Abstract This study presents a secondary analysis of word recognition patterns of 650 second‐grade students on an untimed oral reading fluency assessment, using explanatory item‐response models (EIRMs). The analytic sample included 50 passages containing 1,267 word‐tokens. Rasch model calibration showed most words clustered around the lower third of student ability distribution, capturing variability among struggling readers. Subsequent EIRM analyses indicated that several factors had significant effects on word recognition difficulty: Lexical features including word frequency, age of acquisition, and first‐syllable vowel patterns (especially r‐controlled vowels, diphthongs, and long vowels) were key predictors. Content words (nouns and verbs) proved easier than function words, while more concrete words were unexpectedly more difficult. Word position within passages significantly predicted difficulty. When examined simultaneously, first‐syllable vowel patterns emerged as the most robust decoding‐related predictor, explaining variance previously attributed to broader decoding measures. The final model explained 40% of item variance. By identifying specific item features that challenge developing readers in oral reading, this research provides a foundation for more precise instructional approaches that target particular sources of word recognition difficulty rather than relying on conventional aggregate reading indicators.
Toyama et al. (Thu,) studied this question.