Based on the findings and their alignment with existing

The gap

Evidence profile

Stated in the future work and recommendations sections of the source papers, classified as general, spanning 6 journals.

Supporting evidence — 8 representative gaps

• The Impacts of Artificial Intelligence on Higher Education: A Tanzanian Context (2026) · Journal of Technology-Assisted Learning · doi

  The future of AI in Tanzanian higher education lies in leveraging advanced technologies to address systemic challenges and align with global educational goals. Developing adaptive learning systems tailored to individual student needs can enhance academic outcomes, particularly for diverse learners in resourceconstrained settings (Xuan Vu, H. 2024). Virtual assistants, offering 24/7 support for student queries, and collaborative AI tools, such as platforms for group projects, hold promise for improving engagement and accessibility, especially in rural areas with limited infrastructure. AI-driven virtual learning environments (VLEs) that operate offline or on low-bandwidth networks can bridge the digital divide, ensuring equitable access to education (Mambile & Mwogosi, 2025). Tanzanian HEIs should align AI strategies with UNESCO’s 2030 objectives, focusing on equitable access and quality education. Research should prioritize process-based frameworks to predict AI’s impact across diverse demographics, addressing Tanzania’s unique socio-economic and cultural context. Investments in infrastructure, such as reliable internet and affordable devices, are critical to scaling AI adoption. Additionally, fostering public-private partnerships with tech companies can support the development of localized AI tools and training programs to build AI literacy among faculty and students. By pursuing these directions, Tanzanian HEIs can harness AI’s transformative potential to create an inclusive, innovative, and sustainable higher education system. 11. CONCLUSION AND RECOMMENDATIONS AI holds transformative potential for Tanzanian higher education, offering innovative solutions to long-standing challenges such as resource constraints, large class sizes, and unequal access to quality education. By enabling personalized learning, streamlining administrative processes, and enhancing accessibility, AI can significantly improve academic outcomes and promote inclusivity, particularly among underserved populations. Empirical studies, such as Stuart (2024) at Kampala International University in Tanzania (KIUT), reveal that AI tools like ChatGPT and Grammarly enhance students’ academic writing and overall performance, while also supporting faculty through automated grading and data-driven insights. However, effective AI integration remains constrained by infrastructural limitations, ethical concerns, inadequate policies, and limited technical expertise among faculty and students. Addressing these barriers is critical to achieving equitable and sustainable AI-driven education across Tanzania’s HEIs. The practical implications of these findings extend directly to educational policy, curriculum reform, and institutional management.

  generalstated in future workevidence 5/5
  Keywords: education tanzanian higher learning academic tools driven equitable access heis tanzania among faculty students challenges
• ARTIFICIAL INTELLIGENCE IN EDUCATION: EXPLORING OPPORTUNITIES AND CHALLENGES IN THE TEACHING-LEARNING PROCESS (2026) · The Social Science Review A Multidisciplinary Journal · doi

  i. Capacity Building and Teacher Professional Development: Developing teacher preparation programs with an emphasis on digital pedagogy and artificial intelligence is crucial. Initiatives for ongoing professional development should be developed to improve instructors’ technological proficiency, pedagogical knowledge, and self-assurance in successfully incorporating AI tools into teaching methods. ii. Ensuring Equity and Access to Technology: To deal with the problem of digital inequality, it is necessary to make sure that everyone has equal access to technology. Particularly in rural and poor regions, governments and educational institutions should make investments in digital infrastructure, such as devices, internet connectivity, and AI-enabled platforms. iii. Ethical Governance and Data Protection: The proper application of AI in education depends on the development of strong data protection regulations and unambiguous ethical standards. To promote confidence among all parties involved, regulatory frameworks must ensure accountability, openness, and the security of student data. Page | 413 The Social Science Review A Multidisciplinary Journal. March-April, 2026. Vol. 4. Issue 2. 410-415 Published by: Pather Dabi Educational Trust, (Regn No: IV-1402-00064/2023), Under Govt. of West Bengal, India iv. Collaborative and Multi-Stakeholder Approach: Teachers, legislators, and IT developers must work together to integrate AI successfully. These collaborations can help ensure that technology developments are in line with educational requirements by facilitating the development of context-specific and pedagogically relevant AI solutions. v. Balanced Integration of AI and Human Interaction: It is important to promote a balanced approach to AI implementation, where technology enhances human connection rather than takes its place. The social, emotional, and ethical aspects of education can be maintained through blended learning models that integrate AI-driven technologies with traditional instructional methods.

