Artificial Intelligence Data Analysis Tools Utilization and Research Writing Activities of Business Education Students in Tertiary Institutions in Cross River State (Published)
This study examined the relationship between AI data analysis tools utilization and research writing activities of Business Education students in tertiary institutions in Cross River State. The study was guided by three specific purposes, three research questions, and three hypotheses. A correlational survey research design was adopted for the study. The population of the study was one thousand, three hundred and nineteen (1319) Business Education students (1251 from Universities and 68 from Colleges of Education) in four (4) public tertiary institutions in Cross River State. The sample size of this study was 307 students (291 from Universities and 16 from Colleges of Education). The data for the study were collected using an AI Data Analysis Tools Utilization Questionnaire (AIDATUQ) and the Research Writing Activities Questionnaire (RWAQ). The instruments were face-validated by three experts and further tested for reliability. For the AIDATUQ, the Cronbach’s alpha coefficient was 0.69, and for the RWAQ, the K-R20 coefficient was 0.88. Data were analyzed using Pearson product-moment correlation to answer the research questions and linear regression to test the null hypotheses at a 0.05 confidence level. The findings revealed that there is a high positive relationship between AI Data Analysis Tools and research writing activities of Business Education students in tertiary institutions in Cross River State. The relationship is statistically significant. There is a low positive relationship between AI data analysis Tools and research writing activities of Business Education students in colleges of education in Cross River State. The relationship is statistically significant. There is a low negative relationship between AI Data Analysis Tools Utilization and research writing activities of Business Education students in universities in Cross River State. The relationship is not statistically significant. It was recommended, among others, that tertiary institutions should provide Business Education students with regular practical training on the effective and responsible use of AI Data Analysis Tools for research writing, particularly in data analysis, interpretation, and presentation of research findings.
Keywords: Artificial Intelligence, artificial intelligence data analysis tools, research writing activities
Leveraging Artificial Intelligence to Redesign TVET Assessment Systems for Enhancing Creativity and Innovation in Technical Education (Published)
This study explores the integration of Artificial Intelligence (AI) into Technical Vocational Education and Training (TVET) assessment systems in Nigeria, focusing on how AI can enhance creativity, innovation, and problem-solving among students. Traditional assessment methods in Nigerian TVET institutions have been found to inadequately evaluate 21st-century competencies, particularly in areas such as innovation and creative thinking. The research employed a descriptive survey design using a structured questionnaire administered to 285 respondents, including educators, students, and ICT personnel. Findings revealed moderate effectiveness of current assessments in capturing technical skills and a significant gap in evaluating creativity and innovation. While 57.9% of respondents were aware of AI in education, confidence in using AI tools remained moderate. Key AI technologies such as adaptive testing, learning analytics, and automated grading were widely recognized and positively perceived. However, challenges such as poor infrastructure, limited training, high implementation costs, and resistance to change were identified as major barriers. Despite these, respondents highlighted several opportunities AI offers, including real-time feedback, personalized learning, and improved assessment accuracy. Respondents also emphasized the need for targeted support such as training, digital infrastructure, policy frameworks, funding, and collaboration with tech providers. The study concludes that AI integration in TVET assessment holds substantial potential to modernize educational practices and better prepare students for the demands of an innovation-driven workforce, provided that strategic implementation and capacity-building measures are in place.
Keywords: Artificial Intelligence, Creativity, Innovation, Nigeria, TVET assessment, personalized learning