Tag: Assessment

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

Summary generated by ChatGPT 5.3

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

We Asked Teachers About Their Experiences With AI in the Classroom — Here’s What They Said

GenAI:N3
A digital illustration showing a diverse group of teachers sitting around a conference table in a modern classroom, each holding a speech bubble or screen displaying various short, contrasting statements about AI, such as "HELPFUL TOOL," "CHEAT DETECTOR," and "TIME SINK." Image (and typos) generated by Nano Banana.
Diverse perspectives on the digital frontier: Capturing the wide range of experiences and opinions shared by educators as they navigate the benefits and challenges of integrating AI into their classrooms. Image (and typos) generated by Nano Banana.

Source

The Conversation

Summary

Researcher Nadia Delanoy interviewed ten Canadian teachers to explore how generative AI is reshaping K–12 classrooms. The teachers, spanning grades 5–12 across multiple provinces, described mounting pressures to adapt amid ethical uncertainty and emotional strain. Common concerns included the fragility of traditional assessment, inequitable access to AI tools, and rising workloads compounded by inadequate policy support. Many expressed fear that AI could erode the artistry and relational nature of teaching, turning it into a compliance exercise. While acknowledging AI’s potential to enhance workflow, teachers emphasised the need for slower, teacher-led, and ethically grounded implementation that centres humanity and professional judgment.

Key Points

  • Teachers report anxiety over authenticity and fairness in assessment.
  • Equity gaps widen as some students have greater AI access than others.
  • Educators feel policies treat them as implementers, not professionals.
  • AI integration adds to burnout, threatening teacher autonomy.
  • Responsible policy must involve teachers, ethics, and slower adoption.

Keywords

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URL

https://theconversation.com/we-asked-teachers-about-their-experiences-with-ai-in-the-classroom-heres-what-they-said-265241

Summary generated by ChatGPT 5

GenAI News

How AI Is Challenging the Credibility of Some Online Courses

GenAI:N3
A digital illustration of a diploma or certificate with a prominent "CERTIFIED" seal, but the document is visibly fraying and breaking apart into digital code and pixels. A small, glowing AI chatbot icon hovers near the broken area, symbolizing the erosion of credibility. Image (and typos) generated by Nano Banana.
Questioning the digital degree: AI-generated work is forcing educators to reassess the integrity and perceived value of completion certificates for online courses. Image (and typos) generated by Nano Banana.

Source

The Conversation

Summary

Mohammed Estaiteyeh argues that generative AI has exposed fundamental weaknesses in asynchronous online learning, where instructors cannot observe students’ thinking or verify authorship. Traditional assessments—discussion boards, reflective posts, essays, and multimedia assignments—are now easily replaced or augmented by AI tools capable of producing personalised, citation-matched work indistinguishable from human output. Detection tools and remote proctoring offer little protection and raise serious equity and ethical issues. Estaiteyeh warns that without systemic redesign, institutions risk issuing credentials that no longer guarantee genuine learning. He advocates integrating oral exams, experiential learning with external verification, and programme-level redesign to maintain authenticity and uphold academic integrity in the AI era.

Key Points

  • Asynchronous online courses face the highest risk of undetectable AI substitution.
  • Discussion boards, reflections, essays, and even citations can be convincingly AI-generated.
  • AI detectors and remote proctoring are unreliable, inequitable, and ethically problematic.
  • Oral exams and experiential assessments offer partial safeguards but require major redesign.
  • Institutions must invest in structural change or risk turning asynchronous programmes into “credential mills.”

Keywords

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URL

https://theconversation.com/how-ai-is-challenging-the-credibility-of-some-online-courses-264851

Summary generated by ChatGPT 5

GenAI News

This Professor Let Half His Class Use AI. Here’s What Happened

GenAI:N3
A split classroom scene with a professor in the middle, presenting data. The left side, labeled "GROUP A: WITH AI," shows disengaged students with "F" grades. The right side, labeled "GROUP B: NO AI," shows engaged students with "A+" grades, depicting contrasting outcomes of AI use in a classroom experiment. Image (and typos) generated by Nano Banana.
An academic experiment unfolds: Visualizing the stark differences in engagement and performance between students who used AI and those who did not, as observed by one professor. Image (and typos) generated by Nano Banana.

Source

Gizmodo

Summary

A study by University of Massachusetts Amherst professor Christian Rojas compared two sections of the same advanced economics course—one permitted structured AI use, the other did not. The results revealed that allowing AI under clear guidelines improved student engagement, confidence, and reflective learning but did not affect exam performance. Students with AI access reported greater efficiency and satisfaction with course design while developing stronger habits of self-correction and critical evaluation of AI outputs. Rojas concludes that carefully scaffolded AI integration can enrich learning experiences without fostering dependency or academic shortcuts, though larger studies are needed.

Key Points

  • Structured AI use increased engagement and confidence but not exam scores.
  • Students used AI for longer, more focused sessions and reflective learning.
  • Positive perceptions grew regarding efficiency and instructor quality.
  • AI integration encouraged editing, critical thinking, and ownership of ideas.
  • Researchers stress that broader trials are required to validate results.

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URL

https://gizmodo.com/this-professor-let-half-his-class-use-ai-heres-what-happened-2000678960

Summary generated by ChatGPT 5

GenAI News