Tag: AI literacy

Student Generative AI Survey 2026

GenAI:N3

Source

Higher Education Policy Institute (HEPI), Report 199, 2026

Summary

This HEPI report presents findings from a large-scale survey of UK higher education students on their use of generative artificial intelligence (GenAI), building on earlier surveys from 2024 and 2025. It shows that GenAI use is now widespread and normalised across the student population, with most students using AI tools regularly for tasks such as explaining concepts, summarising readings, generating ideas, and supporting writing. The report highlights a shift from experimental use to embedded study practice, with students increasingly viewing GenAI as a standard academic tool rather than an optional extra.

However, the findings also reveal a complex landscape of uneven skills, uncertainty, and institutional inconsistency. While many students report benefits in efficiency and understanding, concerns persist around overreliance, accuracy, and fairness. The report notes that guidance from institutions remains variable, with students often unclear about acceptable use in assessments. Importantly, the data suggests a growing expectation that universities should actively teach students how to use GenAI effectively and ethically, rather than simply regulate or restrict it. The report underscores the need for clearer policies, improved AI literacy, and assessment redesign that reflects real-world practices.

Key Points

  • The majority of students now use GenAI regularly in their studies.
  • Common uses include explaining concepts, summarising, and drafting work.
  • GenAI is becoming embedded as a standard academic tool.
  • Students report gains in efficiency, productivity, and understanding.
  • Concerns remain about accuracy, bias, and overreliance.
  • Institutional guidance on GenAI use is inconsistent or unclear.
  • Many students are uncertain about acceptable use in assessments.
  • There is strong demand for formal AI literacy education.
  • Assessment practices are not yet aligned with widespread AI use.
  • Equity issues arise from unequal access to tools and skills.

Conclusion

The HEPI Student Generative AI Survey 2026 highlights a decisive shift: generative AI is no longer emerging but embedded in student learning. The challenge for higher education is to move from reactive policy-making to proactive educational design—equipping students with the skills, clarity, and critical awareness needed to use AI responsibly and effectively in both academic and professional contexts.

Keywords

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URL

https://www.hepi.ac.uk/wp-content/uploads/2026/03/HEPI-Report-199-Gen-AI-Survey-2026.pdf

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Gen AI Reports

Ethical Guidelines on the Use of Artificial Intelligence (AI) and Data in Teaching and Learning for Educators

GenAI:N3

Source

European Commission: Directorate-General for Education, Youth, Sport and Culture, Guidelines on the ethical use of artificial intelligence and data in teaching and learning for educators, Publications Office of the European Union, 2026, https://data.europa.eu/doi/10.2766/7967834

Summary

These European Commission guidelines provide practical and ethical direction for educators using artificial intelligence (AI) and data-driven technologies in teaching and learning. Aimed primarily at school education but broadly applicable across educational contexts, the document emphasises that AI should enhance human-centred, inclusive, and equitable education. It introduces a structured framework to help educators critically assess AI tools, ensuring their use aligns with pedagogical goals, respects learners’ rights, and supports professional autonomy.

The guidelines are grounded in key ethical principles, including human agency, transparency, fairness, privacy, and accountability. They highlight the importance of developing AI literacy among educators and learners, enabling them to understand how AI systems function, what data they use, and what limitations they carry. A strong emphasis is placed on critical engagement—educators are encouraged to question AI outputs, address bias, and avoid overreliance on automated systems. The document also provides a practical self-reflection tool to support educators in evaluating AI tools across dimensions such as reliability, safety, inclusiveness, and educational value.

Key Points

  • AI should support human-centred, inclusive teaching and learning.
  • Educators retain responsibility for decisions made using AI tools.
  • Transparency and explainability are essential for trust in AI systems.
  • AI literacy is critical for both teachers and learners.
  • Data protection and privacy must comply with GDPR principles.
  • Bias and fairness must be actively monitored and mitigated.
  • Educators should critically evaluate AI outputs and limitations.
  • AI tools should align with pedagogical goals, not drive them.
  • A self-reflection framework supports responsible AI adoption.
  • Ethical use of AI requires ongoing professional development and awareness.

