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days ago"},{"type":"web_search_result","title":"How much do 15-year-olds learn over one year of schooling?","url":"https://www.oecd.org/content/dam/oecd/en/publications/reports/2021/10/how-much-do-15-year-olds-learn-over-one-year-of-schooling_bf040ad5/b837fd6a-en.pdf","encrypted_content":"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","page_age":null},{"type":"web_search_result","title":"Mediabias","url":"https://mediabias.news/politics/global-student-performance-hits-lowest-point-in-25-years","encrypted_content":"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days ago"},{"type":"web_search_result","title":"Students who don’t use AI are ahead on every measure","url":"https://pivot-to-ai.com/2026/09/08/students-who-dont-use-ai-are-ahead-on-every-measure/","encrypted_content":"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","page_age":"2 days ago"},{"type":"web_search_result","title":"Pivot to AI – It can't be that stupid, you must be prompting it wrong","url":"https://pivot-to-ai.com/","encrypted_content":"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","page_age":null}],"caller":{"type":"direct"}},{"type":"text","text":"I have solid material to write the analysis now. The OECD itself and multiple secondary sources explicitly frame this as correlational, not causal, and note reverse-causation/confounding explanations.\n\nCONTEXT_BOT_DRAFT\ntitle: Is the OECD AI-scores link causal?\ncompact_reply: No — OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors (motivation, prior achievement, assignment type) remain uncontrolled.\nCONTEXT_BOT_DRAFT_END\n\n## Bottom line\n\n**No, the association shown in that chart is not established as causal — and the OECD says so explicitly.** The report describes a correlation between self-reported AI use for drafting writing assignments and PISA science scores, not a causal effect of AI use on achievement. It is likely strong partly because of **reverse causation and selection effects**: students who are already struggling academically (and thus already score lower) may be more likely to lean on AI to complete work they find difficult, rather than AI use causing the lower scores. The socioeconomic-status adjustment shown in the second (light blue) line in the graph narrows the gap somewhat but does not eliminate it, meaning other unmeasured confounders (motivation, prior achievement, teacher quality, assignment difficulty, self-selection into AI use) likely still explain much of what remains.\n\n## What the OECD itself says\n\nThe OECD's own PISA 2025 report is careful to hedge causal language. "},{"citations":[{"type":"web_search_result_location","cited_text":"PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores...","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html","title":"PISA 2025 Results (Volume I) | OECD","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDF89H8j6YJ1joE1DGBoMXFM7V8niiSD+6fM6IjDqPfE7obOXQwbDjTCwBCyXYU5MYBnSbWWLCgpZd8JMDe22kI4p4fnLMvJGoFzROdsqEz1IaFC7R9pWOeGizkilXd/7aQoYBA=="}],"type":"text","text":"PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI."},{"type":"text","text":" The magnitude cited matches the tweet: "},{"citations":[{"type":"web_search_result_location","cited_text":"In these scenarios, students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schoo...","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html","title":"PISA 2025 Results (Volume I) | OECD","encrypted_index":"EpABCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDGNh9i+aIl1X8UjbBxoMl0t6KtdegP7mu1t1IjBdkl086jaQu1kzgbtZcdsRxX53HrK/EkgWkBt2C0293ypdHdZZRahrhbgPW4lJr5kqFB4XJ0tLxuLvX2DrGQhVDu97qHUMGAQ="}],"type":"text","text":"students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers."},{"type":"text","text":"\n\nBut the same report and its press coverage stress the \"complex\" and non-random nature of this relationship: "},{"citations":[{"type":"web_search_result_location","cited_text":"How AI use relates to student performance is complex, varying with how students use it and what for. ","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html","title":"PISA 2025 Results (Volume I) | OECD","encrypted_index":"EpABCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDM1ztrAa/XgturD8/RoMpIso/mBFSCyYZGd9IjD4UEk318njMgO+Wi2UIUcNwP/xKU9D59n+CWQThJ39nx8bn23JWiflZfKOaOn///EqFPSZJE+Vbf8daz+oza2AZPSxBss0GAQ="}],"type":"text","text":"how AI use relates to student performance is complex, varying with how students use it and what for."},{"type":"text","text":" Crucially, "},{"citations":[{"type":"web_search_result_location","cited_text":"However, weekly users of AI for general purposes have similar performance outcomes to non-users. ","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html","title":"PISA 2025 Results (Volume I) | OECD","encrypted_index":"EpEBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDC0ePZRTA73RiIVMjRoMhCg43V9SWczANA7JIjD8+Kdblk3B6tFRdj+21U1URnTtYLx8Uvhm0p7g2tyfT8f4WUsLC1/6+hBXbzfdFawqFZemgM2qFRZMk2IMwF8kLeMMtDJpqRgE"}],"type":"text","text":"weekly users of AI for general purposes have similar performance outcomes to non-users,"},{"type":"text","text":" and "},{"citations":[{"type":"web_search_result_location","cited_text":"Students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly hig...","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html","title":"PISA 2025 Results (Volume I) | OECD","encrypted_index":"EpQBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDLySJC7tEtgjoQzKphoM8a1IX0Tup8+9qLSQIjDKcjEtEYOb+mF8YEdnlj9fm+7mmmmRZ4AscsZPosd2x3oVW6SFv3FkhwZybptloowqGNw9H0JTA3Y+ufqGaETF2QwNhWyk0nEq9hgE"}],"type":"text","text":"students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science — though these opportunities are more common among socio-economically advantaged students."},{"type":"text","text":" This nuance (non-monotonic pattern, benefits when paired with AI-literacy instruction) is inconsistent with a simple \"AI use directly damages learning\" causal story and instead points to effect modification by context and skill.\n\n## Explicit \"correlation, not causation\" statements from analysts covering the report\n\nMultiple outlets summarizing the PISA release explicitly flag the correlational nature of the data:\n\n- "},{"citations":[{"type":"web_search_result_location","cited_text":"The findings show an association rather than proof that AI use raises or lowers achievement.\n\n","url":"https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/","title":"Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDPdPfKb7viHBV9AqDBoMJ9Iqr56hitB9oUi9IjB493LE5ZaLvq+1jaZlqcIbah0cuJwYg/SJjT9S2jKLEPyPcO/yXE2jtpH2wAwqh4UqE5Y9BtfKF2v4kM9G9j7BOslsDPwYBA=="}],"type":"text","text":"The findings show an association rather than proof that AI use raises or lowers achievement."},{"type":"text","text":"\n- "},{"citations":[{"type":"web_search_result_location","cited_text":"The OECD’s PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores. ","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDDV8B6GdZ6GqGhkhdxoMu3K4eFWo1t4A2eTLIjDsIDvakjKWER0LnQTYRQA/r0nUe8Q+il3bUrgqpq2aIXgFALnSWlrMPqC6YpBUc08qE++HRJNL40fLX96LUVHnD0CrpvEYBA=="}],"type":"text","text":"The OECD's PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores."},{"type":"text","text":"\n- "},{"citations":[{"type":"web_search_result_location","cited_text":"The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. [7] The OECD adjusted its sc...","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","encrypted_index":"EpEBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDFXKRro/qNwsG+cv2BoMV5uSs0oul2Y5YZ7NIjBC/8/oaIPNyD2fiPghOB96Q0gLe5sHXYWBNaMI+XghH8g+OodKsm1Z6W3rIRcfoKAqFdtbID1bJ+L5uaTYJ2lzUutRZFVLYhgE"}],"type":"text","text":"The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. The OECD adjusted its science comparisons for students' socioeconomic status, but says the relationships do not necessarily show a negative effect from AI."