This paper introduces S-DAT (Synthetic-Divergent Association Task), a scalable, multilingual framework for automated assessment of divergent thinking (DT) -a core component of human creativity. Traditional creativity assessments are often labor-intensive, language-specific, and reliant on subjective human ratings, limiting their scalability and cross-cultural applicability. In contrast, S-DAT leverages large language models and advanced multilingual embeddings to compute semantic distance -- a language-agnostic proxy for DT. We evaluate S-DAT across eleven diverse languages, including English, Spanish, German, Russian, Hindi, and Japanese (Kanji, Hiragana, Katakana), demonstrating robust and consistent scoring across linguistic contexts. Unlike prior DAT approaches, the S-DAT shows convergent validity with other DT measures and correct discriminant validity with convergent thinking. This cross-linguistic flexibility allows for more inclusive, global-scale creativity research, addressing key limitations of earlier approaches. S-DAT provides a powerful tool for fairer, more comprehensive evaluation of cognitive flexibility in diverse populations and can be freely assessed online: https://sdat.iol.zib.de/.

翻译：本文介绍了S-DAT（合成发散联想任务），这是一个用于自动化评估发散思维的可扩展、多语言框架。发散思维是人类创造力的核心组成部分。传统的创造力评估通常劳动密集、语言特定且依赖主观的人工评分，限制了其可扩展性和跨文化适用性。相比之下，S-DAT利用大型语言模型和先进的多语言嵌入技术来计算语义距离——这是一种与语言无关的发散思维代理指标。我们在包括英语、西班牙语、德语、俄语、印地语和日语（汉字、平假名、片假名）在内的十一种不同语言中评估了S-DAT，证明了其在各种语言环境下评分具有稳健性和一致性。与先前的DAT方法不同，S-DAT显示出与其他发散思维测量方法的聚合效度，以及与聚合思维的正确区分效度。这种跨语言的灵活性使得更具包容性、全球规模的创造力研究成为可能，解决了早期方法的关键局限。S-DAT为更公平、更全面地评估不同人群的认知灵活性提供了一个强大工具，并可在线免费访问：https://sdat.iol.zib.de/。