Conclusion

The guidelines position AI as a valuable but carefully bounded tool in education. By embedding ethical reflection, critical engagement, and human oversight into everyday practice, educators can harness AI’s benefits while protecting learner rights, educational integrity, and professional judgement.

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URL

https://op.europa.eu/en/publication-detail/-/publication/f692aa0b-17a7-11f1-8870-01aa75ed71a1

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Gen AI Reports

OECD Digital Education Outlook 2026

GenAI:N3

Source

OECD (2026), OECD Digital Education Outlook 2026: Exploring Effective Uses of Generative AI in Education, OECD Publishing, Paris, https://doi.org/10.1787/062a7394-en..

Summary

This flagship OECD report examines how generative artificial intelligence (GenAI) is reshaping education systems, with a strong emphasis on evidence-based uses that enhance learning, teaching, assessment, and system capacity. Drawing on international research, policy analysis, and design experiments, the report moves beyond hype to identify where GenAI adds genuine educational value and where it introduces risks. It highlights GenAI’s potential to support personalised learning, high-quality feedback, teacher productivity, and system-level efficiency, while cautioning against uses that displace cognitive effort or undermine deep learning.

A central theme is the need for hybrid human–AI approaches that preserve teacher autonomy, learner agency, and professional judgement. The report shows that GenAI can be effective when embedded in pedagogically grounded designs, such as intelligent tutoring, formative feedback, and collaborative learning, but harmful when used as a shortcut to answers. It also reviews national policy responses, noting a global shift towards targeted guidance, AI literacy frameworks, and proportionate regulation aligned with ethical principles, transparency, and accountability. The report calls for coordinated strategies that integrate curriculum reform, assessment redesign, professional development, and governance to ensure GenAI strengthens, rather than substitutes, human learning and expertise.

Key Points

  • GenAI can enhance personalised learning and feedback at scale when pedagogically designed.
  • Overreliance on GenAI risks reducing cognitive engagement and deep learning.
  • Hybrid human–AI models are essential to preserve teacher and learner agency.
  • Generative AI should support formative assessment rather than replace judgement.
  • AI literacy is a foundational skill for students, teachers, and leaders.
  • Teacher autonomy and professional expertise must be protected in AI integration.
  • Evidence-informed design is critical to avoid unintended learning harms.
  • National policies increasingly favour guidance over blanket bans.
  • Ethical principles, transparency, and accountability underpin responsible use.
  • Cross-system collaboration strengthens sustainable AI adoption.

Conclusion

The OECD Digital Education Outlook 2026 positions generative AI as a powerful but conditional force in education. Its impact depends not on the technology itself, but on how thoughtfully it is designed, governed, and integrated into learning ecosystems. By prioritising human-centred, evidence-based, and ethically grounded approaches, education systems can harness GenAI to improve quality and equity while safeguarding the core purposes of education.

Keywords

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URL

https://www.oecd.org/en/publications/oecd-digital-education-outlook-2026_062a7394-en.html

Summary generated by ChatGPT 5.2

Gen AI Reports

HEA – Generative AI in Higher Education Teaching & Learning: Policy Framework

GenAI:N3

Source

O’Sullivan, James, Colin Lowry, Ross Woods & Tim Conlon. Generative AI in Higher Education Teaching &
Learning: Policy Framework. Higher Education Authority, 2025. DOI: 10.82110/073e-hg66.

Summary

This policy framework provides a national, values-based approach to guiding the adoption of generative artificial intelligence (GenAI) in teaching and learning across Irish higher education institutions. Rather than prescribing uniform rules, it establishes a shared set of principles to support informed, ethical, and pedagogically sound decision-making. The framework recognises GenAI as a structural change to higher education—particularly to learning design, assessment, and academic integrity—requiring coordinated institutional and sector-level responses rather than ad hoc or individual initiatives.