},{"type":"text","text":"\n- "},{"citations":[{"type":"web_search_result_location","cited_text":"Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive....","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDMX6VeQ4CQs02XR1FBoMUR1TB89l4E/NcMP0IjA3G6FJBgVKWkjj3gUefNN/LmbNMUuNSwJNoEuhuOy6ltnCsSFiya44gfFWA2tfNwEqE6WBLMbrL1vLthk7/Y3pioA2eW8YBA=="}],"type":"text","text":"Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive."},{"type":"text","text":"\n\nThis last point is the core mechanism analysts point to for **why the association could be strong without being causal**: PISA is an observational, cross-sectional survey (students self-report their AI use and take a test at one point in time). There is no random assignment, no experimental manipulation, and no way to rule out that weaker students select into heavier AI use — for example, using a chatbot specifically because they struggle to draft or summarize on their own — which would produce exactly this pattern (non-users scoring highest) even if AI use itself had zero or even a positive effect on learning for a given student.\n\n## Additional nuance in the data that supports a \"not simply causal\" reading\n\n- The relationship is **not linear/monotonic** across all task types. For \"using AI to help me learn,\" "},{"citations":[{"type":"web_search_result_location","cited_text":"The one exception was using AI “to help me learn” as students using it about weekly scored highest, at around 500 points, and non-users came second, s...","url":"https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/","title":"Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDOOLdQsaqxeE04BQCxoMPkrPgkZVAa3wJO8kIjBknGq62Xqg/yEsP6w2cXggbUwl/002eXMckHp6fyJa4JFMn3tw1Tw6rEIH5zYejpAqE38glApqW8DJOP92CyKSHaxxaU4YBA=="}],"type":"text","text":"using it about weekly scored highest, at around 500 points, and non-users came second, slightly below the top one."},{"type":"text","text":" A purely harmful causal effect would predict monotonic decline with more use across all use-cases, but it doesn't.\n- Quality of use and instruction matters: "},{"citations":[{"type":"web_search_result_location","cited_text":"Among frequent users, however, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to...","url":"https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html","title":"PISA 2025: Students’ reading and mathematics performance declined sharply across the OECD","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDO+WGpV4zlORy+c3GhoMq3wmkIZ/RIqhfPIKIjCl8AeOA4U+vmuJ6O5NC9oIWyR8nkXa8qVFynOCLaOSJbopXs+G4lgk2nnEYLfUjagqEwSMcG/FE7uRzyrpVP46ib6zYcgYBA=="}],"type":"text","text":"among frequent users, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to perform better than those who received no such guidance."},{"type":"text","text":" Similarly, "},{"citations":[{"type":"web_search_result_location","cited_text":"The report also notes that 20 points on PISA's scale is roughly equal to one year of schooling. Another notable pattern: for students using AI every d...","url":"https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/","title":"OECD: Heavy AI Use Linked to Lower Science Scores","encrypted_index":"EpIBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDAa4rl3bDGV6dwMwlxoMosDhEkVwLSS5XXKeIjDjWjucc+A7/9KM6UFUi1RuorhI6ttaUQj2VurZ3sZrNsqzTyz+0BpWEUDw2jwMY7YqFrXzDrqnbNdgBHEbL1lR86v/yZNrcfUYBA=="}],"type":"text","text":"20 points on PISA's scale is roughly equal to one year of schooling, and for students using AI every day, science scores are higher by 13 points — equivalent to over half a year of instruction — when classes consistently ask them to critique AI-produced content."},{"type":"text","text":" This suggests the relationship is moderated heavily by *how* AI is used and taught, not simply *whether* it's used — again cutting against a single, uniform causal \"AI harms learning\" story.\n- The OECD's Andreas Schleicher framed the underlying concern in terms of cognitive engagement rather than asserting a direct causal test: "},{"citations":[{"type":"web_search_result_location","cited_text":"Andreas Schleicher, the OECD's Director for Education and Skills, put it bluntly: \"In the same way that we do not become fit by watching sports but by...","url":"https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/","title":"OECD: Heavy AI Use Linked to Lower Science Scores","encrypted_index":"EpIBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDJMlTYTHsAWoi0CVhxoMdtSWSIONdelvOfW4IjC5QintcR5C/kY73aWQnV+5zbckFrnxfqOfSzME65TzIg51IZGt1+fPzMKECHD76PoqFklCbb0Knix3eSI8g3f+XctYTidN4g4YBA=="}],"type":"text","text":"\"In the same way that we do not become fit by watching sports but by doing sports, learning does not occur through the consumption of content, but as a productive cognitive struggle of the mind with new material.\" His advice for classrooms: treat AI as support, not a substitute. \"Where technology enables or enhances that cognitive struggle, students will advance. Where technology short-circuits the productive struggle of learning, it will undercut students' development.\""},{"type":"text","text":" This is a theoretical/plausibility argument for a causal channel, not evidence that this survey design has demonstrated it.\n\n## Why the SES adjustment (the two lines in the chart) doesn't settle causality\n\nThe chart in the thread shows two lines — raw and SES-adjusted scores — and adjusting for socioeconomic status **narrows the gap somewhat but leaves a substantial gap intact** (e.g., one write-up reports "},{"citations":[{"type":"web_search_result_location","cited_text":"Students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test. Daily users scored 481. That's a...","url":"https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/","title":"OECD Finds Students Who Use AI Chatbots Daily Score Far Worse on Tests - Startup Fortune","encrypted_index":"EpEBCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDIg9zAFMAjlkdOPwZBoMQZLUAYmxohZRShr4IjDBN6i6a6v8u6IYk4mqfWfB4n4Ah18zVxaQntKWvJkiqnQ5iN9m7se4Qi7KdAuCHBYqFZINxiTWYtEt99QXbcR0hHmEF2GElxgE"}],"type":"text","text":"students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test, daily users scored 481, a 28-point gap adjusted for socioeconomic background, which the OECD says is roughly equivalent to a year and a half of teaching lost"},{"type":"text","text":"). Controlling for SES rules out one obvious confound (family wealth/background), but it does not rule out others like: baseline academic ability/motivation, whether a student's school assigns different amounts of AI-eligible work, self-selection by weaker students into heavier reliance on tools, or reverse causation. As one summary succinctly put it: "},{"citations":[{"type":"web_search_result_location","cited_text":"Students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science tha...","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","encrypted_index":"Eo8BCioIExgCIiRmYzhlYTgzMy05NjkwLTQ2NTUtYTM0Yy04NjM0ZDRkNWYyNTcSDNU49vwjjQlcPdStrRoMFWUhH9kUtrGo/GkMIjDqkfoaRHeKdroY4vwXW2rW1uWkt6na92CsVCG/mLFO6rC6JD8R8laDbEJ3fsqdgCkqE1R0Agog0Z6TScrLK472FPsGT7MYBA=="}],"type":"text","text":"students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science than non-users, after adjustment for socioeconomic status."},{"type":"text","text":" \"After adjustment for SES\" is not the same as \"after adjustment for all plausible confounders.\"\n\n## Conclusion\n\n- **Causal or not:** The OECD explicitly frames this as an association/correlation, not a demonstrated causal effect, and multiple independent write-ups of the same report reiterate that caveat.