Why does the author believe traditional assessment outputs ...
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Ano: 2026
Banca:
ISET
Órgão:
Prefeitura de Lajedinho - BA
Prova:
ISET - 2026 - Prefeitura de Lajedinho - BA - Professor de Ensino Fundamental II - Língua Estrangeira (Inglês) |
Q4361871
Inglês
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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?