Focused explicitly on teaching and learning, the framework foregrounds five core principles: academic integrity and transparency; equity and inclusion; critical engagement, human oversight, and AI literacy; privacy and data governance; and sustainable pedagogy. It emphasises that GenAI should neither be uncritically embraced nor categorically prohibited. Instead, institutions are encouraged to adopt proportionate, evidence-informed approaches that preserve human judgement, ensure fairness, protect student data, and align AI use with the public mission of higher education. The document also outlines how these principles can be operationalised through governance, assessment redesign, staff development, and continuous sector learning.

Key Points

  • The framework offers a shared national reference point rather than prescriptive rules.
  • GenAI is treated as a systemic pedagogical challenge, not a temporary disruption.
  • Academic integrity depends on transparency, accountability, and visible authorship.
  • Equity and inclusion must be designed into AI adoption from the outset.
  • Human oversight and critical engagement remain central to learning and assessment.
  • AI literacy is positioned as a core capability for staff and students.
  • Privacy, data protection, and institutional data sovereignty are essential.
  • Assessment practices must evolve beyond reliance on traditional written outputs.
  • Sustainability includes both environmental impact and long-term educational quality.
  • Ongoing monitoring and sector-wide learning are critical to responsible adoption.

Conclusion

The HEA Policy Framework positions generative AI as neither a threat to be resisted nor a solution to be uncritically adopted. By grounding AI integration in shared academic values, ethical governance, and pedagogical purpose, it provides Irish higher education with a coherent foundation for navigating AI-enabled change while safeguarding trust, equity, and educational integrity.

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URL

https://hea.ie/2025/12/22/hea-publishes-national-policy-framework-on-generative-ai-in-teaching-and-learning/

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Australian Framework for Artificial Intelligence in Higher Education

GenAI:N3

Source

Lodge, J. M., Bower, M., Gulson, K., Henderson, M., Slade, C., & Southgate, E. (2025). Australian Centre for Student Equity and Success, Curtin University

Summary

This framework provides a national roadmap for the ethical, equitable, and effective use of artificial intelligence (AI)—including generative and agentic AI—across Australian higher education. It recognises both the transformative potential and inherent risks of AI, calling for governance structures, policies, and pedagogies that prioritise human flourishing, academic integrity, and cultural inclusion. The framework builds on the Australian Framework for Generative AI in Schools but is tailored to the unique demands of higher education: research integrity, advanced scholarship, and professional formation in AI-enhanced contexts.

Centred around seven guiding principles—human-centred education, inclusive implementation, ethical decision-making, Indigenous knowledges, ethical development, adaptive skills, and evidence-informed innovation—the framework links directly to the Higher Education Standards Framework (Threshold Standards) and the UN Sustainable Development Goals. It emphasises AI literacy, Indigenous data sovereignty, environmental sustainability, and the co-design of equitable AI systems. Implementation guidance includes governance structures, staff training, assessment redesign, cross-institutional collaboration, and a coordinated national research agenda.

Key Points

  • AI in higher education must remain human-centred and ethically governed.
  • Generative and agentic AI should support, not replace, human teaching and scholarship.
  • Institutional AI frameworks must align with equity, inclusion, and sustainability goals.
  • Indigenous knowledge systems and data sovereignty are integral to AI ethics.
  • AI policies should be co-designed with students, staff, and First Nations leaders.
  • Governance requires transparency, fairness, accountability, and contestability.
  • Staff professional learning should address ethical, cultural, and environmental dimensions.
  • Pedagogical design must cultivate adaptive, critical, and reflective learning skills.
  • Sector-wide collaboration and shared national resources are key to sustainability.
  • Continuous evaluation ensures AI enhances educational quality and social good.

Conclusion

The framework positions Australia’s higher education sector to lead in responsible AI adoption. By embedding ethical, equitable, and evidence-based practices, it ensures that AI integration strengthens—not undermines—human expertise, cultural integrity, and educational purpose. It reaffirms universities as stewards of both knowledge and justice in an AI-shaped future.

Keywords

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URL

https://www.acses.edu.au/publication/australian-framework-for-artificial-intelligence-in-higher-education/

Summary generated by ChatGPT 5.1

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