\n- **Why the correlation is strong despite likely not being (purely) causal:** The leading explanations are (1) reverse causation/self-selection — struggling students may turn to AI more for tasks like drafting or summarizing precisely because they need the help, so the causal arrow may run partly from \"weaker student\" → \"more AI use\" rather than the other way; (2) uncontrolled confounders beyond SES, such as motivation, prior achievement, and school/assignment differences; and (3) heterogeneity in *how* AI is used — the pattern flips or weakens for general-purpose/moderate use and for classrooms that teach students to critically evaluate AI output, which is inconsistent with a single uniform causal mechanism of \"AI use lowers scores.\"\n- This is a genuinely contested interpretive question in the underlying report itself and in expert commentary — the OECD does not claim causality, but some commentators (and headlines) are already presenting the correlation more starkly than the data alone can support."}],"container":null,"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":4,"cache_creation_input_tokens":24540,"cache_read_input_tokens":10026,"cache_creation":{"ephemeral_5m_input_tokens":24540,"ephemeral_1h_input_tokens":0},"output_tokens":3268,"output_tokens_details":{"thinking_tokens":153},"service_tier":"standard","inference_geo":"global","server_tool_use":{"web_search_requests":2,"web_fetch_requests":0}}}","received_at":"2026-09-10T22:55:58.795651Z","duration_ms":37354,"invocation_id":58,"attempt_key":"invocation-58-attempt-1-research","budget_entry_id":109,"metadata_blob":"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","storage_bytes":67226},{"id":110,"status":200,"metadata":{"attempt_key":"invocation-58-attempt-2-structure","duration_ms":67908,"headers":{"anthropic-ratelimit-input-tokens-limit":["10000000"],"anthropic-ratelimit-input-tokens-remaining":["9996000"],"anthropic-ratelimit-input-tokens-reset":["2026-09-10T22:56:00Z"],"anthropic-ratelimit-output-tokens-limit":["2000000"],"anthropic-ratelimit-output-tokens-remaining":["1999000"],"anthropic-ratelimit-output-tokens-reset":["2026-09-10T22:57:06Z"],"anthropic-ratelimit-requests-limit":["10000"],"anthropic-ratelimit-requests-remaining":["9999"],"anthropic-ratelimit-requests-reset":["2026-09-10T22:55:58Z"],"anthropic-ratelimit-tokens-limit":["12000000"],"anthropic-ratelimit-tokens-remaining":["11995000"],"anthropic-ratelimit-tokens-reset":["2026-09-10T22:56:00Z"],"content-type":["application/json"],"request-id":["req_011CevapfXFqFjAfuWBmDzKF"]},"kind":"structure","received_at":"2026-09-10T22:57:06.724974Z","status":200},"kind":"structure","inserted_at":"2026-09-10T22:57:06.726162Z","updated_at":"2026-09-10T22:57:06.726162Z","raw_body":"{"model":"claude-sonnet-5","id":"msg_011CevapfoP58xreGeEzQnDb","type":"message","role":"assistant","content":[{"type":"text","text":"{\"compact_reply\":\"No — OECD itself calls this an association, not proof AI causes lower scores. Likely reverse causation: struggling students may lean on AI to draft work they can't do alone, while stronger students need it less. SES-adjustment narrows the gap but doesn't erase it; other confounders remain uncontrolled.\",\"disposition\":\"reply\",\"title\":\"Is the OECD AI-scores link causal?\"}\n\nConsider\n\nRound 21 - Modeling assistant behaviors and constraints in JSON\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:15.8k results:1.5k\n\nRound 21 focuses on structured JSON output for AI assistant behavior, evaluated across 15,800 prompt tokens and 1,500 result tokens. This benchmark round tests how effectively different models handle modeling assistant behaviors and constraints in json.\n\nPerformance rankings in this table are calculated using a composite scoring algorithm that weighs multiple factors including task completion accuracy, response latency, and resource utilization efficiency. Models are ranked according to their overall performance across these evaluated dimensions, providing a comprehensive view of capability across different providers and model architectures.\n\nThe results in this benchmark demonstrate meaningful differences in how various models approach modeling assistant behaviors and constraints in json. These variations highlight the importance of selecting appropriate models based on specific use case requirements, as performance characteristics can vary significantly across different task types and complexity levels.\n\nUnderstanding these benchmark results helps developers and organizations make informed decisions when choosing models for production applications. Consider factors such as the specific requirements of your use case, acceptable latency thresholds, and budget constraints alongside raw performance metrics when selecting a model for your particular application.\n\nOther Rounds in This Battle\n\nExplore combinations from the same test battle\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 1\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:2.4k results:718\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 2\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:2.5k results:1.1k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 3\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:2.4k results:1.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 4\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:2.6k results:1.1k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 5\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:9.0k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 6\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:5.0k results:1.1k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 7\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:3.5k results:975\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 8\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:6.3k results:1.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 9\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:5.9k results:1.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 10\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:6.9k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 11\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:5.7k results:1.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 12\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:6.3k results:1.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 13\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:9.2k results:1.4k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 14\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:9.7k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 16\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:11.0k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 17\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:11.4k results:1.8k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 18\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:12.8k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 19\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:12.4k results:1.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 20\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:14.4k results:1.5k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 22\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:16.1k results:1.5k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 23\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:16.7k results:1.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 24\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:17.9k results:1.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 25\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:18.2k results:1.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 26\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:20.3k results:1.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 27\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:19.4k results:1.9k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 28\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:20.7k results:1.9k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 29\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:21.7k results:2.0k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 30\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:23.9k results:2.