🤖 Artificial Intelligence (AI) in Assessment
How artificial intelligence is transforming assessment design, delivery, marking, and analysis across education and professional certification.
Key Concepts
- **Productive offloading**: AI support that improves performance without removing the thinking the assessment is meant to evidence. - **Unproductive offloading**: AI support that replaces the cognitive work being assessed. - **Construct alignment**: the fit between the intended skill or knowledge and the work the learner must actually do. - **Critical thinking**: judgement based on evidence, not just recall of facts. - **Metacognitive equity gap**: the possibility that some learners are better …
Vendor Landscape
Supplier messaging generally frames automated item generation as a route to faster production and better scale. That is useful as a market signal, but it does not by itself validate item quality or defensibility. The current market story is stronger on efficiency than on independently demonstrated assessment performance.
Key Concepts
- **Remote proctoring**: monitoring candidates during an assessment, often through webcam, screen capture, or identity checks. - **Device control**: restricting what a candidate can do on a device during an assessment. - **Platform telemetry**: logging activity within a system to help detect unusual patterns or support review. - **Authenticity**: whether the assessment evidence really shows the candidate’s own work. - **Proportionality**: whether the level of surveillance is justified by the ris…
What Experts Agree On
The source set points to AI use being embedded in campus life rather than hypothetical. HEPI’s student survey suggests that student generative AI use is now part of higher education reality, which makes AI policy an assessment governance issue, not just an IT question. There is also broad practical agreement that institutions need shared rules and clearer staff and student guidance. Without that, acceptable use becomes inconsistent across departments and assessment validity is harder to defend.…
Key Sources
- HEPI, *Student Generative AI Survey 2026* — strongest source here on student use and institutional implications. - ChatEDU episodes on campus AI ecosystems, Google’s AI training investment, career dreaming with AI, robots in 2025, and distributed cognition — useful for sector discussion and framing, but closer to expert commentary than independent validation. - Vendor pages from Anthology, Aptem, Constructor, and Cornerstone OnDemand — useful as market signals about how suppliers are packaging…
Suggested Citation
Test Community Network. "Generative AI in credentialing assessments." TCN AI & Assessment Wiki. Last reviewed 2026-05-02. https://www.testcommunity.network/wiki/generative-ai-in-credentialing-assessments.html
Sources
- ChatEDU episode on campus AI ecosystems. - ChatEDU episode on Google's AI training investment. - ChatEDU episode on Google's new Gen AI career counsellor. - ChatEDU episode on emotional and conversational AI in education. - ChatEDU episode on distributed cognition and human-AI partnership. - EdTech Together London event listing. - PIE News article on Efekta Education. - HEPI Student Generative AI Survey 2026. - Anthology vendor source. - Aptem vendor source. - Constructor vendor source. - Corn…
Good Practice
1. Define exactly what thinking the assessment is meant to evidence. 2. Decide which forms of AI use preserve that evidence and which forms weaken it. 3. Write the permitted-use rule around the task’s cognitive demand, not around generic comfort with the tool. 4. Build tasks that make reasoning visible if independent judgement matters. 5. Separate learning support from evidence of capability when the qualification stakes are high. 6. Treat new correlational findings as a warning to design carefu…
Suggested Citation
Test Community Network. "Cognitive offloading and AI." TCN AI & Assessment Wiki. Last reviewed 2026-08-12. https://www.testcommunity.network/wiki/cognitive-offloading-and-ai.html
Key Concepts
- **Credential validity**: whether the award really measures the intended competence. - **Human oversight**: keeping people responsible for review, moderation, exception handling, and final accountability. - **Regulatory confidence**: whether external stakeholders can trust the process and the result. - **Product safety expectations**: the operational and governance controls suppliers are expected to meet before deployment. - **Academic integrity**: the principle that assessment evidence should …