. Previous applications have shown that hybrid cryptography can effectively ensure confidentiality and prevent unauthorized access to highly sensitive information, such as user credentials and authentication tokens. The proposed model integrates Secure Hash Algorithm (SHA-2), ChaCha20, and Rivest-Shamir-Adleman (RSA). SHA-2 is used to ensure the integrity and confidentiality of the data, providing protection against brute force and relay attacks during token transmission. ChaCha20, a symmetric encryption algorithm, is employed to securely generate private keys for encrypting the tokens, while RSA, an asymmetric encryption method, facilitates secure key exchange within the hybrid system. The design is based on computational complexity theory, where the increased complexity of encryption operations significantly strengthens the system against adversarial attacks. This hybrid encryption model specifically addresses the security of token transmission, offering a robust solution for secure token distribution across diverse fields such as healthcare, education, agriculture, and commerce. By evaluating the impact of adversarial models on hybrid encryption schemes, the study provides insights into mitigating security risks and improving the resilience of token transmission systems. A Journal article published in the Tech Science Press. 2026-03-16T00:00:00Z