Walter van Heuven
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This calculator computes scores for LexTALE (Lemhöfer & Broersma, 2012) and LexTALE-type vocabulary tests using three different scoring methods. Enter your test results below to calculate the original LexTALE score, Ghent score (Brysbaert, 2013), and Normalised Ghent score (Wen et al., 2024).
The original scoring method proposed by Lemhöfer & Broersma (2012) calculates the average of the percentage correct for words and nonwords separately. This corrects for the unequal proportion of words and nonwords (typically 2:1 ratio) and penalises both "yes" bias and "no" bias equally.
For the original English LexTALE, Lemhöfer & Broersma (2012) provide cut-off scores to classify participants according to the Common European Framework of Reference for Languages:
The Ghent score, introduced by Brysbaert (2013), adjusts the calculation by taking into account incorrect responses to nonwords (false alarms) rather than correct rejections. This provides a score that can range from negative values to positive values, better reflecting guessing behaviour.
When the word:nonword ratio is 2:1, this simplifies to:
\[ \text{Ghent Score} = N_{\text{yes to words}} - 2 \times N_{\text{yes to nonwords}} \]The normalised Ghent score, proposed by Wen et al. (2024), divides the Ghent score by the number of word items to produce a percentage score with a fixed range of −100% to +100%, regardless of the number of items in the test. This allows for better comparison across different LexTALE-type tests.
d′ is a measure from signal detection theory that quantifies the ability to discriminate between words (signals) and nonwords (noise). It is calculated as the difference between the z-transformed hit rate and false alarm rate. Higher d′ values indicate better discrimination ability.
Where:
\[ \text{Hit Rate} = \frac{\text{Correct Words}}{N_{\text{words}}} \quad \text{and} \quad \text{False Alarm Rate} = \frac{\text{Incorrect Nonwords}}{N_{\text{nonwords}}} \]For LexCHI, Wen et al. (2024) conducted a receiver operator characteristic (ROC) curve analysis to determine a cut-off score that can distinguish native from non-native Chinese speakers. The analysis yielded:
If a participant has a Normalised Ghent Score lower than 70%, it is very likely they are not a native speaker of Chinese. This cut-off can be used as a screening test when recruiting native Chinese speakers for online studies.
The following table lists the LexTALE and LexTALE-type vocabulary tests currently available:
| Language | Test Name | Words | Nonwords | α | Reference | OSF | Online version |
|---|---|---|---|---|---|---|---|
| Arabic | LexArabic | 60 | 30 | .92 | Alzahrani (2024) | — | — |
| Basque | Basque LexTALE | 50 | 25 | — | de Bruin et al. (2017) | — | — |
| Chinese | LexCHI | 40 | 20 | .96 | Wen et al. (2024) | osf.io/dh3ty | — |
| Chinese (single character) | LEXTALE_CH | 60 | 30 | .95 | Chan & Chang (2018) | osf.io/qdy4n | — |
| Dutch | Dutch LexTALE | 40 | 20 | — | — | — | lextale.com |
| English | LexTALE | 40 | 20 | — | Lemhöfer & Broersma (2012) | — | lextale.com |
| Estonian | LexEst | 60 | 30 | .96 | Lõo et al. (2025) | osf.io/y42xv | lexest.ut.ee |
| Finnish | Lexize | 60 | 30 | .97 | Salmela et al. (2021) | — | — |
| French | LEXTALE_FR | 56 | 28 | .96 | Brysbaert (2013) | — | — |
| German | German LexTALE | 40 | 20 | — | — | — | lextale.com |
| Italian | LexITA | 45 | 21 | .96 | Amenta et al. (2020) | — | — |
| Japanese | LexJP | 60 | 30 | .94 | Suzukida & Saito (2025) | — | — |
| Korean | LexKo | 40 | 20 | .92 | Chang et al. (2025) | osf.io/rf39u | — |
| Malay | LexMAL | 60 | 30 | .97 | Lee et al. (2024) | osf.io/8y4ft | lexmal.org |
| Portuguese | LextPT | 60 | 30 | .97 | Zhou & Li (2022) | — | — |
| Sicilian | LexSIC | 50 | 25 | .97 | Kupisch et al. (2023) | osf.io/nwrq5 | — |
| Spanish | Lextale-Esp | 60 | 30 | .96 | Izura et al. (2014) | — | — |
| Venetan | LexVEN | 50 | 25 | .98 | Ferin et al. (2023) | osf.io/f8vpu | — |
Note: α = Cronbach's alpha reliability coefficient from the final validation study (where available). All tests maintain a 2:1 word:nonword ratio.
Stimuli, instructions and other information about LexTALE and LexTALE-type tests can generally be found in the paper's Appendix/Supplementary Information, on OSF, online, or requested by contacting the corresponding author.