当学生在真实作业中使用ChatGPT时会发生什么？质量的提升是否以原创性为代价？
博科尼大学的研究人员与OpenAI经济研究部门合作开展的一项新实验发现，ChatGPT的使用和批判性思维训练产生了截然不同且互补的效果。使用ChatGPT提高了学生作业的质量和连贯性，而因果推理练习——一种批判性思维形式——则促使学生产生更多独特的想法。同时接受ChatGPT和训练的学生则表现出这两种效果。
结果还强调了在评估学生进步时采用整体方法的重要性。随着AI使学生更容易产出精雕细琢的答案，作业可能需要调整，以衡量其他期望的品质，如原创性。
AI帮助学生缩小了专业差距
在实验期间，博科尼大学1000多名一年级本科生参与了一个真实世界的商业案例，为大学商品店制定营销建议。
学生按上课时段随机分配到四个组之一：获得ChatGPT（GPT-4o）访问权限、接受因果推理训练、两者兼有、或两者皆无。因果推理是一种特定形式的批判性思维，涉及将因果关系联系起来，并解释为什么某个解决方案可能有效或无效。学生接受的训练与AI无关，而是通过一个包含游戏、示例、问题和反馈的练习来教授因果推理概念。
学生的提交作品由训练有素的人工评分员使用五级评分标准进行评估。另外，研究人员使用自动化文本分析来衡量每份提交作品的想法数量与多样性、因果推理的迹象，以及与三位专家提交作品的相似度。
可以使用ChatGPT的学生在五级评分标准上得分高出近整整一分。他们的答案包含更多想法，逻辑更清晰，与专家撰写的建议更为相似。换句话说，AI帮助新手产出了看起来更专业的工作。重要的是，学生并不是简单地把作业交给ChatGPT。他们仍然需要决定问什么、评估回答，并选择最终提交的内容。
批判性思维训练以不同方式发挥作用
批判性思维练习产生了一个更出人意料的结果。完成练习的学生更清楚地解释了他们的想法为何可能有效以及何时可能失败，但在评分标准上并未获得更高分数，因为该标准只衡量建议在多大程度上解决了两个标准营销目标：提高大学商店的知名度和使用率。
文本分析揭示了评分标准未捕捉到的另一项好处。在整个小组中，完成练习的学生产生了更广泛的想法，与同龄人相比更具独特性。这一点很重要，因为传统的评分标准（如本实验中用于评分的标准）可能会奖励清晰、结构良好的答案，却忽略了学生是否提出了别人没想到的想法。
AI使用可以补充思维能力
将教育辩论框定为学生应该学会独立思考还是学会使用AI的选择，这种倾向很诱人。
这项实验表明，两者在不同方面都有价值。使用AI帮助学生产出更精炼、想法更丰富、逻辑更连贯的答案。批判性思维训练鼓励他们发展更广泛的原创想法、质疑假设，并解释为什么他们的想法应该有效。
两者相辅相成。
同时获得ChatGPT访问权限和批判性思维练习的学生表现出了两者的好处。他们的想法多样性与仅完成练习的学生相当。他们的评分标准和想法数量与仅使用ChatGPT的学生相似。他们的作品还表现出更强的逻辑连贯性，以及更多寻找解释和质疑假设的证据。总体而言，这一组在最多衡量指标上都有所提升。
实验的随机设计使研究人员能够深入探究这些不同因素，将ChatGPT访问权限和批判性思维练习的效果与两者结合的效果区分开来。这使得该实验对快速增长的关于AI对学生影响以及如何最好地构建和支持学习的研究领域做出了特别有用的贡献。
学校面临的挑战
练习对学生的影响与传统评分标准所捕捉到的差异，指向了学校面临的更广泛挑战。
如果AI能帮助学生产出精炼、专家级的工作，那么只看最终答案就无法告诉我们学生真正理解了什么。
许多教育工作者已经在思考作业和评估可能需要改变的问题。这遵循了数十年来技术与教育共同演进的模式，以支持学生在现代社会中所需的技能。
这些结果强调了奖励学生产出反映原创性、推理能力和考虑多种方法的作品的重要性，而不仅仅是最传统或最精炼的答案。
要点： AI帮助学生改进答案。批判性思维训练帮助拓宽想法。两者在为学生未来做准备方面发挥着互补作用。
What happens when students use ChatGPT on a real-world assignment? Do quality improvements come at the expense of originality?
