The rapid shift to online learning during the COVID-19 pandemic has significantly influenced educational practices worldwide and increased the use of online learning platforms. This systematic review examines the impact of online learning on student engagement and performance, providing a comprehensive analysis of existing studies. Using the Preferred Reporting Items for Systematic review and Meta-Analysis (PRISMA) guideline, a thorough literature search was conducted across different databases (PubMed, ScienceDirect, and JSTOR for articles published between 2019 and 2024. The review included peer-reviewed studies that assess student engagement and performance in online learning environments. After applying inclusion and exclusion criteria, 18 studies were selected for detailed analysis. The analysis revealed varied impacts of online learning on student performance and engagement. Some studies reported improved academic performance due to the flexibility and accessibility of online learning, enabling students to learn at their own pace. However, other studies highlighted challenges such as decreased engagement and isolation, and reduced interaction with instructors and peers. The effectiveness of online learning was found to be influenced by factors such as the quality of digital tools, good internet, and student motivation. Maintaining student engagement remains a challenge, effective strategies to improve student engagement such as interactive elements, like discussion forums and multimedia resources, alongside adequate instructor-student interactions, were critical in improving both engagement and performance.

BACKGROUND: Depression is prevalent during antenatal and postnatal stages of pregnancy. The effect of depression can be seen in complications during and after pregnancy, fetal growth retardation, abortions and preterm births. The literature abounds on postpartum depression (PD) while few studies are on antepartum depression (AD). AIM: The systematic review aims to compute the prevalence of AD from published articles. MATERIAL AND METHODS: The published articles (26) used in this review were obtained from the search of the search keywords “Depressive conditions in pregnancy AND trimesters”. All the articles were considered irrespective of language and their citation status as of the time of the query. Only articles that presented the prevalence mean and sample size were included. Articles on questionnaires filled by nonpregnant women and men were excluded. Articles that presented the prevalence of depression for the postpartum period only were excluded but were included if they addressed depression at both postpartum and trimester(s) of pregnancy. P-value of less than or equal to 0.05 was considered significant. RESULTS: Analysis of the 26 articles showed that 4,303 subjects tested positive for depression in a sample of 28,248 pregnant mothers, giving the prevalence rate as 15%. Confounding was removed, and the sample size was adjusted to be 25,771 and 4,223 were screened to have depressive symptoms, thereby giving a new prevalence rate as 16.4%. It was also revealed that AD is most prevalent in the last trimester of pregnancy and least in the second trimester. Pregnancy duration and PD are not correlated with AD. This implies that AD can be observed in any period of the pregnancy and cannot predict the incidence of PD. CONCLUSION: Efforts must be intensified to monitor pregnant women during the third trimester to reduce the incidence of maternal depression during pregnancy, thereby reducing the prevalence.

Most scientific research generates data. Analysis of the data from scientific research helps create new knowledge or a deep understanding of natural phenomena. Statistical software is used mainly in data analysis. SPSS and Minitab appear to be most popular, especially for those that could neither code nor mathematical inclined to handle advanced software such as R, MATLAB, Maple, etc. Trends and usage pattern of SPSS and Minitab Software in Scientific research was studied in this paper with the data obtained from the Scopus database. In their abstracts or keywords, documents that have mentioned SPSS were extracted for the years 2010 to 2019. Frequency analysis showed that the trend of using SPSS and Minitab is steadily increasing, although the use of Minitab is a fraction of SPSS. Minitab is mostly used in engineering, materials science, and computer science, while SPSS is mainly used in medicine, social science, and engineering. Analysis of the document type showed that SPSS and Minitab are mostly stated in abstracts or keywords of research articles, conference papers, review papers, and books indexed in Scopus.

This dataset covers an investigation into awareness and adoption of information and communication technology (ICT) in town planning firms in Lagos state, Nigeria. A survey of thirty (30) town planning firms in Lagos state, Nigeria was conducted. The survey was carried out between January to March 2017 by the use of questionnaires. The dataset contains responses on the factors that influence ICT usage, barriers and constraints of ICT usage. The five (5) point Likert scale was used for quantitative data analysis. The data can help identify the level of ICT usage, identify areas of concern and solutions can be proffered based on the results of the analysis.