2026

The study investigated the impact of scheduling and timetable clashes on academic performance of integrated science students. Five research questions were raised to guide the study. Descriptive survey research design was adopted by the study. The population of the study comprised of all science education students in of the selected university. Specifically, the study focused on 150 students in integrated science, chemistry education, and biology education. They were selected from the population using the stratified random sampling technique. The questionnaire was the instrument used for data collection. The validity of the instrument was validated by the researcher’s supervisor. The data collected were analyzed using descriptive statistical methods, frequency counts at 0.05 level of significance. The result of the reliability test yielded a Cronbach Alpha coefficient of 0.84, which indicates a high level of internal consistency of the instrument. The study found that many students experience timetable clashes, including lecture overlaps and scheduling conflicts, during their academic activities. It also revealed that timetable clashes vary across academic levels, with students in higher levels (especially 300 and 400 levels) facing more scheduling challenges due to heavier workloads and course combinations. Furthermore, Integrated Science students were found to experience more timetable-related problems because they take courses from multiple science departments, affecting both male and female students. Based on the findings, the study recommends that university management adopt effective timetable planning, computerized scheduling systems, and balanced academic schedules while encouraging students to develop time-management skills in order to reduce timetable clashes, minimize stress, and improve academic performance.

In the 21st century, digital technology has become deeply embedded in nearly every aspect of daily life from communication and commerce to healthcare and education. While younger generations have adapted rapidly to this digital transformation, many elderly individuals remain on the margins of the digital world. This generational divide has created a significant barrier to inclusion, autonomy and access to essential services for older adults. The inability to navigate digital platforms not only limits their participation in modern society but also exacerbates feelings of isolation, dependence and vulnerability. This project investigates the multifaceted challenges that elderly populations face in adopting and using digital technologies. These challenges include physical limitations such as impaired vision and motor skills, cognitive barriers like memory decline and unfamiliarity with digital interfaces and socio-economic factors such as lack of access to devices or internet connectivity. The study also explores the psychological impacts of digital exclusion, including reduced self-esteem, social withdrawal and increased mental health risks. The research further examines how emerging technologies such as voice activated assistants, simplified user interfaces and wearable health devices can be tailored to meet the needs of older adults. It also considers the role of caregivers, family members and community organizations in supporting digital adoption among seniors. Ultimately, this project argues that closing the digital generational gap is not merely a technical challenge but a social imperative. By fostering inclusive design, empathetic education and supportive ecosystems, society can empower elderly individuals to engage meaningfully with technology. Through inclusive design and community driven support, this project envisions a future where older adults actively participate in the digital world, fostering equity and stronger bonds across generations.

This study examined the influence of repeated exposure to social media advertisements on audience adoption of Lush Hair Products, using undergraduate students of the Department of Mass Communication, University of Benin, as the study population. The study was anchored on the Social Learning Theory and the Diffusion of Innovations Theory. The researcher adopted a survey research design, with data collected from 288 respondents drawn from a population of 1,009 students using the Taro Yamane formula and a stratified sampling technique. A structured questionnaire served as the research instrument, and data were analysed using frequency counts and percentages. The study revealed that the level of audience exposure to Lush Hair's social media advertisements is high, with respondents frequently encountering the brand across various platforms. Secondly, audience perceptions were generally positive, particularly regarding visual appeal and clarity of product information, although perceptions of credibility and trustworthiness were relatively weaker. Thirdly, adoption was found to be influenced by influencer endorsements, positive online reviews, affordability, and accessibility, alongside social influence and consumer feedback. Finally, repeated exposure was found to have a positive influence on adoption, as continuous exposure strengthened brand familiarity, purchase intention, and consumer trust over time. It was concluded that sustained, well structured social media advertising, combined with credible messaging, is essential for improving consumer response. It was then recommended that advertisers pair repeated exposure with message variation to reduce ad fatigue, invest in authentic testimonials to build trust, leverage influencer partnerships and favourable product conditions, and use audience-targeting tools to improve campaign precision.