A new experiment from researchers at Bocconi University, in collaboration with OpenAI Economic Research, found distinct and complementary effects from ChatGPT access and critical-thinking training. Access to ChatGPT improved the quality and coherence of students’ work, while an exercise in causal reasoning—a form of critical thinking—led students to generate more unique ideas. Students who received both ChatGPT access and the training showed both effects.
The results also highlight the importance of a holistic approach in assessing student progress. As AI makes it easier for students to produce polished answers, assignments may need to adapt to measure other desired qualities such as originality.
AI helped students close an expertise gap
During the experiment, more than 1,000 first-year undergraduate students at Bocconi University worked on a real-world business case developing marketing recommendations for the university’s merchandise store.
Students were randomly assigned by class period into one of four groups that received: access to ChatGPT (GPT‑4o), training in causal reasoning, both, or neither. Causal reasoning is a specific form of critical thinking related to linking cause and effect and explaining why a given solution may or may not work. The training students received was unrelated to AI, instead teaching students causal reasoning concepts through an exercise that involved a game, examples, questions, and feedback.
Student submissions were evaluated by trained human graders using a five-point rubric. Separately, researchers used automated text analysis to measure each submission’s number and variety of ideas, signs of causal reasoning, and similarity to submissions from three experts.
The students who had access to ChatGPT scored almost a full point higher on the five-point scale. Their answers included more ideas, followed clearer logic, and were more similar to recommendations written by experts. In other words, AI helped novices produce work that looked more professional. Importantly, students weren’t simply handing over their assignments to ChatGPT. They still had to decide what to ask, evaluate the responses, and choose what went into their final submission.
Critical-thinking training helped in a different way
The critical-thinking exercise produced a more unexpected result. Students who completed the exercise explained more clearly why their ideas might work and when they might fail, but did not score higher on the grading rubric, which only measured how well the recommendations addressed two standard marketing goals: increasing awareness and use of the university store.
Text analysis revealed another benefit that the rubric did not capture. Across the group, students who completed the exercise produced a wider range of ideas that were more distinct when compared to what their peers produced. This matters because a traditional rubric, like the one used to grade the students in this experiment, can reward a clear, well-structured answer while overlooking whether a student came up with an idea that no one else did.
AI access can complement thinking skills
It can be tempting to frame the education debate as a choice of whether students should learn to think for themselves or learn to use AI.
This experiment highlights that both are valuable in different ways. AI access helped students produce answers that were more polished, idea-rich, and more logically coherent. Critical-thinking training encouraged them to develop a wider range of original ideas, question assumptions, and explain why their ideas should work.
Together, they are complementary.
Students who received both ChatGPT access and the critical-thinking exercise showed the benefits of each. Their idea variety matched that of students who completed only the exercise. Their rubric scores and number of ideas were similar to those of students with ChatGPT access alone. Their work also showed stronger logical coherence and more evidence of looking for explanations and questioning assumptions. Overall, this group showed gains across the widest range of measures.
The experiment’s randomized design allowed researchers to dig into these different factors, separating the effects of ChatGPT access and the critical-thinking exercise from the effect of combining them. That makes the experiment a particularly useful contribution to a rapidly growing body of research on the impact of AI on students and how to best structure and support their learning.
The challenge for schools
The difference between the impact of the exercise on students and what was captured by the traditional-style rubric points to a broader challenge facing schools.
If AI can help students produce polished, expert-like work, then looking only at the final answer tells us less about what a student actually understands.
Many educators are already grappling with the implication that assignments and evaluations may need to change. This follows a multi-decade pattern of technology and education evolving together in service of supporting the skills students need in modern society.
These results highlight the importance of rewarding students for producing work that reflects originality, reasoning, and consideration of multiple approaches, not just the most conventional or polished answers.
The takeaway: AI helped students make their answers better. Critical-thinking training helped make their ideas broader. The two play complementary roles in preparing students for the future.
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