  generalstated in recommendationsevidence 5/5
  Keywords: development technology digital educational ethical teacher professional successfully access make protection education promote must ensure
• <b>Effects of artificial intelligence assisted instruction on </b><b>E</b><b>nglish language achievement in nigerian secondary schools: A quasi-experimental study</b><b></b> (2026) · Aminu Kano Academic Scholars Association Multidisciplinary Journal · doi

  Based on the findings and their alignment with existing literature, the following recommendations are proposed: i. Integrate AI into English Language Instruction: Schools should adopt AI-assisted tools to support personalized learning, especially in writing, grammar, and comprehension. ii. Strengthen Teacher Capacity (AI-TPACK): Teachers should be trained to effectively integrate AI with pedagogy and content to maximize learning outcomes. iii. Promote Blended Learning Approaches: AI should complement, not replace, teacher instruction, ensuring balanced and meaningful learning experiences. iv. Invest in Infrastructure: Government and stakeholders should provide adequate digital resources, including internet access and devices, to support AI integration. v. Ensure Ethical and Responsible Use: Clear guidelines should be established to address issues of academic integrity, data privacy, and over-reliance on AI tools. https://akasa.com.ng Vol.

  generalstated in recommendationsevidence 5/5
  Keywords: learning integrate instruction tools support teacher akasa based alignment existing literature following recommendations proposed english
• Preserving the Authenticity of Indian Knowledge Systems: Student and Faculty Perspectives on Responsible Use of Generative AI (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Based on the findings, the following recommendations are proposed for students, faculty, and higher education institutions: Guidelines for Responsible AI Use: Institutions should develop clear policies outlining how generative AI can be ethically used in academic work. Guidelines should include citation requirements, limits on direct content use, and encouragement of verification against authentic IKS sources. AI Awareness and Training: Conduct workshops and orientation sessions for both students and faculty on the responsible use of AI tools. Include practical exercises showing how AI can supplement learning without replacing primary sources of IKS knowledge. Integration with IKS Curriculum: Encourage faculty to design assignments that require critical engagement with IKS content, ensuring that students verify and interpret AI-generated information. Include evaluation criteria that reward original thinking and authentic understanding, not mere reproduction of AI outputs. Monitoring and Feedback: Use periodic surveys to monitor students‘ and faculty‘s perceptions and practices regarding AI use. Provide feedback and support mechanisms for students struggling to balance AI use with academic integrity. Promoting a Culture of Integrity: Foster a learning environment that emphasizes honesty, verification, and critical thinking when using AI. Recognize and reward responsible AI practices to reinforce positive behavior.

  generalstated in recommendationsevidence 5/5
  Keywords: students faculty responsible include institutions guidelines academic content verification authentic sources learning critical reward thinking
• Authentic e-assessment in South African higher education: A systematic review of AI-driven assessment practices and challenges (2026) · International Journal of Research in Business and Social Science (2147- 4478) · doi

