A Corpus-Based Lexical Coverage of Coursebooks in Nigeria: A Case Study

IF 0.4 Q4 EDUCATION & EDUCATIONAL RESEARCH REGISTER Journal Pub Date : 2024-06-06 DOI:10.18326/register.v17i1.164-188
Hamisu Hamisu Haruna, A. A. Tajuddin, Ibrahim Bashir
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Abstract

Since vocabulary is one of the most important components of reading comprehension, the relationship between the two has been studied in great detail. The significance of this relationship lies in the fact that learners' vocabulary size and the degree of coverage of the word families of the intended content are closely correlated with their ability to understand the context and the text. This study examined the lexical coverage of a corpus of 6,802,300 words from the first-year course books of the National Open University of Nigeria. With Anthony's AntWordProfiler software, we analyzed the lexical coverage of the corpus using the Lexical Frequency Profiling approach. The current study used Nation's (2012) BNC/COCA to determine the necessary vocabulary size for course book comprehension. The corpus study revealed that in order to reach 95% and 98% of the entire course book corpus, respectively, 5000 and 11000 word-families were required. However, vocabulary size needed for comprehension of each disciplinary field varied greatly, with the hard sciences having a significantly higher lexical demand as compared to the other fields. This means that students need a larger vocabulary to interact with and understand the course books, especially in the hard sciences. It therefore recommended that materials writers and instructors consider the specific disciplinary vocabulary needs in course books.  Similarly, due to disciplinary differences, more specific instructions and glossaries are needed for first-year university students to have a better understanding of course books, especially hard science course books. The study demonstrated the significance of corpus-based approaches in the analysis of language learning materials. Overall, the study underlined the importance of sufficient vocabulary for reading comprehension.
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基于语料库的尼日利亚教科书词汇覆盖:案例研究
由于词汇是阅读理解中最重要的组成部分之一,人们对两者之间的关系进行了深入研究。这种关系的意义在于,学习者的词汇量和对所学内容词族的覆盖程度与他们理解上下文和文章的能力密切相关。本研究考察了尼日利亚国立开放大学一年级课本语料库中 680.23 万个单词的词汇覆盖率。我们使用 Anthony 的 AntWordProfiler 软件,采用词频分析方法分析了语料库的词汇覆盖率。本研究使用 Nation(2012 年)的 BNC/COCA 来确定教材理解所需的词汇量。语料库研究显示,要达到整个教材语料库的 95% 和 98%,分别需要 5000 和 11000 个词族。然而,各学科领域理解所需的词汇量差别很大,硬科学领域的词汇量需求明显高于其他领域。这意味着学生需要更大的词汇量才能与课本互动并理解课本,尤其是在硬科学领域。因此,建议教材编写者和教师在编写教材时考虑具体学科的词汇需求。 同样,由于学科差异,需要为大学一年级学生提供更具体的说明和词汇表,以便他们更好地理解教材,尤其是硬科学教材。这项研究表明,基于语料库的方法在分析语言学习材料方面具有重要意义。总之,研究强调了充足的词汇对阅读理解的重要性。
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来源期刊
REGISTER Journal
REGISTER Journal Multiple-
自引率
4.80%
发文量
2
审稿时长
28 weeks
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