University of Ibadan Journals
Not a member yet
794 research outputs found
Sort by
Predicting the Trend of Dollar/Naira Exchange Rate Using Regression Model and Support Vector Machine
Get PDFThe stock market is a network that provides a platform for nearly all major economic transactions in the world at a dynamic rate referred to as the stock worth that is predicated on market equilibrium. Predicting this stock value offers huge arbitrage profit opportunities that are the enormous motivation for analysis during this space. Knowledge of a stock value beforehand by even a fraction of a second can result in high profits, machine learning technique has proven to be effective in stock market prediction, especially in the stock exchange-traded fund and index exchange-traded fund, but little effort has been extended to the prediction of the currency exchange-traded fund using the linear regression and support vector machine, In this study, the trend of the exchange rate of DOL/NGN was predicted from the exchange rate value generated using the linear regression and support vector Machine. The accuracy of the prediction from the Linear Regression model and support vector machine was analyzed using performance metrics
Assessing the Effects of Academic and Work Experience Backgrounds on Software Defect Detection Effectiveness
Get PDFInspection of various software artefacts increases the quality of the end product – the software. The question yet unanswered is “Does effectiveness of software inspection depend largely on the academic and work experience backgrounds of individual inspectors involved?” To address this issue, a medium-scale controlled code inspection experiment with 28 final year students from selected Departments in the Faculty of Science and 10 professionals was conducted at University of Ibadan. The experiment was designed to find out the relationship (if exist) between inspectors’ academic and work experience backgrounds and their defect detection effectiveness during an industrial code inspection. The results of the study showed that those with computer related background found significantly more defects than those with non computer related background. It is also found out that prior industrial code writing and inspection experiences significantly impact the effectiveness of an inspector. Finally, professionals with prior code inspection experience found significantly more defects than their student counterparts
SENIOR SECONDARY SCHOOL CURRICULUM: ISSUES AND STRATEGIES FOR EFFECTIVE IMPLEMENTATION
Get PDFCurriculum and education have been described as Siamese twins. The importance of curriculum in any educational enterprise cannot be overemphasized. The Nigerian educational sector has been experiencing various challenges in terms of the output of its graduates. This is as a result of the fact that students are fallen short of the standards in skills acquisition and understanding needed to participate effectively in the economic, scientific and political environment later in life, despite government interventions in terms of curriculum development and review. This paper, therefore, attempted to explore reforms in implementation processes of the senior secondary schools curriculum. It started with the concept of curriculum, curriculum implementation, issues and strategies for enhancing effective implementation of senior secondary schools curriculum in Nigeria. It was concluded that funding of secondary education should not be the sole responsibility of the government but a synergy of efforts between the government and other stakeholders in the education sector to achieve effective implementation of the policy
ATTITUDINAL DISPOSITION OF TEACHERS AND SCHOOL ADMINISTRATORS TO CORPORATE SOCIAL RESPONSIBILITY (CSR) AMONG PRIVATE SECONDARY SCHOOLS IN LAGOS STATE, NIGERIA
Get PDFThe study investigated attitudinal disposition of teachers and school administrators to corporate social responsibility among private secondary schools in Lagos State. The study has two research questions and adopted descriptive survey design. The population of the study comprised all teachers and school administrators in government approved private secondary schools in Educational District IV, Lagos State. Purposive and simple random sampling technique was used to arrive at 330 samples for the study. Validated questionnaire (Attitude towards CSR) was used to obtain data from the respondents. The questionnaire was administered under good supervision, while descriptive statistics (mean and simple percentages) and independent ttest was used to analyse data obtained in the study at 0.05 level of significance. Finding of the study showed that teachers has positive attitudinal disposition to CSR and there was significant difference in the attitudinal disposition of teachers and school administrators (t=.2.434, p < 0.05). The paper therefore concluded that teachers attitude towards CSR is important, also the school administrators should encourage teachers to show more positive attitude to CSR, while school administrators should not only focus on profit making alone. Based on the findings and conclusion therefore, the study recommended that private schools should endeavour to be socially responsible to win the goodwill of their stakeholders
