Língua InglesaInterpretação de texto em inglêsISET 2026
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Questão de Língua Inglesa
Read the text and answer questions 42 to 44. 11 | P á g i n a What's worth measuring? The future of assessment in the AI age The rise of AI tools disrupts traditional ideas of assessment, and urges a shift toward promoting and evaluating higher-order thinking, creativity, and ethical reasoning. By Hrishikesh Desai Artificial Intelligence (AI) tools like ChatGPT have fundamentally disrupted traditional notions of assessment in education. When a machine can generate essays, solve complex problems, and even mimic creative writing, educators are forced to ask: What skills should we assess, and how do we evaluate learning in a world where AI can perform tasks once thought uniquely human? This think piece explores the implications of AI for assessment and argues that we must shift from measuring rote knowledge to promoting and evaluating higher-order thinking, creativity, and ethical reasoning. Historically, educational assessment has relied on measurable outputs, such as essays, exams, and problem sets that test memorization, comprehension, and technical proficiency. However, AI’s ability to generate these outputs undermines their reliability as indicators of individual effort or understanding. For example, a student can prompt ChatGPT or DeepSeek to write a 1000-word essay on climate change in minutes, complete with citations, which leaves educators grappling with how to distinguish human work from machinegenerated content. This disruption extends beyond writing to mathematics, coding, and even creative tasks, where AI tools like GitHub Copilot and DALL-E provide solutions or artifacts that mimic human ingenuity. As AI becomes a ubiquitous resource, the traditional metrics of learning are no longer fit for purpose. The emergence of generative AI has precipitated what can only be described as an assessment crisis. This technological disruption to learning has arrived at a critical juncture. For decades, faculty have critiqued assessment methods that prioritize memorization and formulaic responses over deeper learning. The emergence of sophisticated AI tools has transformed this critique from a theoretical ideal into an immediate practical necessity. We can no longer rely on conventional assessment methods that AI can bypass with ease. I argue that generative AI is not merely challenging our assessment techniques but providing an opportunity to fundamentally realign educational evaluation with more authentic demonstrations of human learning, thinking, and creation. Source: https://www.unesco.org/en/articles/whats-worth-measuring-future-assessment-ai-age
Why does the author believe traditional assessment outputs have become less reliable?
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