Sub-Theme 1: Data for Demographic Dividends
Guiding Question: How can data infused systems accelerate equitable development for Africa’s growing youth population?
Africa’s youthful population represents a unique opportunity for a demographic dividend, yet realising this potential requires a higher education system that is as agile as it is data informed. This sub-theme explores how data-infused systems can act as the primary engine for accelerating equitable development across the continent. The main idea is to shift from retrospective reporting to proactive, predictive models. Institutions can identify and dismantle the structural barriers, such as digital competency gaps and mismatched skill sets, that hinder student success.
We invite discussions on how data can be leveraged to personalise learning at scale, align curricula with future-of-work demands, and ensure that the digital transition empowers every student, regardless of their background, to become a catalyst for Africa’s socio-economic renewal. This includes the use of management information systems and quality assurance data to monitor equity outcomes, inform enrolment planning, and evaluate the effectiveness of student success interventions. Contributions should clearly demonstrate how data is collected, analysed, and used to inform institutional planning, management, or quality assurance processes.
Topics may include:
- Using learner analytics to reduce dropout rates among marginalised youth.
- Data driven strategies for aligning higher education with youth employment needs.
- Ethical use of demographic data in university planning.
- Enrolment planning, access strategies, and student pipeline analysis
- Leveraging HEMIS data to identify student success risk factors.
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Sub-Theme 2: Ethical AI & Curriculum Futures
Guiding Question: What does a data infused, ethically grounded curriculum look like for every African graduate?
As AI and automated systems become integral to the professional landscape, the curriculum must evolve from a static collection of knowledge into a dynamic, data-responsive ecosystem. This sub-theme interrogates the design of learning pathways that integrate advanced digital competencies with a robust ethical compass. A data-infused curriculum goes beyond teaching technical proficiency; it embeds critical inquiry into data sovereignty, algorithmic bias, and the social implications of AI within the African context. We seek contributions that explore how institutions can cultivate graduates who are not only technically adept in data analysis and multimedia creation but are also ethically grounded leaders. The focus is on reimagining a future-ready curriculum that balances global technological trends with local values, ensuring that every African graduate is equipped to navigate and shape a digitally complex world with integrity and social responsibility.
Contributions may include academic planning, programme review, and quality assurance processes that use institutional data to evaluate curriculum effectiveness and ensure alignment with ethical and societal priorities. Contributions should clearly demonstrate how data is collected, analysed, and applied to inform institutional planning, management, or quality assurance processes.
Topics may include:
- Embedding AI ethics across disciplines (not just computer science).
- Curriculum models that balance technical skills with moral reasoning.
- Case studies of “ethics across the curriculum” initiatives in African universities.
- Preparing graduates for an AI augmented workplace without losing humanistic values.
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Sub-Theme 3: The Societal Data Campus
Guiding Question: When universities become data driven social actors, how do we ensure impact serves the common good?
This sub-theme explores the evolution of the "Societal Data Campus," in which higher education institutions transcend traditional boundaries to become active, data-driven catalysts for public progress. As universities harness the power of big data and predictive analytics, they move beyond internal administration to address external societal challenges, from local economic development to national policymaking. The guiding question challenges us to define the mechanisms of accountability and transparency necessary to ensure that this analytical power is directed toward the common good. We seek contributions that examine how the "responsive university" can leverage its data assets to foster community engagement, promote social justice, and drive evidence-based innovation, all while maintaining the public trust and ensuring that the benefits of data-infused transformation are shared equitably across society.
This includes the development and use of management information and quality assurance frameworks for institutional performance reporting, monitoring societal impact, and supporting evidence-informed policy and planning. Contributions should clearly demonstrate how data is collected, analysed, and used to inform institutional planning, management, or quality assurance processes.
Topics may include:
- University community partnerships that use data to address local challenges
- Governance frameworks for ethical data sharing and societal impact.
- Measuring social return on investment from data infused university projects.
- Avoiding data extractivism: protecting student and community data rights.
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Sub-Theme 4: Financial Planning & Institutional Data Resilience
Guiding Question: How can universities use predictive data models to achieve long term financial health while pursuing transformation?
This sub-theme addresses the critical tension between the high costs of digital transformation and the imperative of long-term institutional stability. In an era of fluctuating subsidies and rising operational demands, data resilience becomes a foundational requirement for survival and growth. This track explores how universities can shift from reactive budgeting to proactive financial stewardship by leveraging predictive data models. Analysing longitudinal trends in student success, resource allocation, and infrastructure needs, institutions can identify efficiencies that free up capital for transformative projects. We invite research and practical frameworks that demonstrate how data-driven insights can optimise enrolment management, mitigate the financial risks of student attrition, and create sustainable funding models that allow African HEIs to remain globally competitive without compromising their social mission.
This includes the use of HEMIS data, enrolment modelling, academic planning processes, and quality assurance reporting systems to support financial sustainability and institutional decision-making. Contributions should clearly demonstrate how data is collected, analysed, and used to inform institutional planning, management, or quality assurance processes.
Topics may include:
- Predictive analytics for enrolment, retention, and revenue forecasting.
- Balancing financial sustainability with investments in digital transformation.
- Data driven approaches to resource allocation for equity goals.
- Risk management and scenario planning using institutional data.
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Sub-Theme 5: Student Employability & AI Readiness
Guiding Question: Can data infused internship systems bridge the gap between youth potential and AI driven labour markets?
This sub-theme focuses on the critical transition from the classroom to the modern workforce, examining how the "responsive university" can leverage data and emerging technology to close the persistent gap between academic preparation and industry requirements. As artificial intelligence redefines global labour markets, traditional internship models must be reimagined as data-infused ecosystems that offer more than mere work experience. Making use of data to map student competencies against real-time industry demands, higher education institutions can create personalised, high-impact placement systems that prepare the youth demographic for an AI-augmented economy. We invite explorations into how digital tracking, virtual work-integrated learning, and AI-driven career matching can empower students, particularly those from marginalised backgrounds, to navigate shifting job landscapes, ensuring that youth potential is not just recognised but actively translated into sustainable, future-proof careers.
Contributions may include the use of graduate tracking systems, labour market intelligence, and quality assurance mechanisms to evaluate employability outcomes and inform academic planning and curriculum alignment. Contributions should clearly demonstrate how data is collected, analysed, and used to inform institutional planning, management, or quality assurance processes.
Topics may include:
- Platforms that match students to internships using skills and labour market data.
- Internships as spaces for developing AI literacy and ethical judgement.
- Employer university data partnerships for real time planning and curriculum alignment.
- Tracking graduate outcomes through longitudinal data systems.
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