http://hdl.handle.net/123456789/484 Collection of research theses and dissertations written by graduate students in the school of information technology and computing for the following programmes; Msc computer science, Msc information sysytems, PhD computer science, etc. 2026-07-17T11:03:51Z http://hdl.handle.net/123456789/602 Performance evaluation of Manet proactive and reactiverouting protocols using NS3 Nwuku, Yakubu Ernest Mobile Ad hoc network which is known as MANET is a network communication medium that is made up of mobile wireless node. The network operates as an infrastructure-less network that doesn’t require an existing network infrastructure such as routers, switches or mounted access point for network communication. MANET is a network which its setup is independent regardless of its location, but has the problem of establishing an effective network route. As wired network communication is governed by topologies, MANET in its application is governed by network routing protocols which are the basis for effective network communication. In this thesis, the routing protocols which includes DSDV, OLSR as Proactive and AOMDV as Reactive routing protocols respectively. Simulated using NS3 at 20, 40 and 60 number of nodes in a real-time scenario. Results obtained shows their performance based on the following parameter metrics: Average Throughput, Average End-to-End Delay and Average Energy Consumption. Overall, the Optimized Link State Routing (OLSR) protocol outperformed the other two routing protocols DSDV and AOMDV for the tested metrics for small networks of 20 number of nodes. Ad hoc On-demand Multipath Distance Vector (AOMDV) performs better at medium networks of 40 number of nodes. While Destination Sequence Distance Vector (DSDV) performs better at larger networks of 60 number nodes. OLSR showed better performance based on the cumulative performance on the network scenario of both small and larger networks, which serves useful information in terms of designing a network. 2020-01-01T00:00:00Z http://hdl.handle.net/123456789/601 Acceptance of Learning Management Systems: a perspective of Northern Nigerian Students. Yakubu, M Nasiru Access to the internet in developing countries is on the increase due to the declining cost of internet subscription and the availability of cheaper alternatives to internet-ready devices. This has ensured that most industries can leverage on technology advancements in order to improve their processes. In Nigeria however, there is a disparity between the way government-owned and private-owned industries use technology, while privately owned industries are funded (investment) to make profit, government-owned industries have been neglected. Higher education institutions are a good example of this disparity. Private universities have invested heavily in technological resources to provide value-for-money education; on the other hand public universities are faced with challenges resulting from inadequate funding. In higher education institutions, a very important technology is the learning management system (LMS) and prior research has shown that an LMS, when used prudently, has the potential to improve the instruction and learning process both in and out of the classroom. Till date, only a few of Nigerian universities have been able to implement a fully functional learning management system (LMS) and as a result, the present literature is devoid of research examining the factors that facilitate the acceptance of these eLearning systems by Nigerian students. Most of the studies have omitted critical factors such as instructors’ influence and course content and design quality; thus, there is no study that has been carried out in Nigeria that has comprehensively investigated the acceptance and use of LMS’. There is an abundance of studies on the acceptance of LMS’ in developed countries and these studies have identified factors that are responsible for influencing both instructors and students to use a LMS. However, this may not be applicable to developing countries where there is a significant difference in culture. This dissertation aims to fill this gap by the development and testing of a conceptual framework, which is derived from the socio-psychology domain. The framework is applied to investigate Nigerian university students’ acceptance and use of learning management systems and to compare the similarities and differences between public and private Nigerian university students’ acceptance and use of learning management systems. The universities in this study comprise of 2 (two) public and 2 (two) private universities located School of Information Technology and Computing Fall 2020 xi in northern Nigeria and a total of 1116 usable responses were received. Structural Equation Modeling (SEM) was used test the research model and its associated hypotheses while multi-group analysis method was used to test the effect of the moderators and to compare the similarities and differences between the public and private university students use of LMS’. The findings showed that students from both private and public universities attribute their use of the LMS to the perceived ease of using (PEOU) the system, facilitating conditions (FC) and the influence of others (SI) to use the system. There was no support for the relationship between course quality (CQ) and the usefulness of the LMS in both student samples. Similarly, the relationship between learning value (LV) on BI in both student samples was not supported. Only the private university students attributed the usefulness (PU) of the systems as a determinant of their intention to use the system. The multi-group analysis results showed that age gender and experience have some effect on some of the relationships. The T-test analysis for the equality of the means was also carried out to determine if there are differences between public and private university students use of the LMS. The results indicated that indeed there are disparities in the use of LMS’s in both types of institutions. The results presented by this research contribute to existing literature by validating and supporting the conceptual model used in this study, which is based on prominent technology acceptance models, and provides several prominent implications to theory and practice for individuals and educational institutions. 2020-01-01T00:00:00Z http://hdl.handle.net/123456789/593 Learning Management Systems: The Nigerian Students Experience Yakubu, Mohammed N; Kah, Muhammadou M. O.; Dasuki, Salihu. I; Quaye, Ago This study focuses on trying to understand the Nigerian student’s experience of using an eLearning application called Canvas. This study focuses on three main elements, course quality, technological aspects, and instructor influence as factors that influence Nigerian student’s experience of using Canvas. A paper-based survey was used to collect responses from 12 students participating in an Information Systems course. The results showed that all three elements contribute towards the student’s positive experience in using the system and that the students rated the instructor's influence as the most significant contributor towards their use of the application. The functionality of the system (technology aspect) was the next significant factor followed by the course content. The study contributes to the existing body of knowledge of eLearning use by students in developing countries specifically in Nigeria. The results from this study can be used by educators and administrators of Nigerian higher education institutions as a guide for policies and best practices. 2019-03-10T00:00:00Z http://hdl.handle.net/123456789/582 Data classification using various learning algorithms AHMAD BABA, Usman Dimensionality reduction provides a compact representation of an original high-dimensional data, which means the reduced data is free from any further processing and only the vital information is retained. For this reason, it is an invaluable preprocessing step before the application of many machine learning algorithms that perform poorly on high-dimensional data. In this thesis, the perceptron classification algorithm – an eager learner - is applied to three two-class datasets (Student, Weather and Ionosphere datasets). The k-Nearest Neighbors classification algorithm - a lazy learner - is also applied to the same two-class datasets. Each dataset is then reduced using fifteen different dimensionality reduction techniques. The perceptron and k-nearest neighbor classification algorithms are applied to each reduced set and the performance (evaluated using confusion matrix) of the dimensionality reduction techniques is compared on preserving the classification of a dataset by the k-nearest neighbors and perceptron classification algorithms. This investigation revealed that the dimensionality reduction techniques implemented in this thesis seem to perform much better at preserving K-Nearest Neighbor classification than they do at preserving the classification of the original datasets using the perceptron. In general, the dimensionality reduction techniques prove to be very efficient in preserving the classification of both the lazy and eager learners used for this investigation. Graduate Research Thesis submitted to the School of Graduate Studies in partial fulfillment of the requirements for the award of the degree of Master of Science in Information Systems. 2017-12-01T00:00:00Z