University of Ibadan Journals
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Internet Addiction and Peer Pressure as Determinants of Senior Secondary School Students' Academic Performance in Ogun State, Nigeria
No full textThis study examined peer influence and internet addiction as determinant of students’ academic performance in secondary schools in Ijebu-Ode Local Government Area of Ogun State, Nigeria. The study adopted the descriptive survey research design. Simple random sampling technique was used to select 560 students from eleven schools. Two questionnaires and students’ performance score was obatined from schools used for the study and analysis was carried out with the use of regression analysis at 0.05 level of significance. Results showed that peer pressure and internet addiction significantly determined senior secondary school students academic performance (F(558) = 29.013, P < 05, F(558) = 60.449, P < 05) respectively. Also, combination of peer pressure and internet addiction significantly determined senior secondary school students academic performance (F(557) = 36.842, P < 05). The study concluded that peer pressure and internet addiction are good predictors of students’ academic performance when observed relatively and combined. It was recommended that parents should pay attention to how their children uses the internet and possibly restrict them on site to visit
Navigating Through Change Implementation Barriers in Institution of Learning
No full textGlobalization, fiscal and budgetary constraints, upsurge enrolment, international competition for ranking, advent of advance Information, Communication and Technology (ICT), pressure for accountability from the government and public, request for job-ready university products are some of new waves of change calling for different modifications in our citadels of learning at all levels. Leaders therein need to brace up to embrace the new norms and adjust accordingly. They need to accommodate international dimensions to compete in the global world, modify their curriculum to entail soft skills, provide open learning, advance online learning and artificial intelligence, review institution mission, restructure administration for quality assurance, create encompassing activities in order to significantly contribute to 2030 agenda of Sustainable Development Goals (SDGs). Hence, change implementation is imperative. However, it is not an easy task. It always faces resistance and other challenges which leaders need to carefully and systemically bypass. This paper discussed various dimensions of change initiatives, causes of resistance and how to successfully navigate through change implementation hurdles. The discussion of the paper will help leaders in different institutions of learning to be battle ready for any type of change necessary to be implemented and able to successfully skip through the change process. It is recommended that leaders of various institutions of learning should embrace the new norms and adjust accordingly, acclimatize to the various dimensions of change initiatives, causes of resistance and learn how to successfully navigate through change implementation
Gender-Related Issues and Labour Force Status of Federal University Graduates in Southwestern Nigeria
No full textGender is a major demographic factor that determines who gets a place in the labour market. However, in Nigeria, the number of women in formal employment does not reflect the population ratio of women to men in the country. Women are mostly found in the informal sector working as sub-contractors, home-based businesses, and dependent employees although women with higher educational certificates tend to earn more, hence the need for this study. The Quant+qual mixed methods design was adopted, while multi-stage sampling technique was used to select two thousand graduates. Thirty human resource managers (HRMs) were interviewed. Quantitative data were analysed using descriptive statistics, while qualitative data were content analysed. The findings of the study revealed that gender influenced the labour force status of respondents in Southwestern Nigeria while the female gender was mostly into self-employment. This study recommended that universities should provide more females with relevant skills and information required by different economic sectors
Comparative Analysis of Machine Learning Algorithms for the Classification of Twitter Bots
Get PDFSocial media platforms have become risky for actual users due to the rise in the number of bots. The security mechanisms put in place to help identify and categorize bots accounts from legitimate human accounts have significant drawbacks, such as the misclassification of accounts because of behavioral change. In general, studies on Twitter bots identification demonstrate that bots can be useful while also having a negative impact on users by broadcasting misleading news, spamming, or posing as a phony follower to boost an account's popularity. This study employed Logistic Regression, Catboost, and Random Forest algorithms to develop Twitter bots classification systems, capable of distinguishing between useful and harmful bots accounts in order to limit their impact on users and the Twitter community. The feasibility of the algorithms was tested on Twitter spam bots dataset gotten from Kaggle, containing eight(8) features, which were reduced to two (2) using decision tree. The selected features were further utilized to develop bots classification systems. Comparative analysis of the results showed that Random forest classifier recorded best performance when evaluated on training set, while the Logistic recorded highest performance in terms of accuracy, precision, and F1 Score achieving 83%, 78%, and 81%, respectively when evaluated on test set. The classification systems can help identify and mitigate the impact of harmful bots on Twitter, such as those used for spamming or disseminating fake news. The study has demonstrated the effectiveness of machine learning algorithms in classifying Twitter bots and provided a potential solution for improving online social media platforms
IoT-Based Gas and Smoke Detection System using Blynk application with Automatic SMS and Alarm Notifications
Get PDFThe Internet of Things (IoT) has revolutionized safety and security by providing innovative solutions to critical challenges. Gas leakage, a dangerous chemical from petroleum, can cause health issues and disrupt workspaces. To prevent such accidents and maintain a clean air environment, a monitoring gas leakage detector system is proposed. The system uses a NodeMCU ESP8266 Wi-Fi microcontroller and a combustible gas sensor (MQ-2) to detect the presence of propane, butane, and Liquefied Petroleum Gas (LPG). The sensor's voltage output determines gas concentration, and the ESP8266 sends data to the blynk application. This system aims to maintain a clean and safe workspace. The IoT-based gas and smoke detection system uses sensors and a mobile app to monitor premises remotely. It sends SMS alerts to users and authorities in case of incidents and activates audible alarms to the users. This system enhances security by reducing risks and reducing the need for manual monitoring, making it a significant step towards safer environments. 
