A Comparative Study on Engineering Student's Performance between the Single-Gender Classroom and Co-educational Classroom: A Case Study of Islamic University of Technology

The purpose of this research was to conduct a comparative study to find out which setting performs better between students in the Co-educational Instruction setting and Students in the Single-gender Instruction set. In this research process, the researchers compared the performance of students who receive instruction in a single-gender classroom with the performance of other students who receive instruction in a co-educational classroom. The study population was 756 students of single and mixed-gender streams, classified into two groups (A & B). Out of this, one single-gender male class of 268 students (group A) and one COED class of 488 students (group B) were sampled from the Islamic University of Technology (IUT) in Bangladesh. The research adopted a quasi-experimental research design. The instruments used for data collection were the summative assessment of both groups' first and second-semester results that serve as test instruments. Frequency counts and the Arithmetic means were used for descriptive analysis. The independent sample t-test was used to test the hypotheses. Social learning theory emphasizes the importance of biological, social, and cultural impacts on human behavioral development and learning, especially on gender and genders specific traits and roles. Based on the analyses and interpretation of the data, the researcher found that male students perform better academically in single-gender classes, contrary to their academic performance when mixed with females in the same classes. Thus, single-gender instruction could be a more favorable environment for male students than a co-educational instruction environment.

Efficient Machine Learning-Based Model for Cerebrovascular Disease Prediction with Nigerian Dataset

Cerebrovascular accidents (CVA) or stroke has been a global phenomenon that causes disability and deaths of people worldwide, particularly in the middle- and low-income countries. It has been reported that more than 100,000 cases are recorded every year in Nigeria. Moreover, several deaths were reported globally by the World Health Organization (WHO). Diagnostic tools, preventive measures, and medical experts are insufficient and contribute to the escalation of the disease worldwide. Several predictive models have been proposed by scholars but have been inadequate due to variability in the risk factors, race, and geographical variations. This paper compared six machine learning-based models with three feature selection algorithms on a Nigerian dataset containing 103 instances with 22 features. We trained and evaluated the NB, SVM, LR, MLP, J-48, and RF with CBFS, CAE FS, and Relief FS algorithms. The results of our experiments showed that the J-48 model with the CBFS algorithm was computationally faster and achieved an excellent prediction accuracy of 100.00% in 0.00 seconds. The type of data used has a substantial impact on the performance of machine learning classifiers. Therefore, based on the experiments performed, J-48 with CBFS algorithm was proposed for deployment as the clinical decision support system that could assist medical professionals in predicting cerebrovascular diseases.

The Psychological Effects of Bring Your Own Device (BYOD)

The study of the mind and how we behave regarding certain things is tied to psychology. Psychology in itself is merely a field of study that studies the scientific nature of the mental states and processes of the mind. American Psychological Association defines psychology as the study of the mind and behavior. The question of how our minds affect our physical processes is a topic of great concern in psychology. Asserts that psychology is considered mainly a "hub science," having hefty connections to social sciences, medical science, and education. The interactions involve the mutuality between our internal and external states, and what extends from it plays an essential role in shaping the manifestations of our life's endeavors. The outfits of psychology determine how we handle tools, people, processes, etc., even in our places of work; the way we address our fellow workers, devices, and tools has almost everything to do with our psychological makeup.

The Information and Communication Technology (ICT) during the COVID-19 Pandemic

The novel coronavirus disease 2019 (COVID-19) has become a serious global challenge that has tremendously impacted socio-economic, cultural, and educational lives over the past few months. It has lead to the worldwide recession, a stoppage in all fields of life.

The Artificial Intelligence (AI) during COVID-19 Pandemic

The coronavirus disease 2019 (COVID-19) pandemic is the twenty-first century's first global public health crisis. Currently, a variety of AI-powered initiatives based on data science, "machine learning," or "big data," are being employed in a variety of disciplines to forecast, explain, and manage the various scenarios produced by the health issue.