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 31\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:23.4k results:2.1k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 32\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:25.1k results:2.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 33\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:26.9k results:2.1k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 34\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:26.7k results:2.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 35\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:28.9k results:2.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 36\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:29.4k results:2.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 37\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:31.0k results:2.3k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 38\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:30.9k results:2.2k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 39\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:31.4k results:2.4k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 40\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:33.6k results:2.4k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 41\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:34.2k results:2.5k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 42\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:35.2k results:2.4k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 43\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:36.7k results:2.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 44\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:37.9k results:2.5k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 45\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:38.9k results:2.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 46\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:40.9k results:2.7k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 47\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:39.9k results:2.6k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 48\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:42.6k results:2.9k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 49\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:43.7k results:3.0k\nView Details →\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nRound 50\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nprompt:45.0k results:2.8k\nView Details →\n🏠 Back to Home\n\nBattle Details\n\n⚔️ View Full Battle Page\n\nStructured JSON output for AI assistant behavior with schema constraints\n\nAll Rounds in This Battle\n\nRound 1prompt:2.4k results:718\nRound 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— OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors…"},"reply_part3_uri":null,"raw_notification":{"author":{"associated":{"activitySubscription":{"allowSubscriptions":"followers"}},"avatar":"https://cdn.bsky.app/img/avatar/plain/did:plc:33avz2l7y5scw3abq3lmylns/bafkreigbjf57loh3e4wrreoyg27rz7kzj4yjlorl5grogfoacxahp22g7m","createdAt":"2024-11-22T00:24:23.152Z","description":"Cofounder of social-protocols.org. Working on algorithms to make online conversations less toxic and more intelligent. Former engineer, architect, product manager at Yahoo!, ZipRecruiter.\n\nhttps://bluenotes.social\nhttps://getcontext.bot","did":"did:plc:33avz2l7y5scw3abq3lmylns","displayName":"Jonathan Warden","handle":"jonathanwarden.com","indexedAt":"2026-09-03T17:41:52.060Z","labels":[],"viewer":{"blockedBy":false,"muted":false,"mutedOnlyQuoteposts":false,"mutedOnlyReposts":false}},"cid":"bafyreieusjcljgsedy3oz6iwbdnk5gnhn76sdmxiblzihrd5lf67dzfbdq","indexedAt":"2026-09-10T22:55:03.806Z","isRead":false,"labels":[],"reason":"mention","record":{"$type":"app.bsky.feed.post","createdAt":"2026-09-10T22:55:03.806Z","facets":[{"$type":"app.bsky.richtext.facet","features":[{"$type":"app.bsky.richtext.facet#mention","did":"did:plc:anbhmngzs3exwbq47xxzogk4"}],"index":{"byteEnd":15,"byteStart":0}}],"langs":["en"],"reply":{"parent":{"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27"},"root":{"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27"}},"text":"@getcontext.bot Is this association causal? If not, why is it so strong?"},"uri":"at://did:plc:33avz2l7y5scw3abq3lmylns/app.bsky.feed.post/3mv75hvxv3k2y"},"canonical_thread":"CONTEXT_BOT_THREAD_V2\n\n[ancestor]\nAuthor: aicaution.ca (did:plc:haekwbhk7lxoqlbiiw6fcqqw)\nURI: at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27\nText:\nThe data from this OECD PISA report is damning.\n\n\"students who do not use AI outperform those who do, ... equivalent to being around one year of schooling ahead of their peers.\"\n\nwww.oecd.org/en/publicati...\nImages:\n- [image 1] Alt text: Graph showing students who never use AI scoring 505 on a \"draft texts for writing assignments\" task. As students use AI more, the score goes down, until students who use it daily score 480.  \n\n[invocation]\nAuthor: jonathanwarden.com (did:plc:33avz2l7y5scw3abq3lmylns)\nURI: at://did:plc:33avz2l7y5scw3abq3lmylns/app.bsky.feed.post/3mv75hvxv3k2y\nText:\n@getcontext.bot Is this association causal? If not, why is it so strong?","reply_part2_record":{"$type":"app.bsky.feed.post","createdAt":"2026-09-10T22:57:48.984408Z","facets":[{"features":[{"$type":"app.bsky.richtext.facet#link","uri":"https://standard-reader.app/a/did:plc:anbhmngzs3exwbq47xxzogk4/3mv75ms6rjxky"}],"index":{"byteEnd":87,"byteStart":74}}],"reply":{"parent":{"cid":"bafyreifccrqxymyfvhtxlij35u5ibq2z2j3vkw26dlhtha3z3veobmpeve","uri":"at://did:plc:anbhmngzs3exwbq47xxzogk4/app.bsky.feed.post/3mv75ms6rjxkz"},"root":{"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27"}},"text":"…(motivation, prior achievement, assignment type) remain uncontrolled. (full response)"},"deferred_attempt_kind":null,"follower_post_rkey":null,"received_at":"2026-09-10T22:55:19.110445Z","reply_part3_cid":null,"reply_part2_cid":"bafyreigc55rmudtvd4cano7wg4x36datxw6bmnscelxbdh2uqog4eg7mem","no_reply":false,"admitted_at":"2026-09-10T22:55:19.428148Z","root_cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","follower_post_cid":null,"failure_category":null,"publication_claimed_at":null,"canonical_thread_version":"2","reply_part2_uri":"at://did:plc:anbhmngzs3exwbq47xxzogk4/app.bsky.feed.post/3mv75mtiq4sl5","citation_sources":[{"cited_text":"PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores...","span":"PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI.","title":"PISA 2025 Results (Volume I) | OECD","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"},{"cited_text":"In these scenarios, students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schoo...","span":"students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers.","title":"PISA 2025 Results (Volume I) | OECD","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"},{"cited_text":"How AI use relates to student performance is complex, varying with how students use it and what for. ","span":"how AI use relates to student performance is complex, varying with how students use it and what for.","title":"PISA 2025 Results (Volume I) | OECD","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"},{"cited_text":"However, weekly users of AI for general purposes have similar performance outcomes to non-users. ","span":"weekly users of AI for general purposes have similar performance outcomes to non-users,","title":"PISA 2025 Results (Volume I) | OECD","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"},{"cited_text":"Students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly hig...","span":"students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science — though these opportunities are more common among socio-economically advantaged students.","title":"PISA 2025 Results (Volume I) | OECD","url":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"},{"cited_text":"The findings show an association rather than proof that AI use raises or lowers achievement.