A Usability Review of Undergraduate Student Web Portals at University of Ibadan
Get PDFTertiary institutions have deployed web portals for undergraduate students as a crowd management tool and fraud reduction technique. Tertiary institutions offer student web portals for a wide variety of self-service features such as admission, registration, payment, e-mail, transcripts, repository, counselling and so on. University of Ibadan (UI) is a tertiary institution located in the southwestern region of Nigeria. The institution has student web portals used for registration, admission purposes amongst others. The University of Ibadan is a complex organisation with governance aided by the Committee System and technology such as web portals. This paper examined the usability of undergraduate student web portals currently in use at University of Ibadan,Nigeria. A modified University Portal Usability Assessment Index was used on a digital platform. Six web portals forundergraduate students was identified. The results indicate that students require consolidation of the various portals into a single portal and improvement on support for portal users. The study identified the need for a mobile app to be developed since most users access the portal via mobile devices
Design of a Variable-length Accented Character-based CAPTCHA System
Get PDFCompletely Automated Public Turing test to Tell Humans and Computers Apart (CAPTCHA) is aimed at distinguishing humans from computers by using text, images, audio, or video. Text-based CAPTCHAs, are the most common but face vulnerabilities due to their limited use of latin characters. This study enhanced the design of the NaijaCAPTCHA by generating variable-length accented character-based CAPTCHA codes, utilising latin and accented characters to bolster online transaction security. The design was implemented using Javascript, PHP, HTML, and CSS. The enhanced NaijaCAPTCHA comprised of four modules: CAPTCHA generator, obfuscator, display unit, and database. The generator employed the Gimpy algorithm to create codes of varying lengths (4 to 7 characters) with at least two accented characters. The obfuscator manipulated the code's appearance through color, text distortion, background noise, and skewing. User presentation and authentication occurred in the display unit, with code correctness verified against the obfuscated value. Thirty CAPTCHA categories were generated from the combination of background and text modification. The enhanced NaijaCAPTCHA system presents a formidable challenge to bots, suggesting its potential adoption for government websites and transactional purposes. 
Efficient Tuberculosis Detection Using Chest X-ray Images with Deep Learning Algorithms
Get PDFTuberculosis is a threat to the existence of the human race due to its substantial mortality rate and it has become a significant public health concern, which if detected at an early stage could reduce the death rate globally. Harnessing the potential of machine learning to combat the low detection rate of tuberculosis detection by traditional methods and promote a faster and more accurate diagnosis of the disease. An online Dataset comprising 11,200 Chest X-ray (CXR) images of different categories of patients that are healthy, Sick but not infected, and those infected with Tuberculosis with their corresponding bounding box annotations were used for this research, and feature engineering was carried out on the dataset for effective data cleaning, Image resizing, normalization, and augmentation to increase the quality of data during data segmentation. The dataset was divided into training, validation, and testing sets using the RestNet50 model which demonstrated a good performance in classification, achieving impressive precision, and recall of 98%, and 96% respectively, and YOLOv8 was also used with 68% precision, 65% recall, and 68% mean average precision respectively which showed that the model needs improvement to further accurately detect regions infected with tuberculosis
The Influence of Robotics-Enhanced Instructional Strategy on Senior Secondary School Students’ Achievement in Physics in Abeokuta South Metropolis
No full textThis study investigated the influence of educational robotics as an instructional strategy on the academic achievement of secondary school students in physics within Abeokuta South Metropolis, Nigeria. Despite the recognized importance of physics education to technological advancement, students’ performance in physics examinations had been consistently poor. The study adopted a quasi-experimental design and purposive sampling technique, a Physics Achievement Test (PAT) was administered as a pretest and posttest to 120 Senior Secondary School 2 students from two different schools (60 from each school) with treatment groups exposed to robotics-enhanced instruction using the mBot. Data analysis employed mean, standard deviations, and Analysis of Covariance (ANCOVA) to test the null hypotheses. The findings revealed that students taught with mBot performed better than those without it. Gender differences in academic achievement were not significant. The study underscored the effectiveness of educational robots in enhancing physics education and called for its integration into the curriculum, teacher training, and the promotion of gender equality in Science Technology Engineering and Mathematics (STEM) education. Implementing these recommendations could contribute to improved academic outcomes and foster technological advancement in Nigeria
Perceived Influence of Principals’ Leadership Styles on Teachers’ Job Performance in Public Secondary Schools in Benue State, Nigeria
No full textThe objective of this study was to: examine the perceived influence of principals’ autocratic, democratic, laissez-faire, transactional and transformational principals’ leadership styles on teachers’ job performance in public secondary schools in Benue State. Five research questions were used. A survey research design was adopted for the study. Sample size of 371 was derived from the population of 5,190 comprising principals and teachers in Benue State. Self-structured questionnaire was administered using random sampling technique. Descriptive statistics was used to answer the research questions, where mean values greater than the critical mean of 2.50 on a 4-point likert scale indicated high level of influence for the 31-items used. Results of the study showed that; there was high level of perceived influence of principals’ leadership style on teachers’ job performance in Benue State. Therefore, the adoption of the autocratic, democratic, laissez-faire, transactional and transformational leadership styles by principals in Benue State was recommended to improve teachers’ job performance