Word recognition norms

Definition

Word recognition norms measure the cognitive effort required to recognize and process words. These norms are based on average response times (latencies) and accuracy scores from lexical decision tasks (identifying if a word is real or not) and word-naming tasks (time taken to begin pronouncing a word) by native English speakers (Balota et al., 2007; Berger et al., 2017). Such norms provide insights into the ease or difficulty of processing specific words. They are valuable for modeling vocabulary development and assessing lexical proficiency, as words with longer response times generally indicate greater cognitive processing demands, potentially requiring higher language proficiency for quick access.

Methodology

  • These norms are calculated in various ways, such as mean response times, z-scores (standardized latencies), standard deviations, and accuracy rates, reflecting performance on lexical decision and word-naming tasks.

Calculated indices

Lexical decision time (LD)

Lexical decision time refers to the time required to determine whether a string of letters forms a real word.

  • Indices:
    • LD_Mean_RT_[(AW)/CW/FW]: Mean lexical decision reaction time
    • LD_Mean_RT_Zscore_[(AW)/CW/FW]: Z-score of lexical decision reaction time
    • LD_Mean_RT_SD_[(AW)/CW/FW]: Standard deviation of lexical decision reaction time
    • LD_Mean_Accuracy_[(AW)/CW/FW]: Accuracy rate in lexical decision tasks

Word naming response time (WN)

Word naming response time refers to the time taken to begin pronouncing a word aloud.

  • Indices:
    • WN_Mean_RT_[(AW)/CW/FW]: Mean word naming reaction time
    • WN_Zscore_[(AW)/CW/FW]: Z-score of word naming reaction time
    • WN_SD_[(AW)/CW/FW]: Standard deviation of word naming reaction time
    • WN_Mean_Accuracy_[(AW)/CW/FW]: Accuracy rate in word naming tasks

Notes

  • When indices are calculated for all words (AW) in this sub-construct, they do not include the "AW" tag in the index name (e.g., LD_Mean_RT).

References

  • Balota, D. A., Yap, M. J., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., … & Treiman, R. (2007). The English lexicon project. Behavior research methods, 39, 445-459. https://doi.org/10.3758/BF03193014
  • Berger, C. M., Crossley, S. A., & Kyle, K. (2017). Using novel word context measures to predict human ratings of lexical proficiency. Journal of Educational Technology & Society, 20(2), 201-212.