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There has been an increase in research based on corpus analysis, especially in the field of teaching English to foreign language students. Such research covers aspects like grammar, syntax, morphology, semantics, and pragmatics in a broader sense. However, corpus studies on vocabulary are limited, and the need to work on them has increased in the last decade. Vocabulary is essential in learning and teaching any second language to English as a foreign language (EFL) classes. This study aims to thoroughly analyze vocabulary in three textbooks through a corpus analysis tool that is used to teach English as a foreign language to level 1, level 2, and diploma-taking students at a college in Saudi Arabia. Vocabulary is scrutinized through AntConC (1.4.0), a freeware program that uses statistical algorithms to provide visualizations of word frequencies, lexical clusters, and keywords. The results can be seen in the form of lists, tables, or charts to help you understand and draw conclusions. This selected corpus contains 163,716 word tokens. After statistical analysis of these words, English language teachers (ELTs) will understand what type of vocabulary is important for students for a particular level. It will also tell whether the vocabulary used in these textbooks is the correct representation of academic words when compared to baby BNC. Moreover, the study will provide insight to academicians, language teachers, and curriculum designers on what type of vocabulary is suitable for developing reading, writing, listening, or speaking skills according to the needs and levels of students.
Bibi et al. (Tue,) studied this question.