This study examined the impact of fake news on media credibility, with a focus on how exposure to misinformation influences public trust in media organizations. The increasing spread of fake news, particularly through social media platforms, has raised concerns about the reliability of information and the credibility of the media. The study adopted a survey research design, using a structured questionnaire to collect data from respondents. A total of 400 questionnaires were distributed, out of which 350 were retrieved and used for analysis, representing an 87.5% response rate. The data collected were analyzed using frequency counts and simple percentages. Findings from the study revealed that exposure to fake news is widespread, with the majority of respondents encountering false or misleading information, especially on social media platforms such as WhatsApp and Facebook. The study also found that fake news has significantly reduced public trust in media organizations and has increased skepticism among media users. Many respondents indicated that they now verify information from multiple sources before believing or sharing it. The study concludes that fake news has a negative impact on media credibility and poses a serious challenge to the integrity of the media. It therefore recommends improved factchecking by media organizations, increased media literacy among the public, and stronger regulatory measures to control the spread of misinformation.

This study investigated artificial intelligence applications in relation to financial reporting quality among deposit money banks in Nigeria. The specific objectives were to examine the extent to which artificial intelligence accounting, artificial intelligence data analytic, artificial intelligence auditing and artificial intelligence predictive applications have influence on financial reporting quality of deposit money banks in Nigeria. This study was a field survey for the year 2025. A total of 2,839 accountants, auditors and management staff constituted the population size, while 351 staff of deposit money banks in Benin City of Edo state formed the sample size by employing stratified and purposive sampling selection techniques. It was a quantitative research design and the main instrument used in collecting data was questionnaire administration. The statistical techniques employed include descriptive statistics, Pearson correlations, variance inflation factor and least squares regression method. The study found that artificial intelligence accounting, data analytic and predictive applications have significant positive t-statistics value of 2.480, 2.441 and 2.796 with a probability value of 0.010 (1%), 0.010 (1%) and 0.005 (0.5%) respectively. It was also revealed that artificial intelligence auditing applications has no significant influence on financial reporting quality among deposit money banks in Nigeria but has positive t-statistics value of 1.634 with a probability value of 0.103 (10%). Thus, the study concluded that artificial intelligence applications in accounting, data analytics, auditing and predictive analytics are critical in facilitating enhancement in financial reporting quality among deposit money banks. It therefore recommended that organisations should take advantages of artificial intelligence innovation by training and developing their accountants, auditors and senior managers in areas of financial transactions analyses and prediction to enhance financial reporting quality for the interest of stakeholders.

This study examined the impact of fake news on media credibility, with a focus on how exposure to misinformation influences public trust in media organizations. The increasing spread of fake news, particularly through social media platforms, has raised concerns about the reliability of information and the credibility of the media. The study adopted a survey research design, using a structured questionnaire to collect data from respondents. A total of 400 questionnaires were distributed, out of which 350 were retrieved and used for analysis, representing an 87.5% response rate. The data collected were analyzed using frequency counts and simple percentages. Findings from the study revealed that exposure to fake news is widespread, with the majority of respondents encountering false or misleading information, especially on social media platforms such as WhatsApp and Facebook. The study also found that fake news has significantly reduced public trust in media organizations and has increased skepticism among media users. Many respondents indicated that they now verify information from multiple sources before believing or sharing it. The study concludes that fake news has a negative impact on media credibility and poses a serious challenge to the integrity of the media. It therefore recommends improved factchecking by media organizations, increased media literacy among the public, and stronger regulatory measures to control the spread of misinformation.

This study investigated integrating of technology into early childhood preschool classroom in Oredo Local Government Area. The study also sought to find out if there any difference in the level integrating technology into preschool classrooms in Oredo local Government Area based on school location, ownership and teachers’ qualification. Five research questions were raised. Two were answered directly while three were hypothsized and tested at 0.05 level of significance.
The research adopted a descriptive survey design involving 60 preschool teachers selected through multi-stage sampling from both public and private early childhood education centers. Data were collected using a structured questionnaire titled "Technology Integration in Early Childhood Education Questionnaire (TIECEQ)" and analyzed using descriptive statistics (mean and standard deviation) and inferential statistics (Independent sample t-test). Findings revealed that technology is integrated to a high degree in preschool classrooms, with interactive whiteboards, tablets, and educational software being most frequently utilized. However, tools such as headphones, smartphones, and audio equipment were moderately used. The study found no significant differences in technology integration based on school location, ownership type, or teachers' qualifications. Based on the findings the following recommendations were made: The identified technology identified in this study should be well integrated in early childhood classrooms because they have their various roles in the development of the child. In addition, school, should endeavour to source funds to procure these technologies from non governmental organisations and philanthropists.

