Tag: Generative AI

Enacting Assessment Reform in a Time of Artificial Intelligence

GenAI:N3

Source

Tertiary Education Quality and Standards Agency (TEQSA), Australian Government

Summary

This resource addresses how Australian higher education can reform assessment in response to the rise of generative AI. Building on earlier work (Assessment Reform for the Age of Artificial Intelligence), it sets out strategies that align with the Higher Education Standards Framework while acknowledging that gen AI is now ubiquitous in student learning and professional practice. The central message is that detection alone is insufficient; instead, assessment must be redesigned to assure learning authentically, ethically, and sustainably.

The report outlines three main pathways: (1) program-wide assessment reform, which integrates assessment as a coherent system across degrees; (2) unit/subject-level assurance of learning, where each subject includes at least one secure assessment task; and (3) a hybrid approach combining both. Each pathway carries distinct advantages and challenges, from institutional resourcing and staff coordination to maintaining program coherence and addressing integrity risks. Critical across all approaches is the need to balance immediate integrity concerns with long-term goals of preparing students for an AI-integrated future.

Key Points

  • Generative AI necessitates structural assessment reform, not reliance on detection.
  • Assessments must equip students to participate ethically and critically in an AI-enabled society.
  • Assurance of learning requires multiple, inclusive, and contextualised approaches.
  • Program-level reform provides coherence and alignment but demands significant institutional commitment.
  • Unit-level assurance offers quick implementation but risks fragmentation.
  • Hybrid approaches balance flexibility with systemic assurance.
  • Over-reliance on traditional supervised exams risks reducing authenticity and equity.
  • Critical questions must guide reform: alignment across units, disciplinary variation, and student experience.
  • Assessment must reflect authentic professional practices where gen AI is legitimately used.
  • Ongoing collaboration and evidence-sharing across the sector are vital for sustainable reform.

Conclusion

The report concludes that assessment reform in the age of AI is not optional but essential. Institutions must move beyond short-term fixes and design assessment systems that assure learning, uphold integrity, and prepare students for future professional contexts. This requires thoughtful strategy, collaboration, and a willingness to reimagine assessment as a developmental, systemic, and values-driven practice.

Keywords

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URL

https://www.teqsa.gov.au/guides-resources/resources/corporate-publications/enacting-assessment-reform-time-artificial-intelligence

Summary generated by ChatGPT 5

Gen AI Reports

NSW public school students to get access to state-of-the-art generative AI app

GenAI:N3
A diverse group of cheerful public school students in a modern classroom is excitedly gathered around a teacher. The teacher holds a large, glowing tablet displaying a generative AI interface with a 'CREATE' icon. In the background, a large screen shows a variety of AI-generated content (images, text, music notes), and the Sydney skyline is visible through a large window. The scene symbolises public school students gaining access to advanced AI technology. Generated by Nano Banana.
In a significant step forward for public education, students in New South Wales are set to gain access to a state-of-the-art generative AI app. This image envisions a future classroom where students and teachers collaborate using powerful AI tools, highlighting a new era of learning and creativity in Australian schools. Image (and typos) generated by Nano Banana.

Source

CyberDaily.au

Summary

The New South Wales government in Australia is rolling out a generative AI app across public schools to support students in areas like writing, problem solving, and research. The aim is to help with learning and reduce educational inequality—particularly for those with fewer resources. Officials emphasise that the app will supplement—not replace—teaching, with controls in place to prevent outright cheating. Teachers will receive training on appropriate use, and the pilot includes oversight and evaluation to monitor impacts, equity, and risk.

Key Points

  • NSW public schools will gain access to a generative AI app intended as a learning support tool, not a replacement for instruction.
  • The rollout aims to reduce disparity: assist students who may lack advanced tutors, help with writing, research, structuring work.
  • Safeguards include teacher training, monitoring, and policies to restrict misuse or overreliance.
  • The government will pilot the programme to evaluate outcomes: learning improvements, equity effects, and unintended harms.
  • The introduction reflects a shift from resisting AI to integrating it thoughtfully at the school level.

Keywords

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URL

https://www.cyberdaily.au/government/12672-nsw-public-school-students-to-get-access-to-state-of-the-art-generative-ai-app

Summary generated by ChatGPT 5

GenAI News

Generative AI isn’t culturally neutral, research finds

GenAI:N3
A diverse group of four researchers in a lab setting surrounds a large, glowing, circular holographic projection. The projection shows a series of icons, some representing Western culture (a statue of liberty, a hamburger), and others from different cultures (a statue of a Buddha, a bowl of ramen), with data flow lines moving between them. A central red line cuts through the center of the display, indicating a lack of neutrality. The image visualizes the finding that generative AI is not culturally neutral. Generated by Nano Banana.
As generative AI tools become more integrated into our lives, new research highlights a critical finding: these technologies are not culturally neutral. This image visualizes how AI’s training data can embed cultural biases, underscoring the vital need for diverse representation and ethical oversight in the development of future AI systems. Image (and typos) generated by Nano Banana.