\n\n","span":"The findings show an association rather than proof that AI use raises or lowers achievement.","title":"Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal","url":"https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/"},{"cited_text":"The OECD’s PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores. ","span":"The OECD's PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores.","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/"},{"cited_text":"The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. [7] The OECD adjusted its sc...","span":"The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. The OECD adjusted its science comparisons for students' socioeconomic status, but says the relationships do not necessarily show a negative effect from AI.","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/"},{"cited_text":"Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive....","span":"Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive.","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/"},{"cited_text":"The one exception was using AI “to help me learn” as students using it about weekly scored highest, at around 500 points, and non-users came second, s...","span":"using it about weekly scored highest, at around 500 points, and non-users came second, slightly below the top one.","title":"Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal","url":"https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/"},{"cited_text":"Among frequent users, however, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to...","span":"among frequent users, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to perform better than those who received no such guidance.","title":"PISA 2025: Students’ reading and mathematics performance declined sharply across the OECD","url":"https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html"},{"cited_text":"The report also notes that 20 points on PISA's scale is roughly equal to one year of schooling. Another notable pattern: for students using AI every d...","span":"20 points on PISA's scale is roughly equal to one year of schooling, and for students using AI every day, science scores are higher by 13 points — equivalent to over half a year of instruction — when classes consistently ask them to critique AI-produced content.","title":"OECD: Heavy AI Use Linked to Lower Science Scores","url":"https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/"},{"cited_text":"Andreas Schleicher, the OECD's Director for Education and Skills, put it bluntly: \"In the same way that we do not become fit by watching sports but by...","span":"\"In the same way that we do not become fit by watching sports but by doing sports, learning does not occur through the consumption of content, but as a productive cognitive struggle of the mind with new material.\" His advice for classrooms: treat AI as support, not a substitute. \"Where technology enables or enhances that cognitive struggle, students will advance. Where technology short-circuits the productive struggle of learning, it will undercut students' development.\"","title":"OECD: Heavy AI Use Linked to Lower Science Scores","url":"https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/"},{"cited_text":"Students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test. Daily users scored 481. That's a...","span":"students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test, daily users scored 481, a 28-point gap adjusted for socioeconomic background, which the OECD says is roughly equivalent to a year and a half of teaching lost","title":"OECD Finds Students Who Use AI Chatbots Daily Score Far Worse on Tests - Startup Fortune","url":"https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/"},{"cited_text":"Students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science tha...","span":"students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science than non-users, after adjustment for socioeconomic status.","title":"OECD’s PISA data link student AI use to lower science scores, with important exceptions | MLQ News","url":"https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/"}],"raw_thread":{"thread":{"$type":"app.bsky.feed.defs#threadViewPost","parent":{"$type":"app.bsky.feed.defs#threadViewPost","post":{"author":{"associated":{"activitySubscription":{"allowSubscriptions":"followers"}},"avatar":"https://cdn.bsky.app/img/avatar/plain/did:plc:haekwbhk7lxoqlbiiw6fcqqw/bafkreia2nikutotwhwouqutp67groasv4tlulxvbvetjyzuq6jkgmrx4uq","createdAt":"2025-12-30T17:54:44.024Z","did":"did:plc:haekwbhk7lxoqlbiiw6fcqqw","displayName":"Pause AI in BC Schools","handle":"aicaution.ca","labels":[],"viewer":{"blockedBy":false,"muted":false,"mutedOnlyQuoteposts":false,"mutedOnlyReposts":false}},"bookmarkCount":77,"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","embed":{"$type":"app.bsky.embed.images#view","images":[{"alt":"Graph showing students who never use AI scoring 505 on a \"draft texts for writing assignments\" task. As students use AI more, the score goes down, until students who use it daily score 480.\n\n","aspectRatio":{"height":1920,"width":1440},"fullsize":"https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:haekwbhk7lxoqlbiiw6fcqqw/bafkreigxkckii6n66wqvfq5kblfd6bdogfwrl7afuz3xo7c3wz7xrcs7qi","thumb":"https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:haekwbhk7lxoqlbiiw6fcqqw/bafkreigxkckii6n66wqvfq5kblfd6bdogfwrl7afuz3xo7c3wz7xrcs7qi"}]},"indexedAt":"2026-09-10T15:01:17.360Z","labels":[],"likeCount":644,"quoteCount":38,"record":{"$type":"app.bsky.feed.post","createdAt":"2026-09-10T15:01:12.732Z","embed":{"$type":"app.bsky.embed.images","images":[{"alt":"Graph showing students who never use AI scoring 505 on a \"draft texts for writing assignments\" task. As students use AI more, the score goes down, until students who use it daily score 480.\n\n","aspectRatio":{"height":1920,"width":1440},"image":{"$type":"blob","mimeType":"image/jpeg","ref":{"$link":"bafkreigxkckii6n66wqvfq5kblfd6bdogfwrl7afuz3xo7c3wz7xrcs7qi"},"size":494260}}]},"facets":[{"features":[{"$type":"app.bsky.richtext.facet#link","uri":"https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html"}],"index":{"byteEnd":207,"byteStart":179}}],"langs":["en"],"text":"The data from this OECD PISA report is damning.\n\n\"students who do not use AI outperform those who do, ... equivalent to being around one year of schooling ahead of their peers.\"\n\nwww.oecd.org/en/publicati..."},"replyCount":14,"repostCount":258,"uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27","viewer":{"bookmarked":false,"embeddingDisabled":false,"threadMuted":false}},"threadContext":{}},"post":{"author":{"associated":{"activitySubscription":{"allowSubscriptions":"followers"}},"avatar":"https://cdn.bsky.app/img/avatar/plain/did:plc:33avz2l7y5scw3abq3lmylns/bafkreigbjf57loh3e4wrreoyg27rz7kzj4yjlorl5grogfoacxahp22g7m","createdAt":"2024-11-22T00:24:23.152Z","did":"did:plc:33avz2l7y5scw3abq3lmylns","displayName":"Jonathan Warden","handle":"jonathanwarden.com","labels":[],"viewer":{"blockedBy":false,"muted":false,"mutedOnlyQuoteposts":false,"mutedOnlyReposts":false}},"bookmarkCount":0,"cid":"bafyreieusjcljgsedy3oz6iwbdnk5gnhn76sdmxiblzihrd5lf67dzfbdq","indexedAt":"2026-09-10T22:55:08.869Z","labels":[],"likeCount":0,"quoteCount":0,"record":{"$type":"app.bsky.feed.post","createdAt":"2026-09-10T22:55:03.806Z","facets":[{"$type":"app.bsky.richtext.facet","features":[{"$type":"app.bsky.richtext.facet#mention","did":"did:plc:anbhmngzs3exwbq47xxzogk4"}],"index":{"byteEnd":15,"byteStart":0}}],"langs":["en"],"reply":{"parent":{"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27"},"root":{"cid":"bafyreihw5ccemsmyrqgm7wc4442cf6lvazbw4thxp2kfy5rgrdrtrniwee","uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27"}},"text":"@getcontext.bot Is this association causal? If not, why is it so strong?"