Probing lexical representations: Simultaneous modeling of word and reader contributions to multidimensional lexical representations.

Abstract

The current study models reader, item, and word contributions to the lexical representations of 39 morphologically complex words for 172 middle school students using a crossed random-effects item response model with multiple outcomes. We report 3 findings. First, results suggest that lexical representations can be characterized by separate but correlated dimensions of derived-word reading, spelling, and meaning. Second, a reader’s morphological knowledge of a root word (e.g., isolate) contributes to that reader’s lexical representations (i.e., mental representation of form and meaning) of a related derived word (e.g., isolation). Specifically, when controlling for reader and word characteristics, knowledge of root-word reading and morphological relatives and self-reported knowledge of meaning contributed to derived-word reading. Similarly, knowledge of root-word spelling and morphological relatives and self-reported knowledge of meaning contributed to derived-word spelling. Also, knowledge of root-word morphological relatives and self-reported knowledge of meaning contributed to self-reported knowledge of derived-word meaning. Our third finding is that after controlling for root-word knowledge, part of the remaining variability in lexical representations can be explained by reader and word characteristics, with different patterns of results for each lexical representation dimension. The significant reader characteristics include reading comprehension, morphological awareness, and vocabulary knowledge, whereas the significant word characteristics include frequency of the derived and root word, orthographic–phonological opaqueness, and phonological opaqueness. A model of what constitutes and contributes to lexical representations for adolescent readers is suggested.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 46 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.