Masters Projects and Theses

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Browsing Masters Projects and Theses by Subject "adaptive leadership practices"

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    Adaptive leadership practices and management of teachers in public secondary schools in tharaka south sub-county, tharaka nithi county, kenya
    (Chuka University, 2024) Mugambi Gatawara Irene
    Effective teacher management is widely recognised to be vital in the thriving of education systems leading to the dispensation of positive education outcome. Schools are vulnerable to modern challenges that can affect effective teacher management. Principals are the heads of management in public secondary schools thus are expected to oversee teacher management functions in schools. There is a growing concern that principals are lacking adaptive leadership skills needed to navigate the complex education environment. The purpose of this study was to establish the relationship between principal’s collaborative problem solving strategies and teacher management in public secondary schools, Tharaka South sub-county, Tharaka Nithi County, Kenya; To examine the relationship between principals’ support for a culture of continuous learning and teacher management in public secondary schools Tharaka South sub-county, Tharaka Nithi County, Kenya; To establish the relationship between principals’ effective communication strategies and teacher management in public secondary schools Tharaka South sub-county, Tharaka Nithi County, Kenya and to establish the relationship between principals’ conflict resolution strategies and teacher management in public secondary schools Tharaka South sub-county, Tharaka Nithi County, Kenya. The study adopted a descriptive research design. The study was conducted in public secondary schools in Tharaka South sub-county. The sub-county has 24 public secondary schools, with a target population of 402 subjects comprising 24 principals, 377 teachers, and 1 Quality Assurance Officer. Simple random sampling was used to sample the principals and the teachers while purposive sampling was used on the Quality Assurance Officer. The researcher used Krejcie and Morgan table to realise a sample size 201 comprising of 6 principals, 194 Teachers and 1 Quality Assurance Officer. The researcher used questionnaires and interview schedules as the instruments for data collection. Piloting was carried out in Neighbouring Tharaka North sub-county, Tharaka Nithi County, Kenya among 21 respondents. The data collected was analysed using chi square and Statistical Packages for Social science (SPSS) version 26. The study analysed both qualitative and quantitative data and presented the results in tables. The findings of the study implied a significant relationship between adaptive leadership practices and management of teachers in public secondary schools in tharaka south sub-county, tharaka Nithi County, kenya. The study concluded that public secondary schools should emphasize on effective collaborative problem solving strategies through allowing teachers to have open communication channels, include them in decisionmaking process and problem solving culture and lastly team building. The findings of this study are expected to be helpful; to the Teachers Service Commission as they may get insights on how to address various inadequacies in teachers’ management among public secondary schools in Kenya. Principals and the teachers also may learn the various adaptive leadership practices and management of teachers. Scholars and researchers interested in the area of adaptive leadership practices and management will find this study a valuable reference point.
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    An efficient detection model of zero-day web application attacks based on convolution neural networks and deep auto encoders
    (Chuka University, 2024) Tuei Kevin Kirui
    The need for secure and trustworthy information systems has taken center stage and proven critical in supporting teleworking, online teaching, and research services. Artificial Intelligence (AI) is the primary driver of the 6th generation of computing, and innovations with applications of AI in computer vision, gaming, robotics, and security. Zero-day web application attacks take advantage of web application software weakness for as long as the developer is unaware and has not developed a mechanism to eliminate the weakness. Zero-day attacks leave vulnerable users grappling with data loss and have the propensity to push an organization out of business. Current zero-day attack detection methods built on signature-based or anomaly-based methods are inefficient in combating these attacks since they rely on previously detected weaknesses for signatures and a deviation from normal behavior for anomaly detection. These methods result in detection rates below 80%, meaning the propensity of Zero-day attacks going undetected is 20% or lower. The application of machine learning techniques has proven to be efficient because these techniques can continuously learn from the code as well as its execution to detect security breaches and trigger an alarm. With the need to improve these techniques, a novel classification model needs to be developed to increase the detection rate further and reduce the false alarm rate. This study applied a hybrid of two machine learning methods, Convolution Neural Networks and deep autoencoders, to develop a classification model that significantly increases the detection rate of zero-day attacks. The KDD'99 Dataset is a comprehensive repository of fully labeled intrusion detection records that was used to develop, test and validate the model. This dataset simulated real-world scenarios and assessed the model's performance under different intrusion scenarios. The Average Detection Rate, Accuracy and F1 score metrics were used to evaluate the model. The hybrid CNN-Deep Autoencoder model had a detection rate of 0.895 against 0.887 of the Fully Connected Network (FCN) with sampling and 0.885 of the pure CNN model. The accuracy and F1-score of the hybrid CNN-Deep Autoencoder were 0.973 and 0.971 respectively. The Hybrid Model of CNN and Deep Autoencoder is efficient in detecting Zero-Day Attacks making it possible for Software Developers to patch their systems sooner resulting in minimal dwell time.