The present study aimed to suggest the implications for the elementary English vocabulary teaching by constructing
and analyzing the SEELC (SEEC Elementary English Learner Corpus). The SEELC contained around 58,000 words of texts written by 271 elementary school English learners who participated in the nationwide English writing contest, SEEC (Seoul National University of Education English Essay Contest). The corpus was analyzed on its characteristics including scale, words variety, a number of words in a sentence, etc. In addition, it was compared to the Korean university students’English learner corpus (YELC) and English writing corpus written by the grade 4 students of a Korean public elementary school. The statistical analysis of the learner corpus and comparison and analysis between the corpus were conducted using the corpus analysis tools. The results indicated that the SEELC contains a variety of level of words compared to the Korean university students’ English learner corpus. Furthermore, When compared with the corpus of grade 4 students, the SEELC had a higher proportion of using function words than content words. The English ability of SEEC participants were higher than those of grade 4 students who had the English writing ability required in the curriculum. Participants of SEEC also used vocabulary learned in class in their actual English writing, where lower level English learners showed higher utilization. Lastly, the SEELC consisted of higher level words of basic word list in 2009 revised national English curriculum than the writing of ordinary students. Based on the results of this study, it was observed that learner’s English writing ability correlated with the use of vocabulary, and that learners with higher level of English writing produced more accurate and natural writing with various vocabulary. The necessity for consistent construction of English learner corpus as a valuable source of elementary school English education was discussed for more effective and learner-customized English teaching method.