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Analysis of Online Academic Writing Tools Usage among Postgraduate Students in North-west Nigeria Yakubu, Muhammad Auwal; Sain, Zohaib Hassan; Lawal, Uthman Shehu; Budiman, Septian Arief; Permana, Dian
Kharisma: Jurnal Administrasi dan Manajemen Pendidikan Vol. 4 No. 1 (2025): Integrative Islamic Education Management
Publisher : Perkumpulan Dosen Tarbiyah Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59373/kharisma.v4i1.69

Abstract

This study investigates the usage of online academic writing tools and reference management software among postgraduate students in North-west Nigeria. A descriptive survey design was employed, with a sample of 420 doctoral students from four regional universities. Data was collected using a structured questionnaire and analyzed using descriptive and inferential statistics. The findings reveal that Google Docs and Authorea are the most widely used online tools for academic writing and collaboration, followed by Overleaf and OneNote. Surprisingly, Microsoft Office 365 showed lower adoption rates. Regarding reference management software, Mendeley and Zotero emerged as the clear favourites, with EndNote and Citavi also showing significant usage. Statistical analysis indicated significant differences in the use of online tools for academic writing and collaboration and the types of reference management software used among postgraduate students. These differences could be attributed to individual preferences, institutional recommendations, or varying levels of technological literacy. The study contributes to understanding digital literacy and technology adoption in higher education in developing countries. It provides valuable insights for educational institutions, policymakers, and software developers to support postgraduate students' academic endeavours. Recommendations include implementing digital literacy programs and developing standardized sets of recommended tools to enhance research productivity and collaboration among doctoral students in North-west Nigeria.
Application of Artificial Intelligence [AI] for Automated Essay Grading in Nigerian Schools Yakubu, Muhammad Auwal; Sain, Zohaib Hassan; Lawal, Uthman Shehu; Budiman, Septian Arief
Indonesian Journal on Education (IJoEd) Vol. 1 No. 2 (2024)
Publisher : LPPI Yayasan Almahmudi bin Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70437/vnve7j92

Abstract

This paper explores the potential application of Artificial Intelligence (AI) for automated essay grading in Nigerian schools. Building on the current challenges in the Nigerian education system, including large student populations, time constraints, and inconsistent grading standards. The paper analyses how AI-based automated essay grading systems can address these issues by improving the assessment process's efficiency, consistency, and scalability. It also provide an overview of AI-based grading mechanisms, including machine learning and natural language processing techniques. It analyzes global case studies from countries like the United States, China, Japan, Spain, and Germany to draw insights into successful implementation strategies. The study also examines emerging applications of AI essay grading in African contexts, including South Africa, Kenya, and Egypt. Key findings highlight the potential benefits of AI grading systems in Nigerian schools, including reduced grading time, increased objectivity, and more detailed student feedback. However, the paper also identifies significant challenges like infrastructure deficits, technical limitations, ethical concerns, and cost implications. Thus, concludes with recommendations for implementing AI essay grading in Nigerian schools, proposing a gradual rollout strategy, developing comprehensive policy frameworks, and collaborating with technology providers. These recommendations aim to address the Nigerian context's unique challenges while leveraging AI's potential to enhance educational assessment and outcomes.
Bridging the Digital Divide: Artificial Intelligence Adoption Among Lecturers in Kaduna State, Nigeria Yakubu, Muhammad Auwal; Sain, Zohaib Hassan; Shehu Lawal, Uthman; Musnandar, Aries
Paedagogia: Jurnal Pendidikan Vol 14 No 2 (2025): PAEDAGOGIA: Jurnal Pendidikan
Publisher : Fakultas Tarbiyah dan Ilmu Keguruan IAIN Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24239/pdg.Vol14.Iss2.598

Abstract

This study investigates the awareness, adoption, and impact of Artificial Intelligence (AI) technologies among lecturers in Kaduna State, Nigeria. It addresses three primary research questions: the extent of lecturers' awareness of AI-powered educational tools, the types of AI technologies currently adopted, and the impact of these technologies on academic activities. Utilizing a descriptive survey design, data were collected from a sample of 420 academic staff across four tertiary institutions using a validated instrument based on a modified Likert scale. The study employs one-sample t-tests to evaluate three hypotheses about awareness, adoption, and impact. Findings reveal that lecturers possess moderate awareness of AI applications and are highly familiar with plagiarism detection and content creation tools but need more understanding of intelligent tutoring systems and adaptive learning platforms. Adoption is selective; AI-powered research assistants and content creation tools are widely used, while technologies like Natural Language Processing (NLP) are less common. The study identifies a positive impact of AI on academic activities, enhancing collaboration and resource accessibility while raising ethical concerns. Statistical analyses indicate significant differences in awareness levels, adoption rates, and perceived impacts among lecturers. These findings suggest varied engagement with AI tools across educational settings in Kaduna State. The study concludes that while there is a positive perception of AI's educational impact, improvements in training and infrastructure are necessary to leverage these technologies fully. Recommendations include organizing workshops to increase familiarity with underutilized AI tools, integrating AI training into professional development, and establishing guidelines for ethical AI use in education.