},"replyCount":0,"repostCount":0,"uri":"at://did:plc:33avz2l7y5scw3abq3lmylns/app.bsky.feed.post/3mv75hvxv3k2y","viewer":{"bookmarked":false,"embeddingDisabled":false,"threadMuted":false}},"threadContext":{}}},"reply_part2_rkey":"3mv75mtiq4sl5","standard_site_document_uri":"at://did:plc:anbhmngzs3exwbq47xxzogk4/site.standard.document/3mv75ms6rjxky","canonical_media":[{"alt":"Graph showing students who never use AI scoring 505 on a \"draft texts for writing assignments\" task. As students use AI more, the score goes down, until students who use it daily score 480.\n\n","index":1,"post_uri":"at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27","type":"image","url":"https://cdn.bsky.app/img/feed_fullsize/plain/did:plc:haekwbhk7lxoqlbiiw6fcqqw/bafkreigxkckii6n66wqvfq5kblfd6bdogfwrl7afuz3xo7c3wz7xrcs7qi"}],"limit_notice_kind":null,"full_response":"I have solid material to write the analysis now. The OECD itself and multiple secondary sources explicitly frame this as correlational, not causal, and note reverse-causation/confounding explanations.\n\nCONTEXT_BOT_DRAFT\ntitle: Is the OECD AI-scores link causal?\ncompact_reply: No — OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors (motivation, prior achievement, assignment type) remain uncontrolled.\nCONTEXT_BOT_DRAFT_END\n\n## Bottom line\n\n**No, the association shown in that chart is not established as causal — and the OECD says so explicitly.** The report describes a correlation between self-reported AI use for drafting writing assignments and PISA science scores, not a causal effect of AI use on achievement. It is likely strong partly because of **reverse causation and selection effects**: students who are already struggling academically (and thus already score lower) may be more likely to lean on AI to complete work they find difficult, rather than AI use causing the lower scores. The socioeconomic-status adjustment shown in the second (light blue) line in the graph narrows the gap somewhat but does not eliminate it, meaning other unmeasured confounders (motivation, prior achievement, teacher quality, assignment difficulty, self-selection into AI use) likely still explain much of what remains.\n\n## What the OECD itself says\n\nThe OECD's own PISA 2025 report is careful to hedge causal language. PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) The magnitude cited matches the tweet: students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html)\n\nBut the same report and its press coverage stress the \"complex\" and non-random nature of this relationship: how AI use relates to student performance is complex, varying with how students use it and what for.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) Crucially, weekly users of AI for general purposes have similar performance outcomes to non-users,[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) and students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science — though these opportunities are more common among socio-economically advantaged students.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) This nuance (non-monotonic pattern, benefits when paired with AI-literacy instruction) is inconsistent with a simple \"AI use directly damages learning\" causal story and instead points to effect modification by context and skill.\n\n## Explicit \"correlation, not causation\" statements from analysts covering the report\n\nMultiple outlets summarizing the PISA release explicitly flag the correlational nature of the data:\n\n- The findings show an association rather than proof that AI use raises or lowers achievement.[[2]](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/)\n- The OECD's PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n- The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. The OECD adjusted its science comparisons for students' socioeconomic status, but says the relationships do not necessarily show a negative effect from AI.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n- Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n\nThis last point is the core mechanism analysts point to for **why the association could be strong without being causal**: PISA is an observational, cross-sectional survey (students self-report their AI use and take a test at one point in time). There is no random assignment, no experimental manipulation, and no way to rule out that weaker students select into heavier AI use — for example, using a chatbot specifically because they struggle to draft or summarize on their own — which would produce exactly this pattern (non-users scoring highest) even if AI use itself had zero or even a positive effect on learning for a given student.\n\n## Additional nuance in the data that supports a \"not simply causal\" reading\n\n- The relationship is **not linear/monotonic** across all task types. For \"using AI to help me learn,\" using it about weekly scored highest, at around 500 points, and non-users came second, slightly below the top one.[[2]](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/) A purely harmful causal effect would predict monotonic decline with more use across all use-cases, but it doesn't.\n- Quality of use and instruction matters: among frequent users, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to perform better than those who received no such guidance.[[4]](https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html) Similarly, 20 points on PISA's scale is roughly equal to one year of schooling, and for students using AI every day, science scores are higher by 13 points — equivalent to over half a year of instruction — when classes consistently ask them to critique AI-produced content.[[5]](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/) This suggests the relationship is moderated heavily by *how* AI is used and taught, not simply *whether* it's used — again cutting against a single, uniform causal \"AI harms learning\" story.\n- The OECD's Andreas Schleicher framed the underlying concern in terms of cognitive engagement rather than asserting a direct causal test: \"In the same way that we do not become fit by watching sports but by doing sports, learning does not occur through the consumption of content, but as a productive cognitive struggle of the mind with new material.\" His advice for classrooms: treat AI as support, not a substitute. \"Where technology enables or enhances that cognitive struggle, students will advance. Where technology short-circuits the productive struggle of learning, it will undercut students' development.\"[[5]](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/) This is a theoretical/plausibility argument for a causal channel, not evidence that this survey design has demonstrated it.\n\n## Why the SES adjustment (the two lines in the chart) doesn't settle causality\n\nThe chart in the thread shows two lines — raw and SES-adjusted scores — and adjusting for socioeconomic status **narrows the gap somewhat but leaves a substantial gap intact** (e.g., one write-up reports students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test, daily users scored 481, a 28-point gap adjusted for socioeconomic background, which the OECD says is roughly equivalent to a year and a half of teaching lost[[6]](https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/)). Controlling for SES rules out one obvious confound (family wealth/background), but it does not rule out others like: baseline academic ability/motivation, whether a student's school assigns different amounts of AI-eligible work, self-selection by weaker students into heavier reliance on tools, or reverse causation. As one summary succinctly put it: students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science than non-users, after adjustment for socioeconomic status.