  Strengthen institutional preparedness for AI enhanced assessment South African higher education institutions should invest in the foundational conditions necessary for responsible AI enhanced authentic e-assessment. This includes prioritising broadband expansion, strengthening learning management system capacity, and implementing devise access programmes, especially for historically disadvantage institutions and students with limited digital access. Institutions should also establish coordinated support structures involving academic development, information technology services, assessment specialists, and student support units to ensure that AI integration is sustainable and equitable. Establish mandatory professional learning for academic staff Institutions should introduce mandatory AI literacy and assessment design workshops for all academic staff involved in teaching, learning, and assessment. These capacity development initiatives should focus on authentic task design, constructive alignment, rubric development, feedback literacy, moderation practices, ethical AI use, and the interpretation of AI generated outputs. Such professional learning should be continuous rather than once off, and should be embedded within institutional academic staff development frameworks. Develop clear and enforceable institutional governance frameworks Institutions should develop institution wide AI assessment policies and procedures that provide an explicit guidance on transparency, fairness, accountability, disclosure, and data protection. These policies and procedures should clearly state when and how AI tools may be used in assessment design, feedback, grading support and verification processes. They should also require human oversight in high stakes assessments decisions and ensure that students have accessible mechanisms to challenge AI mediated outputs that may affect their academic outcomes. Pilot hybrid assessment models in selected programmes Rather than adopting AI enhanced assessment at scale without evidence, institutions should pilot hybrid assessment models in selected programmes and disciplines. These pilots should combine authentic assessment tasks with learning assurance mechanisms such as staged submissions, oral defences, reflective journals, supervised demonstrations, process logs and version histories. Formal evaluations of these pilots should be undertaken, and the lessons learnt should be documented and disseminated across faculties to inform wider institutional implementation. Introduction of institutional assessment evaluation cycles Higher education institutions should establish formal assessment evaluation cycles to determine whether AI enhanced Assessment practices are improving educational quality. These cycles should track learning gains, validity, reliability, fairness, workload implications, feedback quality, student experience, and long term graduate capabilities. Evaluation findings should be used to refine assessment policy and procedures, strengthen institutional support, and identify discipline specific good practice rather than assuming that one model will suit all contexts. 437 Mkhize-Simelan & Khohliso, International Journal of Research in Business & Social Science 15(2) (2026), 429-443 Strengthen student AI literacy and academic integrity development Student should be supported through structured through structured AI literacy programmes that clarify the ethical and appropriate use AI in learning and assessment. Institutions should provide clear guidance on acceptable and unacceptable uses of AI, expectations for disclosure where required, and the relationship between AI use and academic integrity. This support should be integrated into orientation, fist year experience initiatives, and ongoing academic development so that students are equipped to participate responsibly in AI mediated assessment environments.

  generalstated in recommendationsevidence 5/5
  Keywords: assessment institutions academic learning institutional development support enhanced programmes student literacy strengthen authentic students establish
• Usage Pattern of AI-Driven Adaptive Learning and Analytics: Transforming Higher Education through Intelligent Instructional Systems (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Based on the findings and challenges identified, the following recommendations are proposed to enhance the effective integration of intelligent instructional systems in higher education: 1. Higher education institutions should invest in reliable internet connectivity, stable electricity and modern ICT infrastructure to support effective deployment of AI-driven instructional systems and learning analytics. Collaboration between the government and institutions is essential for sustainability. KIJER 3(2) 374 Kontagora International Journal of Educational Research (KIJER) Volume 3, Issue 2, March 2026 https://fuekjournals.org/index.php/kijer 2. Continuous professional development should be provided to improve lecturers’ digital literacy and competence in using AI tools, learning analytics and adaptive learning systems, with emphasis on practical application and instructional integration. 3. Institutional leadership should implement awareness and sensitization programmes to reduce resistance to technological change and promote acceptance of AI-driven teaching innovations among academic staff. 4. Clear institutional and national policies should be established to guide data privacy, ethical use of student information, funding and strategic implementation of digital transformation in higher education.

