higher education

This study investigated university students’ attitude towards chemistry and its effect on their academic achievement among 50 undergraduate chemistry students at the University of Benin. The aim was to determine how perceived relevance, enjoyment, and difficulty influence performance in chemistry courses. Using a descriptive survey design, data were collected with a structured questionnaire and analyzed with SPSS using descriptive statistics, correlation, and regression. The mean scores showed moderate to positive attitudes: perceived relevance (M = 3.01, SD = 0.64), enjoyment (M = 2.95, SD = 0.62), and perceived difficulty (M = 2.83, SD = 0.59). The mean academic achievement score was 68.7 ± 9.4, indicating moderate–high performance. Correlation analysis revealed significant positive relationships between relevance (r = 0.42, p < 0.01) and enjoyment (r = 0.49, p < 0.01) with academic achievement, while perceived difficulty correlated negatively (r = –0.34, p < 0.01). Regression analysis showed that the attitude components jointly explained 43% of the variance in performance (R = 0.66, R² = 0.43, Adjusted R² = 0.41, F = 20.26, p < 0.001). Enjoyment (β = 0.37, p = 0.000) and relevance (β = 0.28, p = 0.000) were the strongest positive predictors, while difficulty had a significant negative effect (β = –0.25, p = 0.000). Gender differences were observed, with females (M = 69.8 ± 9.1) outperforming males (M = 67.2 ± 9.7, p = 0.037). No significant difference occurred across study levels (F = 0.71, p = 0.546). The study concludes that positive attitudes—especially enjoyment and perceived relevance—enhance academic success, while perceived difficulty lowers performance. It recommends interactive teaching, real life applications, and improved laboratory access to strengthen students’ engagement and achievement in chemistry.

Efficient complaint management is essential for enhancing student satisfaction and institutional accountability in higher education. However, most existing systems lack intelligence, scalability, and analytical depth. This dissertation presents the design and implementation of an AI-driven Student Complaints Management System (SCMS) that integrates Natural Language Processing (NLP) and sentiment analysis to improve how student grievances are captured, categorized, and resolved. The system applies text-mining techniques to interpret complaint narratives, classify issues by department, and assess emotional tone to prioritize responses. A modular web-based architecture enables real-time reporting, trend visualization, and administrative insights. Using a design science research methodology, the study demonstrates that intelligent automation significantly reduces resolution time and enhances decision-making transparency. The proposed SCMS contributes to the field of educational technology by merging human-computer interaction with data analytics to foster responsive governance and continuous improvement in higher education service delivery

This project work looks into how higher education promotes social mobility and reduces inequality by equipping individuals with skills, knowledge, and social capital for economic and social advancement. However, this potential is limited by systemic barriers like financial constraints, geographic disparities, and the digital divide, which disproportionately affect disadvantaged groups. Overcoming these obstacles through equitable access and supportive policies is essential to ensuring higher education functions as a true pathway to upward mobility and a more just society.

This project work looks into how higher education promotes social mobility and reduces inequality by equipping individuals with skills, knowledge, and social capital for economic and social advancement. However, this potential is limited by systemic barriers like financial constraints, geographic disparities, and the digital divide, which disproportionately affect disadvantaged groups. Overcoming these obstacles through equitable access and supportive policies is essential to ensuring higher education functions as a true pathway to upward mobility and a more just society.

This study investigated the effectiveness of online counselling in addressing anxiety disorders among undergraduate students at the University of Benin, Nigeria. It was anchored on Cognitive Behavioural Theory, Self-Determination Theory, and the Technology Acceptance Model, which together explain the therapeutic, motivational, and technological dimensions of online counselling. The study adopted an ex post facto research design, and a sample of 394 undergraduates was drawn through proportionate stratified sampling. Data were collected using the Online Counselling Feedback Questionnaire (OCFQ) and analysed using Pearson’s product–moment correlation and Fisher’s Z tests at the 0.05 level of significance. The results revealed a significant positive relationship between engagement in online counselling and reduction in anxiety symptoms (r = .252, p < .001), indicating that students who participated in online counselling reported lower levels of worry and tension. Further analysis showed a significant difference based on sex, with male students showing a stronger relationship (r = .376) than female students (r = .168). However, age did not significantly moderate the counselling–anxiety relationship. These findings suggest that online counselling is an effective and accessible tool for mitigating anxiety among university students. The study concludes that while online counselling holds strong potential to enhance student mental health, sex-responsive engagement strategies are essential to ensure equitable benefits. It is recommended that universities integrate structured online counselling systems, train counsellors in digital modalities, and promote awareness of technology-based mental health services within higher education institutions in Nigeria