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/) \"After adjustment for SES\" is not the same as \"after adjustment for all plausible confounders.\"\n\n## Conclusion\n\n- **Causal or not:** The OECD explicitly frames this as an association/correlation, not a demonstrated causal effect, and multiple independent write-ups of the same report reiterate that caveat.\n- **Why the correlation is strong despite likely not being (purely) causal:** The leading explanations are (1) reverse causation/self-selection — struggling students may turn to AI more for tasks like drafting or summarizing precisely because they need the help, so the causal arrow may run partly from \"weaker student\" → \"more AI use\" rather than the other way; (2) uncontrolled confounders beyond SES, such as motivation, prior achievement, and school/assignment differences; and (3) heterogeneity in *how* AI is used — the pattern flips or weakens for general-purpose/moderate use and for classrooms that teach students to critically evaluate AI output, which is inconsistent with a single uniform causal mechanism of \"AI use lowers scores.\"\n- This is a genuinely contested interpretive question in the underlying report itself and in expert commentary — the OECD does not claim causality, but some commentators (and headlines) are already presenting the correlation more starkly than the data alone can support.\n\n## Sources\n\n1. [PISA 2025 Results (Volume I) | OECD](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html)\n2. [Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/)\n3. [OECD’s PISA data link student AI use to lower science scores, with important ex…](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n4. [PISA 2025: Students’ reading and mathematics performance declined sharply acros…](https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html)\n5. [OECD: Heavy AI Use Linked to Lower Science Scores](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/)\n6. [OECD Finds Students Who Use AI Chatbots Daily Score Far Worse on Tests - Startu…](https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/)","dry_run":false,"standard_site_document_rkey":"3mv75ms6rjxky","reply_repo":"did:plc:anbhmngzs3exwbq47xxzogk4","limit_notice_cid":null,"completed_at":"2026-09-10T22:57:48.982642Z","standard_site_document_cid":"bafyreige23ytcx7m3kw27ek4nlxwlt6ayujnc4tgv3nju7apb5iruz3vze","id":58,"follower_post_record":null,"anthropic_messages":{"cache_control":{"type":"ephemeral"},"max_tokens":4096,"messages":[{"content":"STRUCTURE_OUTPUT\n\nResearch drafts (starting point; shorten or lightly rewrite only as needed to meet the hard cap. Do not self-count; use the measured lengths below):\ntitle: Is the OECD AI-scores link causal?\ntitle_length: 34 graphemes / 34 bytes\ncompact_reply: No — OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors (motivation, prior achievement, assignment type) remain uncontrolled.\ncompact_length: 367 graphemes / 369 bytes\ncompact_reply_seed: No — OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors (m\nhard_cap: 300 graphemes / 3000 bytes\nover_cap: compact is 67 graphemes over; shorten by about 67 graphemes\n\nCanonical thread:\n\nCONTEXT_BOT_THREAD_V2\n\n[ancestor]\nAuthor: aicaution.ca (did:plc:haekwbhk7lxoqlbiiw6fcqqw)\nURI: at://did:plc:haekwbhk7lxoqlbiiw6fcqqw/app.bsky.feed.post/3mv6cylzkhs27\nText:\nThe data from this OECD PISA report is damning.\n\n\"students who do not use AI outperform those who do, ... equivalent to being around one year of schooling ahead of their peers.\"\n\nwww.oecd.org/en/publicati...\nImages:\n- [image 1] Alt text: Graph showing students who never use AI scoring 505 on a \"draft texts for writing assignments\" task. As students use AI more, the score goes down, until students who use it daily score 480.  \n\n[invocation]\nAuthor: jonathanwarden.com (did:plc:33avz2l7y5scw3abq3lmylns)\nURI: at://did:plc:33avz2l7y5scw3abq3lmylns/app.bsky.feed.post/3mv75hvxv3k2y\nText:\n@getcontext.bot Is this association causal? If not, why is it so strong?\n\nResearch writeup:\n\nI have solid material to write the analysis now. The OECD itself and multiple secondary sources explicitly frame this as correlational, not causal, and note reverse-causation/confounding explanations.\n\nCONTEXT_BOT_DRAFT\ntitle: Is the OECD AI-scores link causal?\ncompact_reply: No — OECD itself says this is an association, not proof AI use lowers scores. Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors (motivation, prior achievement, assignment type) remain uncontrolled.\nCONTEXT_BOT_DRAFT_END\n\n## Bottom line\n\n**No, the association shown in that chart is not established as causal — and the OECD says so explicitly.** The report describes a correlation between self-reported AI use for drafting writing assignments and PISA science scores, not a causal effect of AI use on achievement. It is likely strong partly because of **reverse causation and selection effects**: students who are already struggling academically (and thus already score lower) may be more likely to lean on AI to complete work they find difficult, rather than AI use causing the lower scores. The socioeconomic-status adjustment shown in the second (light blue) line in the graph narrows the gap somewhat but does not eliminate it, meaning other unmeasured confounders (motivation, prior achievement, teacher quality, assignment difficulty, self-selection into AI use) likely still explain much of what remains.\n\n## What the OECD itself says\n\nThe OECD's own PISA 2025 report is careful to hedge causal language. PISA data show that students who use AI for specific schoolwork tasks, such as summarising texts, drafting or conducting research, attain lower scores in science than students who do not use AI.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) The magnitude cited matches the tweet: students who do not use AI outperform those who do, on average, by around 20 points – equivalent to being around one year of schooling ahead of their peers.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html)\n\nBut the same report and its press coverage stress the \"complex\" and non-random nature of this relationship: how AI use relates to student performance is complex, varying with how students use it and what for.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) Crucially, weekly users of AI for general purposes have similar performance outcomes to non-users,[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) and students who regularly use AI for general purposes, and have learning opportunities at school to develop AI literacy skills, tend to have slightly higher scores in science — though these opportunities are more common among socio-economically advantaged students.[[1]](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html) This nuance (non-monotonic pattern, benefits when paired with AI-literacy instruction) is inconsistent with a simple \"AI use directly damages learning\" causal story and instead points to effect modification by context and skill.\n\n## Explicit \"correlation, not causation\" statements from analysts covering the report\n\nMultiple outlets summarizing the PISA release explicitly flag the correlational nature of the data:\n\n- The findings show an association rather than proof that AI use raises or lowers achievement.[[2]](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/)\n- The OECD's PISA 2025 data show an association between student AI use and science performance, not proof that chatbots cause lower scores.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n- The AI analysis compares reported use with performance, rather than randomly assigning students to use or avoid chatbots. The OECD adjusted its science comparisons for students' socioeconomic status, but says the relationships do not necessarily show a negative effect from AI.