The article presents a methodological update on the lexical profile of informal spoken English with the emphasis on movies, television programs, and soap operas. The study analyzed Mark Davies’s mega-corpora with data containing approximately 625 million words and employed Paul Nation’s comprehensive and up-to-date British National Corpus/Corpus of Contemporary American English wordlists. Data from the analyses showed that viewers would need a vocabulary knowledge at 3,000 and 5,000 words frequency levels to understand 95 and 98% of the words in scripted (...) dialogs, respectively. Soap operas were found to be less lexically demanding compared to TV programs and movies. Findings are expected to fill in the methodological gaps between vocabulary assessment and vocabulary profiling research. (shrink)

Local item dependence is one of the most critical assumption in the Rasch model when it comes to the validity of a test. As the field of vocabulary assessment is calling for more clarity and validity for vocabulary tests, such assumption becomes more important than ever. The article offers a Rasch-based investigation into the issue of LID with the focus on the two popular formats of Vocabulary Levels Tests : multiple-choice and matching. A Listening Vocabulary Levels Test and an Updated (...) Vocabulary Levels Test were given to a single cohort of 311 university students in an English as a Foreign Language context. The analyses of raw score and standardized residuals correlations were conducted. The findings found no relationship between the 4-option, multiple-choice format of the LVLT and item local dependence. However, results from score and standardized residuals correlations analyses showed a strong link between the 3-item-per-cluster, matching format and item local dependence. The study calls for greater attention to the format of future vocabulary tests and support the use of meaning-recall formats in vocabulary testing. (shrink)

The present study analyzed the vocabulary profile of the News on the Web corpus, which contained 12 billion words from online newspapers and magazines in 20 countries to determine the vocabulary knowledge needed to reasonably understand online newspaper and magazine articles. The results showed that, in general, knowledge of the most frequent 4,000 word families in the British National Corpus/Corpus of Contemporary American English wordlist plus proper nouns, marginal words, transparent compounds and acronyms was necessary to gain 95% coverage for (...) the NOW corpus. However, when it came to the 98% coverage, online newspaper and magazine articles from different countries had relatively distinct lexical demands. In-depth analyses were carried out and the findings offered comprehensive insights into the issue. Implications for teaching and learning were also provided. (shrink)