104 research outputs found
Statistical Analysis on Students’ Performance
Full text linkThis research uses Cohen’s Kappa to examine the performance of students in the Faculty of Science, University of Ilorin. The data was collected from eight departments in the faculty and it covers the performance of students measured by their Grade Point Average (GPA) and Cumulative Grade Point Average (CGPA) in both their first and final year between 2000-2006 academic sessions. It is of interest to determine the proportion of students that improved on their performance, dropped from the class of grade point which they started with and those that maintained their performance using psychometrics approach. Also, the strength of agreement that exist between the first and the final year was examined
Unified Generalizations of Hardy-Type Inequalities Through the Nabla Framework on Time Scales
No full textThis research investigates innovative extensions of Hardy-type inequalities through the use of nabla Hölder’s and nabla Jensen’s inequalities, combined with the nabla chain rule and the characteristics of convex and submultiplicative functions. We extend these inequalities within a cohesive framework that integrates elements of both continuous and discrete calculus. Furthermore, our study revisits specific integral inequalities from the existing literature, showcasing the wide-ranging relevance of our results
Data analytics on performance of computing students
No full textThis study was conducted to determine the relationship between computing students' initial and final academic performance to support decision making in higher education institutions. The data used in this research contains the initial GPA and CGPA of 710 computing students for a period of 5 years. Test of normality for the final graduating results and linear regression models were fitted to the data to predict the overall performance based on the initial result. This study revealed that there are strong linear relationships between the GPAs and CGPAs of computing students over the period of this study. The contribution of this work is that the result enables the student and the teacher to understand the trend of students' academic performance for the purpose of decisionmaking. Keeping track of the performance of the students help provide support whenever is needed. This results aimed to decrease student dropout by means of facilitating student to predict their probability of success in computing courses after enrollment. In addition, teachers will be able to boost student performance in their courses as a result of enhanced determination of student's abilities to learn the course and finetuning teaching approaches and techniques
Bayesian inference for the parameters of the generalized logistic distribution under a combined framework of generalized type-I and type-II hybrid censoring schemes with application to physical data
No full textThis study focuses on the Bayesian inference of parameters for the generalized logistic distribution, utilizing a combined framework of generalized type-I and type-II hybrid censoring schemes. The research addresses limitations in existing censoring methods by proposing a flexible model that enhances practical applicability in reliability and life-testing studies. Key objectives include the development of maximum likelihood estimators and asymptotic confidence intervals, alongside Bayesian estimation techniques using Markov chain Monte Carlo methods. These advancements facilitate the computation of credible intervals under various loss functions, thereby improving estimation efficiency. The paper also includes a comprehensive analysis of real-world datasets and simulation experiments to validate the proposed methodologies. A comparative evaluation of different estimators highlights the superiority of the combined framework of generalized type-I and type-II hybrid censoring schemes, providing valuable insights into the reliability and performance of the estimators. Overall, this research contributes significantly to the understanding and application of the generalized logistic distribution, offering practical tools for researchers and practitioners in the field of reliability engineering
University Student’s Academic Performance : An Approach of Tau Statistic
Full text linkAbstractThe poor performance of tertiary graduates in Nigeria has been the subject of speculation for stakeholders in the education sector. In pursuance of Academic excellence, Nigeria’s target is to become one of the top 20 economies. Performance is the ability of a student to complete a task. The task completion results could be positive or negative. Academic performance in private universities is undulating between first and third classes. These results are in public universities. If the result is positive, it indicates that the student performs brilliantly or excellently, but on the other hand, if it is negative, it indicates woeful performance. Student performance is an outcome of a rigorous evaluation through examination or other assessment methods. Performance criteria start from day one on campus, and it extends and accumulates to the end of the student’s study. The study uses 1841 students’ academic records from seven Engineering departments from the School of Engineering, Covenant University, Nigeria. This study examines the relationship between the first year and final year results and the reliability between first year results and final year results. The methodology adopted in this study is a quantitative technique. The analysis for the study carried out with IBM SPSS version 27 using Pearson correlation and Tau statistic. The Pearson correlation coefficient shows a strong positive correlation between the students of the first year and final year results, and it shows a significant linear relationship between students’ first and final year results from the seven departments. This work will serve as a valuable source of advice to stakeholders in the education sector, inside and outside the university system, to enhance students’ academic performance in the University system.Abstract
The poor performance of tertiary graduates in Nigeria has been the subject of speculation for stakeholders in the education sector. In pursuance of Academic excellence, Nigeria’s target is to become one of the top 20 economies. Performance is the ability of a student to complete a task. The task completion results could be positive or negative. Academic performance in private universities is undulating between first and third classes. These results are in public universities. If the result is positive, it indicates that the student performs brilliantly or excellently, but on the other hand, if it is negative, it indicates woeful performance. Student performance is an outcome of a rigorous evaluation through examination or other assessment methods. Performance criteria start from day one on campus, and it extends and accumulates to the end of the student’s study. The study uses 1841 students’ academic records from seven Engineering departments from the School of Engineering, Covenant University, Nigeria. This study examines the relationship between the first year and final year results and the reliability between first year results and final year results. The methodology adopted in this study is a quantitative technique. The analysis for the study carried out with IBM SPSS version 27 using Pearson correlation and Tau statistic. The Pearson correlation coefficient shows a strong positive correlation between the students of the first year and final year results, and it shows a significant linear relationship between students’ first and final year results from the seven departments. This work will serve as a valuable source of advice to stakeholders in the education sector, inside and outside the university system, to enhance students’ academic performance in the University system
