The integration of AI into higher education poses challenges for academic staff, including the need for targeted training and support programs

The gap

Evidence profile

Sourced from the recommendations and stated challenges of the source papers, classified as general, spanning 3 journals.

Supporting evidence — 3 representative gaps

• Exploring Lecturers' Experiences with Artificial Intelligence Integration in Lecturing: A Case Study of a Private Higher Education Institution in Rwanda (2026) · Open Journal of AI, Ethics & Society (ISSN: 3105-3076) · doi

  Based on these findings; 1. Private higher education institutions should develop and formally communicate a clear institutional policy on AI integration in lecturing, specifying expectations, acceptable tools, and quality standards for its pedagogical use. 2. Institutions should invest in continuous, hands-on professional development programs and structured peer-mentoring schemes so that lecturers can move from self-taught, trial-and-error use of AI toward confident, pedagogically grounded practice. 3. Institutions should prioritize investment in reliable technical infrastructure, including stable internet connectivity and accessible IT support, to remove practical obstacles that currently discourage consistent AI use in lecturing. 4. Institutional leaders should consider mechanisms for recognizing and incentivizing lecturers who invest additional effort in integrating AI into their teaching, so as to sustain motivation and encourage broader adoption 5. Future research should extend this case study through multi-institutional qualitative or mixed-methods studies

  generalrecommendations
  Keywords: institutions institutional lecturing invest lecturers based private higher education develop formally communicate clear policy integration
• Influence of Artificial Intelligence–Supported Academic Advising on Academic Adjustment of First-Year Students in Universities in Oyo State (2026) · Aminu Kano Academic Scholars Association Multidisciplinary Journal · doi

  Based on the findings of the study, the following recommendations are made: i. Universities in Oyo State should institutionalize AI-supported academic advising systems to complement traditional face-to-face advising, particularly for first-year students who may require additional academic support and guidance. ii. University management should invest in AI infrastructure, including academic chatbots, predictive analytics systems, and intelligent advising platforms, to facilitate effective academic monitoring and early intervention strategies. iii. Orientation programmes for first-year students should incorporate training on the effective use of AI-supported academic tools to enhance students’ acceptance of technology and improve their academic adjustment. iv. Lecturers and academic advisers should be provided with continuous professional development opportunities to strengthen their capacity to integrate AI tools into academic guidance and advising practices. v. Higher education policymakers should develop clear ethical and operational guidelines for the implementation and use of AI in academic advising to ensure responsible, transparent, and effective utilization of these technologies. vi. Universities should establish regular monitoring and evaluation mechanisms to assess the effectiveness of AI-supported advising systems and make necessary improvements based on students’ needs and feedback. vii. Collaboration between technology developers, university administrators, and academic advisers should be encouraged to ensure that AI-supported advising platforms are user- friendly, accessible, and aligned with students’ academic needs. 303 Synergy of Ideas: AKASA Multidisciplinary Book Chapter Contributions Third Edition May – August, 2026. E-ISBN: 978-978-690-171-8 Email: [email protected] Web: akasa.com.ng

  generalrecommendations
  Keywords: academic advising students supported systems effective based universities face first year guidance university platforms monitoring
• Gender perspectives: Artificial intelligence in academic practice (2026) · Research in Pedagogy · doi

  The integration of AI into higher education poses challenges for academic staff, including the need for targeted training and support programs. The study highlights the importance of considering gender differences in AI tool use and perceptions when designing and implementing AI-based educational initiatives. The study's findings can inform the development of policies and strategies to promote equitable access to AI tools and resources in higher education.

  generalstated challengesevidence 5/5
  Keywords: integration higher education poses challenges academic staff including

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