Modeling Complex Word Reading: Examining Influences at the Level of the Word and Child on Mono- and Polymorphemic Word Reading

ABSTRACT

Purpose

The probability of a child reading a word correctly is influenced by both child skills and properties of the word. The purpose of this study was to investigate child-level skills (set for variability and vocabulary), word-level properties (concreteness), word structure (mono- vs polymorphemic), and interactions between these properties and word structure within a comprehensive item-level model of complex word reading. This study is unique in that it purposely sampled both mono- and polymorphemic polysyllabic words.

Method

A sample of African American (n = 69) and Hispanic (n = 6) students in grades 2–5 (n = 75) read a set of mono- and polymorphemic polysyllabic words (J = 54). Item-level responses were modeled using cross-classified generalized random-effects models allowing variance to be partitioned between child and word while controlling for other important child factors and word features.

Results

Set for variability and the interaction between concreteness and word structure (i.e., mono- vs polymorphemic) were significant predictors. Higher probabilities of reading poly- over monomorphemic words were identified at lower levels of concreteness with the opposite at higher levels of concreteness.

Conclusions

Results indicate important predictors at both the child- and word-level and support the importance of morphological structure for reading abstract polysyllabic words.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Note that imageability and concreteness are highly related (i.e., imageability refers to ease with which an image can be conjured for a word, while concreteness refers to a rating of the degree to which a word is abstract). The correlation between imageability and concreteness exceeds r = .95. We use concreteness in the present study due to availability of data.

2. We choose to use the term set for variability for historical reasons as opposed to more recently used terms such as “mispronunciation correction.”

3. Note that we also tested the following additional word features: bigram frequency by position, orthographic neighborhood size, orthographic Levenshtein distance, phonological Levenshtein distance, and part of speech. None of these predictors were significant predictors and were therefore left out of the final models.

Additional information

Funding

This research was supported in part by Grant R324B190025 awarded to Florida State University by the Institute of Education Sciences (IES) and Grant P20HD091013 awarded to Florida State University by Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The content is solely the responsibility of the authors and does not necessarily represent the official view of IES or NICHD.