What is it about?
The present study examines how well lexical characteristics predict academic vocabulary knowledge, that is, knowledge of words used in academic writing and speech without being specific to any discipline. Participants are university students who are native speakers of Spanish with upper-intermediate or advanced English proficiency level. They tick the English words that they know out of a selection of words from the most frequent 1,000 words in the Academic Vocabulary List (Gardner and Davies 2014). The distribution of percentages of correct answers for these words was predicted mainly by word frequency, then by cognateness and finally by a frequency by cognateness interaction whereby word frequency is a more important factor for non-cognate than cognate words.
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Why is it important?
The finding that cognateness can offer an advantage even to advanced-level EFL Spanish L1 learners indicates that helping Spanish L1 learners identify cognates is worthwhile, especially since this study also indicates that even adult upper-intermediate and advanced-level EFL Spanish L1 learners do not recognise all English academic-word cognates. Since this study is novel, it opens up avenues for future research. For example, studies with Spanish L1 EFL learners of other proficiency levels and using not only recognition tests are necessary. Replication studies are necessary also to examine whether two interesting findings (the interaction between word frequency and cognateness and their reciprocal suppression) are replicable.
Perspectives
Given the difficulty that English academic vocabulary learning poses for students at all educational levels, it is hoped that this study will inspire similar investigations into the learning of English academic words by Spanish native speakers and vice versa.
Dr Sophia Skoufaki
University of Essex
Read the Original
This page is a summary of: Spanish L1 EFL learners’ recognition knowledge of English academic vocabulary: The role of cognateness, word frequency and length, Applied Linguistics Review, November 2019, De Gruyter,
DOI: 10.1515/applirev-2018-0109.
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