Ibrahim Mohammed

Although extensive research has examined AI integration in education and the UTAUT2 model, few studies have explored ChatGPT adoption with demographic variables in Nigeria and other African contexts. Prior studies have analyzed the impacts UTAUT variables have on students’ behavioral intention and use of ChatGPT, yet little is known about how these relationships differ by demographic profiles. This study addresses that gap by investigating the influence of factors such as age, sex, and programme of study on these associations among Nigerian higher education students. A cross-sectional correlational design was used and data were collected from 8,496 students across various tertiary institutions in Nigeria, using a structured questionnaire. Data were gathered electronically between October 13, 2023, and February 14, 2024. Multigroup analysis within the framework of Partial Least Squares Structural Equation Modelling (PLS- SEM) was performed. Both measurement and structural model metrics are reported for all subgroups. Findings indicate that performance expectancy is associated with higher intention to use ChatGPT, particularly among males, older students, and those with advanced qualifications, while its relationship with actual use varies across age groups. Effort expectancy and social influence showed differing associations with intention and use depending on demographic characteristics. Facilitating conditions were generally linked to greater actual use, and both hedonic motivation and habit were consistently associated with intention and behavior. These results provide empirical evidence of demographic variations in ChatGPT adoption among Nigerian students and suggest that interventions promoting AI tools should consider these differences.

Abstract: A complex parasite such as human Plasmodium is likely to generate a variety of substances that injure the hosts directly or cause immunopathology. In malaria, a blood concentration of anti-inflammatory cytokines, such as interleukin (IL-10) is increased. The present study was performed to analyze IL-10 levels in patients with malaria falciparum and healthy controls individuals and correlate with malaria density infection as well as age groups. It is a cross sectional study was carried out in Khartoum state /Sudan, a total of 70 febrile patients and 20 healthy volunteers as controls were included in this study. Blood samples were collected from both patients and control candidates in (EDTA) containers for parasitological and immunological tests. Immunochromatography test and microscopic examination for both thick and thin blood films were used to detect the positive samples for Plasmodium falciparum. Enzyme linked Immunosorbant Assay (ELISA), was used for the determination of IL-10 levels. The result showed that of IL-10 levels in malaria patients were 1598.50 and SD 4771.64 while the levels in healthy participants the level was 10.39 and SD was 124.33 the difference was found to be statistically significant (P= 0.007). The levels of cytokines mentioned above were observed to be raised in malaria individual compared to healthy control candidates.

Over the years, Ghana has developed and implemented policies that are intended to achieve green outcomes. In order to strengthen its green credentials, the country ratified the Paris Agreement in August 2016. Among the twenty action items developed to be implemented to achieve the targets of the Paris Agreement, nine are directly related to the energy sector. This has led to a number of interventions, including the Drive Electric Initiative, which seeks to encourage ownership and use of electric vehicles. In order to examine the readiness of consumers to change to, or pay for EVs, the paper adopts the limited dependent variable regression—with both probit and logit estimators—to determine the factors that influence the demand for electric vehicles. Our measure of the respondents’ willingness to change to or pay for EVs is captured in two forms to ensure robustness of our results. First, we measure willingness to change to EVs (WTC) by asking the respondents about their willingness to change to EVs based on the limited information that the respondents may have on EVs. Secondly, after realizing their limitations of knowledge regarding EVs and giving them further advantages of EV ownership, we measure the respondent’s willingness to change to EVs after exposure. Therefore, we consider the provision of knowledge on EVs to the respondents as some form of a treatment. After these, we examine the respondent’s willingness to pay for EVs (WTP) using the same determinants we considered in their WTC after treatment. The findings indicate that regardless of the level of information provided on EV, travel distance, income, expenditure on fuel and the extent of Green House Gas emissions were key factors that influenced respondents’ willingness to change to or pay for EVs and the result was significant when more information was given.