This study contributes to ongoing discussions on how measures of lexical diversity (LD) can help discriminate between essays from second language learners of English, whose work has been assessed as belonging to levels B1 to C2 of the Common European Framework of 1 We are very grateful to Pearson Education Ltd for sponsoring us with a research grant that made this study possible, and to Kirsten Ackermann, Veronica Benigno and Jeremy Hancock for their support in carrying out this project. 2 This work was funded by Language Testing, a trading division of Pearson Education Ltd.We are very grateful to Kirsten Ackermann, Veronica Benigno and Jeremy Hancock for their support in carrying out this project. We are also indebted to Scott Jarvis for providing a spreadsheet to help us with computing HD-D. Reference (CEFR). The focus is in particular on how different operationalisations of what constitutes a "different word" (type) impact on the LD measures themselves and on their ability to discriminate between CEFR levels. The results show that basic measures of LD, such as the number of different words, the TTR (Templin 1957) and the Index of Guiraud (Guiraud 1954) explain more variance in the CEFR levels than sophisticated measures, such as D (Malvern et al. 2004), HD-D (McCarthy and Jarvis 2007) and MTLD (McCarthy 2005) provided text length is kept constant across texts. A simple count of different words (defined as lemma's and not as word families) was the best predictor of CEFR levels and explained 22 percent of the variance in overall scores on the Pearson Test of English Academic in essays written by 176 test takers.

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