arXiv — NLP / Computation & Language · · 3 min read

CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

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Computer Science > Computation and Language

arXiv:2609.13942 (cs)
[Submitted on 12 Sep 2026]

Title:CRITICS - Critical Science Without Borders: Language Models to Promote Critical Thinking in Science Education

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Abstract:The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation (MT) based on Large Language Models (LLMs) with educational technology. By leveraging MT systems specifically optimized for scientific content, educational institutions can provide accurate, culturally relevant translations of scientific materials in students' native languages, ensuring that complex scientific concepts are comprehensible while maintaining technical accuracy. Building on these translations, the project explores the design and evaluation of innovative science teaching-learning proposals grounded in curriculum-aligned teaching-learning. Thus, CRITICS will investigate key components of scientific argumentation and critical thinking practices together with textual feedback aligned with learning objectives and assessment criteria inspired by competence-based evaluation frameworks. CRITICS aims to break down language barriers to accessing cutting-edge research and educational materials currently available only in high-resourced languages, thereby facilitating the democratization of scientific knowledge and fostering critical thinking in science education.
Comments: 9 pages
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.13942 [cs.CL]
  (or arXiv:2609.13942v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2609.13942
arXiv-issued DOI via DataCite (pending registration)
Journal reference: SEPLN 2026: 42nd International Conference of the Spanish Society for Natural Language Processing, León, Spain, 22-25 September 2026

Submission history

From: Rodrigo Agerri [view email]
[v1] Sat, 12 Sep 2026 13:37:10 UTC (127 KB)
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