http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/35 SICT 2026-06-28T12:39:55Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31717 Title: Bridging the Gender Gap in Artificial Intelligence Education: A Systematic Review of Stem-Based Empowerment Strategies for African Girls Authors: Chuks-Ibe, Prisca Oluchi; Abduldayan, Fatimah Jibril; Tizhe, Martha Abstract: Purpose: This study examines how STEM-based initiatives are being used to bridge the gender gap in artificial intelligence (AI) education among African girls. It aims to identify key barriers, explore existing interventions, and highlight strategies that promote inclusive participation in AI-related learning across the continent. Design/Methodology/Approach: The study adopted a systematic review design using a narrative synthesis approach. Five research objectives and corresponding research questions guided the study. Relevant literature published between 2015 and 2025 was retrieved from databases such as Scopus, Web of Science, ERIC, AJOL, and Google Scholar, alongside grey literature from international organisations. A keyword-based search strategy with Boolean operators was used to identify studies focusing on STEM education, gender inclusion, and AI in Africa. Selected studies were screened through titles, abstracts, and full-text reviews based on defined inclusion and exclusion criteria. Data were analysed thematically to identify recurring patterns and key insights. Findings: The findings reveal that African girls continue to face barriers such as cultural stereotypes, limited access to quality STEM education, inadequate digital infrastructure, and lack of mentorship. However, several effective strategies were identified, including grassroots digital empowerment programmes, mentorship and scholarship initiatives, coding and AI training camps, and continent-wide programmes such as African Girls Can Code. The study also found that partnerships between governments, NGOs, and private organisations play a critical role in expanding access and improving participation. Implication: The study suggests that increasing girls’ participation in AI education requires a combination of policy support, investment in digital infrastructure, and gender-responsive STEM curricula. There is also a need for sustained mentorship programmes, teacher training, and targeted funding to ensure that interventions are scalable and sustainable across different African contexts. Originality/Value: This study is original and contributes to existing literature by providing a consolidated and up to-date synthesis of STEM-based strategies aimed at promoting gender inclusion in AI education in Africa. It offers practical insights for policymakers, educators, and development partners seeking to design effective and context relevant interventions. 2026-06-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31716 Title: Implementing AI-Enabled Learning Management System for Colleges of Education in Kwara State: Insights from a Systematic Review Authors: Abduldayan, Aishat Haruna; Jibril, Fatimah Nna; Tizhe, Martha Abstract: The integration of Artificial Intelligence (AI) into Learning Management Systems (LMS) presents significant opportunities for enhancing teaching and learning in higher education. However, the extent to which these technologies are understood, adopted, and effectively implemented in Colleges of Education in Nigeria remains uncertain. The study adopts a systematic review methodology, drawing on recent literature (2019–2025) from major academic databases. Findings reveal that awareness of AI technologies among lecturers and students is increasing; however, such awareness is largely general and not specifically linked to AI-enabled LMS functionalities. The extent of adoption is found to be low to moderate, with most institutions utilising LMS platforms primarily for basic instructional purposes, while advanced AI features such as adaptive learning, predictive analytics, and automated assessment remain underutilised. The study further identifies key challenges hindering effective implementation, including inadequate technological infrastructure, limited digital and AI competencies, insufficient funding, resistance to change, and the absence of clear institutional policies. In response, the study develops a conceptual framework that highlights the interaction between enabling factors, system features, implementation processes, and expected outcomes. The study concludes that while AI-enabled LMS has the potential to significantly improve teaching effectiveness and learning outcomes, its successful integration requires strategic investment in infrastructure, capacity building, and policy development. Description: Journal Publication 2026-06-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31715 Title: BRIDGING THE GENDER GAP IN ARTIFICIAL INTELLIGENCE EDUCATION: A SYSTEMATIC REVIEW OF STEM-BASED EMPOWERMENT STRATEGIES FOR AFRICAN GIRLS Authors: Chuks-Ibe, Prisca Oluchi; Abduldayan, Fatimah Jibril; Tizhe, Martha Abstract: Purpose: This study examines how STEM-based initiatives are being used to bridge the gender gap in artificial intelligence (AI) education among African girls. It aims to identify key barriers, explore existing interventions, and highlight strategies that promote inclusive participation in AI-related learning across the continent. Design/Methodology/Approach: The study adopted a systematic review design using a narrative synthesis approach. Five research objectives and corresponding research questions guided the study. Relevant literature published between 2015 and 2025 was retrieved from databases such as Scopus, Web of Science, ERIC, AJOL, and Google Scholar, alongside grey literature from international organisations. A keyword-based search strategy with Boolean operators was used to identify studies focusing on STEM education, gender inclusion, and AI in Africa. Selected studies were screened through titles, abstracts, and full-text reviews based on defined inclusion and exclusion criteria. Data were analysed thematically to identify recurring patterns and key insights. Findings: The findings reveal that African girls continue to face barriers such as cultural stereotypes, limited access to quality STEM education, inadequate digital infrastructure, and lack of mentorship. However, several effective strategies were identified, including grassroots digital empowerment programmes, mentorship and scholarship initiatives, coding and AI training camps, and continent-wide programmes such as African Girls Can Code. The study also found that partnerships between governments, NGOs, and private organisations play a critical role in expanding access and improving participation. Implication: The study suggests that increasing girls’ participation in AI education requires a combination of policy support, investment in digital infrastructure, and gender-responsive STEM curricula. There is also a need for sustained mentorship programmes, teacher training, and targeted funding to ensure that interventions are scalable and sustainable across different African contexts. Originality/Value: This study is original and contributes to existing literature by providing a consolidated and upto-date synthesis of STEM-based strategies aimed at promoting gender inclusion in AI education in Africa. It offers practical insights for policymakers, educators, and development partners seeking to design effective and contextrelevant interventions. 2026-06-01T00:00:00Z http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31662 Title: NutriMax: an Android Based Personalized Nutrition Management System Authors: Alabi, Isiaq Oludare; Salau, Rasaq Bolakale; Sesugh, Simon Lankwagh Abstract: t Personal nutrition management is very important for the sustenance of good health, there are a lot of health complications that occur in the human body when certain food nutrients are insufficient, this results in nutritional deficiencies which are very life-threatening for health vulnerable individuals such as pregnant women, sick people, children and the aged. This research focused on the development of mobile application software with an algorithm based on machine learning of data mining principle to learn, train and analyze the challenges of malnutrition and how to effectively manage it. The mineral value content of one hundred and twenty (120) assorted commonly available Nigerian food substances was collected and contrasted with standard dietary benchmarks. Factory processed foods were not be considered. Hence, a list of daily requirements of food nutrients by the human body was sourced together with a selected number of nutritional deficiencies to create a mobile application powered by an algorithm that establishes a relationship between nutritional deficiencies and their requirements to suggest daily meals for users. The data obtained was uploaded to a real-time database and integrated with Android Studio to build a working Android application interspersed with Java programming language. The food guide application was named NutriMax. 2021-01-01T00:00:00Z