  generalstated in recommendationsevidence 5/5
  Keywords: instructional systems higher education learning kijer effective integration institutions driven analytics digital institutional based challenges
• Higher Education in the Age of Artificial Intelligence: An Empirical Review of Curriculum Relevance and Labour Demands in Nigeria (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  In view of the above findings, the paper suggested the following recommendations: 1. Higher education regulatory bodies, particularly the National Universities Commission, should undertake an immediate review of existing university curricula to mandate the integration of artificial intelligence literacy, data analytics, computational reasoning, and ethical technology use as cross-disciplinary components across all undergraduate programmes rather than restricting such competencies to computer science and engineering-related fields. 2. Universities should establish sustained faculty development programmes through partnerships with technology-driven organisations such as Microsoft, Google, and leading Nigerian digital firms to retrain academic staff on AI-related pedagogies, practical applications, and innovative assessment models that reflect workplace problemsolving demands. 3. Higher education institutions should strengthen university-industry collaboration by embedding compulsory project-based learning, industrial simulations, internship pathways, and employer-led curriculum co-design mechanisms into academic programmes to ensure that students gain practical exposure to AI-enabled work environments before graduation. 29https://doi.org/10.5281/zenodo.20254611IJO JournalsVolume 09 | Issue 05 | May 2026 | https://ijojournals.com/index.php/er/index IJO - INTERNATIONAL JOURNAL OF EDUCATIONAL RESEARCH (ISSN: 2805-413X) Edime YUNUSA * https://ijojournals.com/ Volume 09 || Issue 05 || May, 2026 || “Higher Education in the Age of Artificial Intelligence: An Empirical Review of Curriculum Relevance and Labour Demands in Nigeria” REFERENCES Acemoglu, D., & Restrepo, P. (2021). Tasks, automation, and the rise in US wage inequality. Econometrica, 89(5), 1973–2016. Adebayo, T., & Salau, O. (2024). Artificial intelligence awareness and curriculum preparedness among university students in Nigeria. Education and Information Technologies, 29(2), 2451–2473. Adeyemi, A., & Okolie, U. (2024). Graduate employability and digital competence mismatch in Nigerian technology firms. Industry and Higher Education, 38(1), 41–56. Aina, C. (2024). Graduate employability and digital skills gaps in Nigerian higher education. Higher Education, Skills and Work-Based Learning, 14(2), 301–317. Aina, C., & Mhlongo, S. (2024). Curriculum responsiveness and artificial intelligence readiness in Nigerian universities. Higher Education Policy, 37(1), 89–111. Ashwin, P. (2023). Transforming university education: A manifesto (2nd ed.). Bloomsbury Academic. Autor, D. H. (2022).

  generalstated in recommendationsevidence 5/5
  Keywords: education higher university artificial intelligence nigerian curriculum universities technology programmes digital academic https review related
• Influence of AI Tools on the Information Literacy Skills of Grade 10 Students Within Pantay Integrated High School in Social Studies Subject (2026) · International Journal of Latest Technology in Engineering Management & Applied Science · doi

  Based on the findings and conclusions presented, researchers suggested the following recommendations. 1. 2. 3. 4. Social Study Teachers and other educators may integrate AI tools into lesson plans to actively support students in improving their information literacy skills. Special focus should be given to how AI can support critical thinking, information retrieval, and ethical use. Design engaging group activities involving AI tools to encourage collaboration and shared learning. Conduct lessons that emphasize ethical AI practices to instill responsible usage among students. Students may actively engage with AI tools to enhance their academic performance while following ethical practices. Group collaboration is encouraged when using AI tools to foster teamwork and better problem-solving strategies. Develop habits of critical evaluation by assessing the reliability and credibility of AI-generated information. School Administrators are advised to ensure access to AI tools by providing resources and training for both students and teachers. Organize regular workshops focusing on ethical AI use and its academic benefits to promote awareness and understanding. Facilitate partnerships between educators and IT experts to design innovative, technology-integrated learning strategies. Future Researchers, expand the scope of research to include other subject areas and grade levels to further examine the influence of AI tools on a wider range of students. Investigate the long-term effects of AI tools on students' academic performance and critical thinking development. Identify and address potential challenges and barriers to the implementation of AI in learning environments, such as lack of access or technological literacy. RECOMMENDATION This research is entitled The Influence of AI Tools on The Information Literacy Skills of Grade 10 Students Within Pantay Integrated High School in Social Studies Subject which was prepared and submitted by the researchers who are Christian Thirdy Mamangon and Bianca Joy Maya as part of the requirements for the Bachelor of Secondary Education Major in Social Studies, is recommended to be accepted for approval by the board. NELIA P. MANANGUIT, Ed.

  generalstated in recommendationsevidence 5/5
  Keywords: tools students information ethical researchers social literacy critical learning academic following teachers educators actively support

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