Source

MIT Sloan (Ideas Made to Matter)

Summary

A study led by MIT Sloan’s Jackson Lu and collaborators shows that generative AI models like GPT and Baidu’s ERNIE respond differently depending on the language of the prompt, reflecting cultural leanings embedded in their training data. When asked in English, responses tended toward an independent, analytic orientation; in Chinese, they skewed toward interdependent, holistic thinking. Those differences persist across social and cognitive measures, and even subtle prompt framing (asking the AI “to assume the role of a Chinese person”) can shift outputs. The finding means users and organisations should be aware of—and guard against—hidden cultural bias in AI outputs.

Key Points

  • AI models exhibit consistent cultural orientation shifts depending on prompt language: English prompts lean independent/analytic; Chinese prompts lean interdependent/holistic.
  • These cultural tendencies appear in both social orientation (self vs group) and cognitive style (analysis vs context) tests.
  • The cultural bias is not fixed: prompting the model to “assume the role of a Chinese person” moves responses toward interdependence even in English.
  • Such biases can influence practical outputs (e.g. marketing slogans, policy advice), in ways users may not immediately detect.
  • The study underscores the need for cultural awareness in AI deployment and places responsibility on developers and users to mitigate bias.

Keywords

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URL

https://mitsloan.mit.edu/ideas-made-to-matter/generative-ai-isnt-culturally-neutral-research-finds

Summary generated by ChatGPT 5

GenAI News

How AI can drive tailored learning

GenAI:N3
A smiling student wearing futuristic glasses interacts with a holographic display showing a 'Personalized Learning Path' with graphs and DNA-like structures. In the background, other students are engaged in a modern classroom setting, and a screen displays 'Cognitive Adaptation' with a brain icon. The image illustrates AI's role in individualized education. Generated by Nano Banana.
AI is revolutionising education by creating personalised learning paths that adapt to each student’s unique needs and pace. This image depicts a student engaging with an AI-driven interface, highlighting how technology can foster individualised growth and a more effective learning experience in modern classrooms. Image generated by Nano Banana.

Source

Times Higher Education

Summary

In this piece, Andreas Rausch argues that generative AI (GenAI) should be integrated into business and higher education in ways that promote tailored learning without losing the human touch. He emphasises that AI can enhance problem-solving skills, adapt content to individual student needs, and help instructors personalise feedback. But Rausch warns that over-reliance on AI risks eroding essential skills such as creativity, ethical judgement, and interpersonal communication. The article calls for balance: using AI to support learning, not replace human instructors, and designing AI-augmented pedagogy that preserves reflective, human elements while enhancing flexibility and engagement.

Key Points

  • GenAI can help personalise content and feedback, making learning more adaptive to individual progress.
  • Focus on enhancing business students’ problem-solving skills rather than automating them away.
  • There is a risk that AI use, if unmanaged, may diminish human qualities like ethical judgement, reflection, and creativity.
  • Teachers’ role becomes even more important: guiding students through AI outputs, maintaining human connection in learning.
  • Institutional implementation should be thoughtful: adequate training, governance, and ensuring AI is a tool—not a crutch.

Keywords

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URL

https://www.timeshighereducation.com/campus/how-ai-can-drive-tailored-learning

Summary generated by ChatGPT 5

GenAI News

Generative AI in Higher Education Teaching and Learning: Sectoral Perspectives

GenAI:N3

Source

Higher Education Authority

Summary

This report, commissioned by the Higher Education Authority (HEA), captures sector-wide perspectives on the impact of generative AI across Irish higher education. Through ten thematic focus groups and a leadership summit, it gathered insights from academic staff, students, support personnel, and leaders. The findings show that AI is already reshaping teaching, learning, assessment, and governance, but institutional responses remain fragmented and uneven. Participants emphasised the urgent need for national coordination, values-led policies, and structured capacity-building for both staff and students.

Key cross-cutting concerns included threats to academic integrity, the fragility of current assessment practices, risks of skill erosion, and unequal access. At the same time, stakeholders recognised opportunities for AI to enhance teaching, personalise learning, support inclusion, and free staff time for higher-value educational work. A consistent theme was that AI should not be treated merely as a technical disruption but as a pedagogical and ethical challenge that requires re-examining educational purpose.

Key Points

  • Sectoral responses to AI are fragmented; coordinated national guidance is urgently needed.
  • Generative AI challenges core values of authorship, originality, and academic integrity.
  • Assessment redesign is necessary—moving towards authentic, process-focused approaches.
  • Risks include skill erosion in writing, reasoning, and information literacy if AI is overused.
  • AI literacy for staff and students must go beyond tool use to include ethics and critical thinking.
  • Ethical use of AI requires shared principles, not just compliance or detection measures.
  • Inclusion is not automatic: without deliberate design, AI risks deepening inequality.
  • Staff feel underprepared and need professional development and institutional support.
  • Infrastructure challenges extend beyond tools to governance, procurement, and policy.
  • Leadership must shape educational vision, not just manage risk or compliance.

Conclusion

Generative AI is already embedded in higher education, raising urgent questions of purpose, integrity, and equity. The consultation shows both enthusiasm and unease, but above all a readiness to engage. The report concludes that a coordinated, values-led, and inclusive approach—balancing innovation with responsibility—will be essential to ensure AI strengthens, rather than undermines, Ireland’s higher education mission.

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URL

https://hea.ie/2025/09/17/generative-ai-in-higher-education-teaching-and-learning-sectoral-perspectives/

Summary generated by ChatGPT 5

Gen AI Reports