Test of a Model for Predicting Second Language Lexical Growth through Reading

This case study tests a mathematical model for its ability to predict second language vocabulary gains achieved through reading. To overcome the problem of small word gains noted in ear-lier studies of incidental acquisition, the participant (an adult learner of Dutch) read a lengthy text and was tested on hundreds of words. To maximize opportunities for learning from context, an illustrated text (a ‘Lucky Luke’ comic book) was chosen for the reading treatment. Before reading the text and again after each of eight readings, the participant used a rating scale to assess his knowledge of words that occurred only once in the text. Growth rates established in one round of learning (a matrix) were used to predict growth in subsequent rounds. The participant's gains were found to match closely figures generated by the predictive matrix. As in previous studies, nouns proved to be the easiest to learn. Results also detail the need for multiple encounters in order for a word to be retained.