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🎓 How Students Use AI at University — A Real-World Study of 1,000,000 Sessions from Anthropic
AI is increasingly permeating education, but most discussions have so far been based on surveys and lab experiments. In a new report, the Anthropic team conducted one of the largest studies of real-world student AI use, analyzing over 1 million anonymized conversations with Claude.ai.
🤔 Who Uses AI the Most?
✅Computer Science students are the clear winner: they make up 36.8% of all conversations with Claude, although in fact they only make up 5.4% of US graduates.
✅STEM disciplines dominate overall — students in science, math, and engineering use AI far more than students in business, medicine, or the humanities.
✅ Business makes up almost 19% of all degrees, but only 8.9% of all AI sessions. The picture is similar in healthcare and humanities.
🤔 Why students turn to AI: the most popular queries
✅Creating and editing educational materials - 39.3%
✅Solving assignments, coding, explaining theory - 33.5%
✅Analyzing and visualizing data - 11%
✅Assistance in research and tool development - 6.5%
✅Translations, proofreading, creating diagrams - the remaining percentages.
🤔How exactly do students interact with AI?
✅Direct problem solving
✅Direct content creation
✅Collaborative problem solving
✅Collaborative content creation
💡Interestingly, all 4 types are found approximately equally often (23–29% each).
⚠️ The issue of academic honesty and thinking
The study showed that Claude most often performs high-level cognitive functions according to Bloom's taxonomy in conversations with students:
✅Creation — 39.8%
✅Analysis — 30.2%
✅Application, understanding, and memorization — much less often
⚡️ All this turns the familiar "Bloom's pyramid" upside down — and raises concerns: are students starting to "delegate" critical thinking operations to AI too early?
💡This study is just the beginning of a long journey, but it already provides a lot of food for thought for teachers, students, and university administrators.
💻The full text of the article is here
AI is increasingly permeating education, but most discussions have so far been based on surveys and lab experiments. In a new report, the Anthropic team conducted one of the largest studies of real-world student AI use, analyzing over 1 million anonymized conversations with Claude.ai.
🤔 Who Uses AI the Most?
✅Computer Science students are the clear winner: they make up 36.8% of all conversations with Claude, although in fact they only make up 5.4% of US graduates.
✅STEM disciplines dominate overall — students in science, math, and engineering use AI far more than students in business, medicine, or the humanities.
✅ Business makes up almost 19% of all degrees, but only 8.9% of all AI sessions. The picture is similar in healthcare and humanities.
🤔 Why students turn to AI: the most popular queries
✅Creating and editing educational materials - 39.3%
✅Solving assignments, coding, explaining theory - 33.5%
✅Analyzing and visualizing data - 11%
✅Assistance in research and tool development - 6.5%
✅Translations, proofreading, creating diagrams - the remaining percentages.
🤔How exactly do students interact with AI?
✅Direct problem solving
✅Direct content creation
✅Collaborative problem solving
✅Collaborative content creation
💡Interestingly, all 4 types are found approximately equally often (23–29% each).
⚠️ The issue of academic honesty and thinking
The study showed that Claude most often performs high-level cognitive functions according to Bloom's taxonomy in conversations with students:
✅Creation — 39.8%
✅Analysis — 30.2%
✅Application, understanding, and memorization — much less often
⚡️ All this turns the familiar "Bloom's pyramid" upside down — and raises concerns: are students starting to "delegate" critical thinking operations to AI too early?
💡This study is just the beginning of a long journey, but it already provides a lot of food for thought for teachers, students, and university administrators.
💻The full text of the article is here
Anthropic
Anthropic Education Report: How university students use Claude
AI systems are no longer just specialized research tools: they’re everyday academic companions. As AIs integrate more deeply into educational environments, we need to consider important questions about learning, assessment, and skill development. Until now, most discussions have relied on surveys and controlled experiments rather than direct evidence of how students naturally integrate AI into their academic work in real settings.
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