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n- Students who use chatbots may already differ from non-users in motivation, prior achievement, access to help or the kinds of assignments they receive.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n\nThis last point is the core mechanism analysts point to for **why the association could be strong without being causal**: PISA is an observational, cross-sectional survey (students self-report their AI use and take a test at one point in time). There is no random assignment, no experimental manipulation, and no way to rule out that weaker students select into heavier AI use — for example, using a chatbot specifically because they struggle to draft or summarize on their own — which would produce exactly this pattern (non-users scoring highest) even if AI use itself had zero or even a positive effect on learning for a given student.\n\n## Additional nuance in the data that supports a \"not simply causal\" reading\n\n- The relationship is **not linear/monotonic** across all task types. For \"using AI to help me learn,\" using it about weekly scored highest, at around 500 points, and non-users came second, slightly below the top one.[[2]](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/) A purely harmful causal effect would predict monotonic decline with more use across all use-cases, but it doesn't.\n- Quality of use and instruction matters: among frequent users, students who used AI to help them learn and were taught how to assess the quality of AI-generated information tended to perform better than those who received no such guidance.[[4]](https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html) Similarly, 20 points on PISA's scale is roughly equal to one year of schooling, and for students using AI every day, science scores are higher by 13 points — equivalent to over half a year of instruction — when classes consistently ask them to critique AI-produced content.[[5]](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/) This suggests the relationship is moderated heavily by *how* AI is used and taught, not simply *whether* it's used — again cutting against a single, uniform causal \"AI harms learning\" story.\n- The OECD's Andreas Schleicher framed the underlying concern in terms of cognitive engagement rather than asserting a direct causal test: \"In the same way that we do not become fit by watching sports but by doing sports, learning does not occur through the consumption of content, but as a productive cognitive struggle of the mind with new material.\" His advice for classrooms: treat AI as support, not a substitute. \"Where technology enables or enhances that cognitive struggle, students will advance. Where technology short-circuits the productive struggle of learning, it will undercut students' development.\"[[5]](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/) This is a theoretical/plausibility argument for a causal channel, not evidence that this survey design has demonstrated it.\n\n## Why the SES adjustment (the two lines in the chart) doesn't settle causality\n\nThe chart in the thread shows two lines — raw and SES-adjusted scores — and adjusting for socioeconomic status **narrows the gap somewhat but leaves a substantial gap intact** (e.g., one write-up reports students who said they never or almost never use AI to draft writing assignments scored 509 on the PISA science test, daily users scored 481, a 28-point gap adjusted for socioeconomic background, which the OECD says is roughly equivalent to a year and a half of teaching lost[[6]](https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/)). Controlling for SES rules out one obvious confound (family wealth/background), but it does not rule out others like: baseline academic ability/motivation, whether a student's school assigns different amounts of AI-eligible work, self-selection by weaker students into heavier reliance on tools, or reverse causation. As one summary succinctly put it: students who used AI chatbots for tasks such as summarising readings, researching topics or drafting assignments generally scored lower in science than non-users, after adjustment for socioeconomic status.[[3]](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/) \"After adjustment for SES\" is not the same as \"after adjustment for all plausible confounders.\"\n\n## Conclusion\n\n- **Causal or not:** The OECD explicitly frames this as an association/correlation, not a demonstrated causal effect, and multiple independent write-ups of the same report reiterate that caveat.\n- **Why the correlation is strong despite likely not being (purely) causal:** The leading explanations are (1) reverse causation/self-selection — struggling students may turn to AI more for tasks like drafting or summarizing precisely because they need the help, so the causal arrow may run partly from \"weaker student\" → \"more AI use\" rather than the other way; (2) uncontrolled confounders beyond SES, such as motivation, prior achievement, and school/assignment differences; and (3) heterogeneity in *how* AI is used — the pattern flips or weakens for general-purpose/moderate use and for classrooms that teach students to critically evaluate AI output, which is inconsistent with a single uniform causal mechanism of \"AI use lowers scores.\"\n- This is a genuinely contested interpretive question in the underlying report itself and in expert commentary — the OECD does not claim causality, but some commentators (and headlines) are already presenting the correlation more starkly than the data alone can support.\n\n## Sources\n\n1. [PISA 2025 Results (Volume I) | OECD](https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html)\n2. [Students avoiding AI for schoolwork outscore peers in science: OECD - TNGlobal](https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/)\n3. [OECD’s PISA data link student AI use to lower science scores, with important ex…](https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/)\n4. [PISA 2025: Students’ reading and mathematics performance declined sharply acros…](https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html)\n5. [OECD: Heavy AI Use Linked to Lower Science Scores](https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/)\n6. [OECD Finds Students Who Use AI Chatbots Daily Score Far Worse on Tests - Startu…](https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/)\n\nCitation URLs (allowlist; do not invent others):\n- https://www.oecd.org/en/publications/pisa-2025-results-volume-i_73451bc5-en.html\n- https://technode.global/2026/09/08/students-avoiding-ai-for-schoolwork-outscore-peers-in-science-bar-one-use-oecd/\n- https://mlq.ai/news/oecds-pisa-data-link-student-ai-use-to-lower-science-scores-with-important-exceptions/\n- https://www.oecd.org/en/about/news/press-releases/2026/09/pisa-2025-students-reading-and-mathematics-performance-declined-sharply-across-the-oecd.html\n- https://www.briefs.co/news/oecd-flags-a-downside-to-ai-in-class-heavy-users-trail-in-sc/\n- https://startupfortune.com/oecd-finds-students-who-use-ai-chatbots-daily-score-far-worse-on-tests/\n","role":"user"}],"model":"claude-sonnet-5","output_config":{"format":{"schema":{"anyOf":[{"additionalProperties":false,"properties":{"compact_reply":{"description":"Exact text for one short Bluesky post. 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Likely reverse causation: weaker/struggling students may turn to AI to draft/summarize work they can't do alone, while stronger students need it less. SES-adjustment narrows but doesn't erase the gap; unmeasured factors…","standard_site_publication_cid":"bafyreifkqratqorpalwhimdjjw7r5zlrkewu6bqde7l4ldi2w34rlah6my","target_uri":null,"limit_notice_uri":null,"invocation_text":null,"actor_did":"did:plc:33avz2l7y5scw3abq3lmylns"}