Abstract
Collocational competence is essential for all learners, particularly for multilingual learners. This corpus-driven study assembled a 474-collocation list from a digital science corpus compiled from several thousand middle school science resources. Using a corpus of more than 2.7 million tokens and more than 400 node words, the collocation list was extracted by combining two approaches: frequency-based and expert-judged. The Digital Science Collocations List (DSCL) provides middle school learners and teachers with an unprecedented resource covering Life Science, Physical Science, and Earth and Space Science. This list may be especially useful to multilingual learners as most of the collocations in this list are composed of patterns that they struggle with (e.g., adjective + noun and verb + noun).
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