SCHOOL-BASED MANAGEMENT COMMITTEE RESOURCE MOBILIZATION, AVAILABILITY AND UTILIZATION ON PUBLIC PRIMARY SCHOOL PERFORMANCE IN EKITI STATE NIGERIA: ARTIFICIAL INTELLIGENCE NEURAL NETWORK APPROACH
Get PDFSchool performance involves with the efficiency and effectiveness in the service delivery that a school as an organisation rendered to her potential client satisfactorily. This is often created an issue concerned to the stakeholders such as government, parents and the employer of labour especially the public primary schools’ performance. For school performance to be improved upon, relevant resources must be made available at the disposal of the school community that is the teachers and pupil’s use. In the view of this, this study examined School-Based Management Committee resource mobilization, availability and utilization on public primary schools’ performance in Ekiti State: Artificial Neural Network (ANN) approach. One research question was raised and two research instruments were designed to elicit relevant information from the study participants with the titled “Observation Checklist: Resource Mobilization, Availability and Utilization” with the reliability co-efficient of 0.86 Cronbach Alpha and “School Performance Questionnaire” (SPQ) with the reliability coefficient of 0.89 Cronbach Alpha. The study adopted multi-stage sampling technique which embraces purposive sampling methods, simple random sampling methods and stratified sampling methods. Population sampled for the study include: 90 headteachers, 90 SBMC Chairmen and 1020 teachers in 12 Local Government Education Authorities (LGEAs) in Ekiti State Universal Basic Education Board. Data generated from the field for the study was analyzed using the Artificial Neural Network (ANN) which is a statistical package that is more reliable and that work like human brain at 0.05 level of significance. The results findings indicated R2 of 0.85; 0.68; 0.91; 0.84; 0.75; and 0.72 based on the key performance indicators to the study, and arising from the result findings, it is therefore recommended among others that: government at the various levels of governance should step up the awareness campaign of SBMC by sensitizing the citizenry on the significant of the organization in the school system. The SBMC members should be trained and re-trained from time to time on their responsibilities in the school administration in order to avert conflict of interest between them and the PTA executives operating in schools as partners in progress
COMMUNITY PARTICIPATION IN CONFLICT RESOLUTION IN THE ADMINISTRATION OF PUBLIC SECONDARY SCHOOLS IN EKITI STATE
Get PDFThe study investigated the influence of community participation in conflict resolution in the administration of public secondary schools in Ekiti State. Two research questions and two hypotheses guided the study. The study adopted the descriptive survey research design. The population of the study was 4,536 while the sample was 368 respondents. Multi-stage sampling technique was used to determine the sample size of 368 respondents. The instrument for data collection was self-structured questionnaire titled “Community Participation in Conflict Resolution Questionnaire (CPCRAQ)”. Three experts validated the instrument used for the study from the Department of Educational Management, Ekiti State University, Ado-Ekiti. The instrument was trial tested on 30 respondents in Ijero L.G.A of Ekiti State which was not part of the area used for the study. The data collected were analyzed using Cronbach Alpha to establish the reliability estimate and the overall reliability coefficient of 0.77 was obtained. Mean and standard deviation were used to answer the research questions that guided the study, while Analysis of Variance (ANOVA) was used to test the null hypotheses formulated for the study at 0.05 level of significance. The major findings of the study were that communities to a great extent participate in conflict resolution in the administration of public secondary schools in Ekiti State. Findings also revealed that there was no statistically significant difference in the mean ratings of the respondents on the influence of community participation in conflict resolution in the administration of public secondary schools in Ekiti State. Based on the findings of the study, it was recommended that the principals as the managers of secondary school should as a matter of importance be able to identify nature or causes of conflicts in their schools before it affect school as a whole and that the school authority should identify resources persons within the community and reach out to them when the need arises
Predicting Cloud Computing Technology Adoption in Higher Education using Technology Acceptance Model (TAM): A Case Study of Ogun State, Nigeria
Get PDFAbass, Olalere. A., Alaba, Olumuyiwa. B. and Samuel, Babafemi. O.
Department of Computer Science, Tai Solarin College of Education, Omu-Ijebu, Ogun State.
Department of Computer Science, Tai Solarin University of Education, Ijagun, Ogun State.
