A quantitative analysis of some well-known vocabulary books, along with proposed metrics and methods to enhance the vocabulary learning experience.

Some proposed metrics for evaluating vocabulary books, such as the coverage of frequent words for English learners, have their shortcomings. After highlighting these weaknesses, I’ll propose a metric that takes into account both the coverage of essential words and the effort required by the learner.

Afterward, an approach is proposed that aims to optimize this metric. The approach begins by sampling words based on their frequency and categorizing them into two groups: words that are easy to learn automatically and words that need to be learned intentionally. The chosen words are then organized so that the main focus is on the intentionally learnable words, while the automatically learnable words are used to elaborate on and provide context for the main words, as well as in reading examples.

Finally, a quantitative analysis and comparison of some well-known vocabulary books—such as 504 Absolutely Essential Words, 4000 Essential English Words, Barron’s 1100 Words You Need to Know, Merriam-Webster Vocabulary Builder, and Oxford Word Skills Basic Book—is provided. This analysis concludes with adjustments highlighting what makes a vocabulary book effective.

Application Language(s): Persian

Programming Languages and Technologies: Python, nltk

Member(s): Taha Rostami

codes and more information (Available)