Information Communication and Technology (ICT) utilization has become a backbone of e-government implementation. Six components of information system (hardware, software, people, data, process and network) are combined to deliver information from government to their citizen as part of public services. However, there is an interoperability challenge on e-government implementation related to information system. Organizations in Kenya have automated processes and digitize services and information using various information systems e.g. IFMIS systems which acts as a financial management of government departments. These systems due to different vendors and their use of different storage types, data formats, languages and middleware platform have become diverse, thus the issue of egovernment information system heterogeneity and interoperability. This has led to the need for organizations to share information and services through interoperability platforms. Currently most e-government platforms are independent thus result to lack of integration, inconsistency of meaningful data, redundancy of effort and lack of integration. The main aim of this Study was to develop an interoperability framework for e-government information system which will improve efficiency and effectiveness of government services through accurate information among various information systems while the specific objectives were to identify the factors that affected e-government information system interoperability, determine the critical factors that influenced e-government information system interoperability. The Research design used was exploratory study of both national and county governments in Kenya. It focused on the way public organizations managed identity-related data and the sharing of such data, either with other public agencies or with private organizations. The study adopted a mixed methods approach where both quantitative and qualitative data was used. Quantitative data was analyzed descriptively based on the information from the questionnaire and based on the research questions. Factor analysis was conducted on the two sets of data. The target population was users of egovernment information systems in county government and government ministries in Kenya. The study sample was drawn from two county governments and two huduma centres in Kenya. Descriptive statistical analysis and principal component analysis was used. The findings of this study will be essential to both the government and county governments in improving efficiency and effectiveness of government services and also form a basis for future development of interoperability of e-government information systems. The framework was successfully accepted by the experts who were interviewed by the researcher. The framework recombines interoperability framework of egovernment in guiding decision makers to better manage issues related to e-government information system interoperability.

Practical activities are extremely important in teaching sciences as they aid the students in comprehending scientific concepts through participatory learning. However, most Kenyan public schools lack well equipped laboratories. Additionally, the diminishing resources resulting from post-COVID effects offer no beam of hope. Disruption from COVID also poses critical challenges of handling physical devices in times of such pandemics. To address this, the Integration of Virtual Labs to Enhance STEM Education for Girls (IVLESTEG) project was conceptualized to enhance girl’s access to Science, Technology, Engineering and Mathematic (STEM) subjects in Kenyan secondary schools. The aim of this research study was to critically appraise the current technology models in relation  to girls’ access to STEM education with the overall objective of exploring the potential of e-learning in promoting participation of female students in STEM subjects in Kenya.  Upon development and implementation of learning in the V-labs, quasi experiments were conducted to determine the effectiveness of use of V-Labs in enhancing the participation of female students in STEM disciplines in secondary schools. Schools were  randomly chosen and classified as either experimental or control sites. This method allowed  for comparison of performance in STEM subjects of the female learners who were exposed to learning in the V-labs and those not. The findings will contribute to the development  of a framework for  appraising models for ICT use in STEM teaching and learning processes for girls that can inform practice, policy and research.

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Over time, the adoption of ERP systems has been wide across many small, medium, and large organizations. An ERP system is supposed to inform the strategic decision making of the organization; therefore, the information drawn from the ERP system is as important as the data stored in it. Poor data quality affects the quality information in it. Data mining is used to discover trends and patterns of an organization. This chapter looks into the way of integrating these data mining into an ERP system. This is conceptualized in three crucial views namely the outer, inner, and the knowledge discovery view. The outer view comprises of the collection of various entry points, the inner view contains the data repository, and the knowledge discovery view offers the data mining component. Since the focus is data mining, the two strategies of supervised and unsupervised are discussed. The chapter then concludes by presenting the probable problems within which each of these two strategies (classification and clustering) can be put into place within the mining process of an ERP system.

Breast cancer is a top killer disease for women globally. The long term survival rate of women can be improved through early and effective screening of breast cancer cells. Currently, a mammogram is the recommended tool for breast cancer screening since it can identify breast cancer cells several years before physical signs appear and it is cost effective. This paper analyzes mammographic detection of breast cancer by providing an explanation on development and classification of Breast Cancer, Image representation models for breast tumor, mammography technologies, a discussion on various mammographic signs of breast cancer, breast cancer feature extraction techniques, popular breast cancer classification techniques, comparative analysis of existing mammogram breast cancer databases, and a review of mammographic breast cancer detection studies are presented. Finally, a highlight on future work is given.