[email protected]; [email protected]; [email protected]
Abstract Cloud computing (CC) is a nascent paradigm repositioning education system due to global usage of internet-enabled devices with high bandwidth and enhanced mobility requirements of the users. However, some stakeholders in the education system still feel reluctant to adopting CC services due to varying reasons. This paper explores the factors that distance learning system operators consider as important for the adoption and actual usage of CC services in Ogun State, Nigeria. A modified model based on Technology Acceptance Model (TAM) variables was developed. There are seven hypotheses formulated for testing. The researchers administered 389 TAM-based questionnaires to computer literate students in the institutions to obtain datasets. Multiple regression statistics was applied to analyse and test the seven hypotheses using IBM SPSS version 23. Findings revealed that perceived usefulness, ease of use, attitude to use and access cost variables are the most significant predictors of CC adoption. The findings of the study will benefit the management of tertiary institutions towards formulating policies that would promote mass education programmes like open distance learning (ODL) in Ogun State, Nigeria through CC adoptio
A Review of e-Commerce Adoption in Nigeria based on Security and Trust
Get PDFAbstract
Electronic commerce (EC) is an Internet-based technology that has gained wide acceptance by business operators and its usage has drastically increased over the years due to the transformation enabled by information technology. Despite the progress so far made in Information Technology (IT) including the e-Commerce, several factors still affect the services provided by e-commerce vendors that include security, privacy, trusts and perceived risks. This paper, therefore, investigated the adoption of e-commerce based on security and trust in Nigeria using a comprehensive review of literature in the related areas, and the methodology adopted was based on secondary data. The study also proposed theoretical models targeted at investigating the relationship between security issues, privacy and how they affect customers’ behaviour and the trust degree in e-commerce. Findings reveal that improved security and trust are the bases of increase in the adoption threshold and the use of ecommerce in developing countries. The study, therefore, recommends that e-commerce platform developers should endeavour to build websites that are user-friendly and devoid of ambiguity as well as incorporate dynamic security systems to safeguard the personal information of the customers. Also, e-commerce platform developers need to interact frequently with consumers (or merchants) to establish a strong relationship that would engender trust
Phrased-based Machine Translation
No full textAbstract
Over the years, data mining has been successfully adopted to transform the business world by implementing different models for evaluating business performance. Analyzing and evaluating large volume of dataset by these data mining models keeps its application growing wide. Several data generated from student academic results and bio data calls for a need to create knowledge out of the data set. Students' academic performance evaluation is a necessity and incredibly challenging, and thus, is intended for identifying and extracting new and potentially valuable and actionable knowledge from the data. It is a complex research undertaking to identify and indicate the issues harming students’ academic performance. Performance prediction models can be built by applying machine learning tools to enrolment data. This paper presents five Machine Learning models- K-Nearest Neighbour Classifier, Random Forest, Gaussian Naïve Baye’s Classifier, Decision Tree, and Support Vector Classifier- for predicting students’ continuous performance and graduating cumulative Grade Point Average. Each model is applied to data set on the enrolment data and examination results for three different academic sessions ranging from the first year to the graduating year. The comparative analysis of the performance of each of these models is carried out based on accuracy of prediction
A Comparative Study of Age Estimation Using Edge Detection and Regression Algorithm
Get PDFAge Prediction has received a lot of attention over the years because of its numerous applications ranging fromanthropology to archaeology and even forensic science. Even though there have been many methodologiesdeveloped for this purpose, it is still a problem owing to the high variability in physiological age indicators. Thisstudy compares different combinations of Edge Detection and Regression algorithms to determine the bestpossible way to predict the apparent age of an individual using the Histogram of Oriented gradients to extractfeatures from the Detected Edges. The FGNET Dataset which contains over 1000 images of people of ages rangingfrom 0 to 70 years old with each individual represented at least 4 different ages was used. The Edge Detectionalgorithms used were Canny Edge and Sobel Filter combined with the Support Vector Regression and K-NearestNeighbour Regression Algorithms. The performance of the Canny edge detection algorithm and the Sobel filterwhen combined with the HOG feature extraction algorithm were compared. It was observed that the combinationof the Canny Edge Detection Algorithm and the Support Vector Regression Algorithm gave the best PredictiveAccurac