This study examines the impact of microfinance on women’s economic empowerment in Edo State, Nigeria, using the Lift Above Poverty Organisation (LAPO) as a case study. The research is motivated by the persistent financial exclusion and structural inequalities faced by women, particularly those operating within the informal sector. It investigates how access to microfinance services, including loans, savings schemes, and training programmes, influences key dimensions of empowerment such as income generation, financial independence, and decision-making capacity. Adopting a descriptive survey research design, the study utilises primary data collected from 180 female beneficiaries of LAPO, with 174 valid responses analysed. Both descriptive and inferential statistical techniques, including multiple regression analysis, were employed to assess the relationship between microfinance services and women’s economic empowerment. The findings reveal that access to microfinance services has a significant and positive effect on women’s economic empowerment. Specifically, savings services and loan access emerged as the strongest predictors, while training and capacity-building programmes also contributed meaningfully to improved outcomes. The results further indicate that participation in microfinance enhances women’s ability to generate income, strengthens their financial autonomy, and increases their involvement in economic decision-making. However, the study also acknowledges that empowerment is multifaceted and influenced by contextual factors such as social norms and household dynamics. The study concludes that microfinance, when effectively designed and implemented, serves as a critical tool for promoting women’s economic empowerment and inclusive development. It recommends that policymakers and microfinance institutions strengthen gender-responsive financial products, expand access to savings-led initiatives, and integrate capacity-building programmes to ensure sustainable empowerment outcomes.

Expanding noncontact techniques for monitoring groundwater level variations to include laser based devices has been limited in the past by the low reflectivity of water to laser light The advances made in the realization of highly sensitive receivers has greatly enabled Laser devices with the prospect for effective noncontact monitoring of groundwater levels. In this work a real-time groundwater level monitoring devices was implemented using a LiDAR-lite v3HP laser-based sensor, an Arduino Uno rev 3 microcontroller, and an ESP8266 Wi-Fi module. Hardware implementation involved interfacing the microcontroller with the LiDAR-lite, the Wi-Fi module, a 16 x 2 liquid crystal display and other necessary basic electronic components. The software implementation involved writing, editing, compiling and uploading codes through the Arduino ide unto the microcontroller. The implemented prototype was powered by a 20,000mAH, 5V power bank and deployed on two artesian wells to collect depth to water surface data which were uploaded automatically to ThingSpeak platform. Measurements at various times taken with the device were compared with manual measurements from a calibrated tape. A correction factor was applied to correct measurement residuals. Results of the validation showed that measured values were uploaded to the ThingSpeak platform an average of 33 seconds which could be reconfigured to longer timeframes. The results were remotely accessed on the platform. A correlation graph of measurement before and after applying the correction revealed a near perfect correlation coefficient of 0.99995 for the LiDAR readings for both pre-correction and post correction measurements; confirming a strong linear relationship with tape measurements. The coefficient of variation, root mean square error and limits of agreement from the Bland Altman’s plots all ascertained the improvement in post-correction measurements.

Expanding noncontact techniques for monitoring groundwater level variations to include laser based devices has been limited in the past by the low reflectivity of water to laser light The advances made in the realization of highly sensitive receivers has greatly enabled Laser devices with the prospect for effective noncontact monitoring of groundwater levels. In this work a real-time groundwater level monitoring devices was implemented using a LiDAR-lite v3HP laser-based sensor, an Arduino Uno rev 3 microcontroller, and an ESP8266 Wi-Fi module. Hardware implementation involved interfacing the microcontroller with the LiDAR-lite, the Wi-Fi module, a 16 x 2 liquid crystal display and other necessary basic electronic components. The software implementation involved writing, editing, compiling and uploading codes through the Arduino ide unto the microcontroller. The implemented prototype was powered by a 20,000mAH, 5V power bank and deployed on two artesian wells to collect depth to water surface data which were uploaded automatically to ThingSpeak platform. Measurements at various times taken with the device were compared with manual measurements from a calibrated tape. A correction factor was applied to correct measurement residuals. Results of the validation showed that measured values were uploaded to the ThingSpeak platform an average of 33 seconds which could be reconfigured to longer timeframes. The results were remotely accessed on the platform. A correlation graph of measurement before and after applying the correction revealed a near perfect correlation coefficient of 0.99995 for the LiDAR readings for both pre-correction and post correction measurements; confirming a strong linear relationship with tape measurements. The coefficient of variation, root mean square error and limits of agreement from the Bland Altman’s plots all ascertained the improvement in post-correction measurements.