The Strength of Agreement of Students' Academic Performances as A Counseling Guide for The University Prospective Admission Seekers
No full textThis research examines the strength of agreement of students' academic performances for their first and graduating year in the University using Cohen's kappa. Academic records of 710 students which consist of students Grade Point Average (GPA) and Cumulative Grade Point Average (CGPA) for their first and graduating year. This paper is to examine the final academic performances of students in the University based on specific information regarding their academic performances during their first yearat the University. This study reveals that a strong agreement exists between the students' first and graduating year academic performance in their result. This work will serve as a useful counseling guide to prospective admission seekers and all stakeholders at enhancing students' academic performances in the University system. This study is divided into five sections: introduction, literature, methodology, discussion while the study limitation and future study forms the part of the conclusion
Trend of Social Media News : A Viewpoint of COVID-19 Tweets Using Natural Language Processing
Full text linkAbstractThe meteoric rise of social media news during the ongoing COVID-19 is worthy of advanced research. Freedom of speech in many parts of the world, especially the developed countries and liberty of socialization, calls for noteworthy information sharing during the panic pandemic. However, as a communication intervention during crises in the past, social media use is remarkable; the Tweets generated via Twitter during the ongoing COVID-19 is incomparable with the former records. This study examines social media news trends and compares the Tweets on COVID-19 as a corpus from Twitter. By deploying Natural Language Processing (NLP) methods on tweets, we were able to extract and quantify the similarities between some tweets over time, which means that some people say the same thing about the pandemic while other Twitter users view it differently. The tools we used are Spacy, Networkx, WordCloud, and Re. This study contributes to the social media literature by understanding the similarity and divergence of COVID-19 tweets of the public and health agencies such as the World Health Organization (WHO). The study also sheds more light on the COVID-19 sparse and densely text network and their implications for the policymakers. The study explained the limitations and proposed future studies.Abstract
The meteoric rise of social media news during the ongoing COVID-19 is worthy of advanced research. Freedom of speech in many parts of the world, especially the developed countries and liberty of socialization, calls for noteworthy information sharing during the panic pandemic. However, as a communication intervention during crises in the past, social media use is remarkable; the Tweets generated via Twitter during the ongoing COVID-19 is incomparable with the former records. This study examines social media news trends and compares the Tweets on COVID-19 as a corpus from Twitter. By deploying Natural Language Processing (NLP) methods on tweets, we were able to extract and quantify the similarities between some tweets over time, which means that some people say the same thing about the pandemic while other Twitter users view it differently. The tools we used are Spacy, Networkx, WordCloud, and Re. This study contributes to the social media literature by understanding the similarity and divergence of COVID-19 tweets of the public and health agencies such as the World Health Organization (WHO). The study also sheds more light on the COVID-19 sparse and densely text network and their implications for the policymakers. The study explained the limitations and proposed future studies
Investigating Machine Learning Methods for Tuberculosis Risk Factors Prediction - A Comparative Analysis and Evaluation
No full textTuberculosis (TB) is a killer disease, and its root can be traced to Mycobacterium tuberculosis. As the world population increases, the burden of tuberculosis is growing along. Low-and-middle-income nations are not exempted from the tuberculosis crisis. Due to a shortage of medical supplies, tuberculosis bacteria have become a huge public health concern. This study reviewed recent literature from 2015 to 2020 to critically examine what earlier researchers have done about TB burden and treatment. The data used were based on the hospital's medical department's record and used a machine-learning algorithm to predict and determine the risk factors associated with the disease. Furthermore, it developed five predictive models to offer the medical managers a valid alternative to the manual estimation of TB patients' status as cured or not cured. The overall classification showed that all the classification methods performed well for classifying the TB treatment outcome (ranging between 67.5% and 73.4%). Our findings showed that MLP (testing) is the best model to predict TB patients' treatment outcomes. Age and length of stay were identified as significant risk factors for TB patients in this study. This study explains the study's limitation, contributions, managerial implications, and suggest future work
On the Application of Linear Programming on a Transportation Problem
No full textThis research demonstrates the application of Linear programming on a transportation problem to products of Lubcon limited. Data were collected as extracts from the records of the company on the five (5) products and six (6) districts offices. Information regarding the supply capacity and demand requirements were also given. We have been able to formulate a linear programming for the transportation problem for the products of Lubcon limited. We obtained the minimum transportation cost of #183,522,300 with some cartons of products to be transported to their destinations in order to attain a minimum cost which is the goal of the company
Data analytics : an exploration of quality control to determine students' academic performance
No full textQuality control and improvement is a crucial process development of any institution that craves growth. One part of the SPC approach is to aid the constant improvement of performance by further reducing unexplained variability. Another aspect of Statistical Process Control (SPC) is that planned and unplanned changes signaled as fast as considering the natural process variability. This paper aimed to determine whether students' performance is significantly distributed according to academic patterns using the quality control procedure. This study found that one of the notable Nigerian Private University student academic performances drawn from three engineering departments based on the mean chart is in control and out of control, indicating excellent, intermediate, and lower results. The study also shows upper, average, and lower results with a close margin. This insight is an interdepartmental issue. The school managers need to formulate a holistic policy that will improve the existing academic performance to move the outlier students from worst to better and from better to best
- …
