The Science of Reading. Группа авторов

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СКАЧАТЬ segmentations for stimuli like corner ‐> {corn} + {‐er}. The answer goes back to the nature of the writing system, at least in the case of English spelling. Specifically, the analyses by Ulicheva et al. (2020) revealed that words like corner that appear erroneously to be morphologically complex are very rare in English spelling; typically, these words would be spelled in a way that does not make use of the suffix ‐er (e.g., martyr, sulphur, fibre). It is therefore unsurprising that readers should learn about such systematicity (i.e., ‐er as an affix), and capitalize on it to enable rapid, skilled reading (Rastle, 2019b).

Research has only just begun to understand the mechanisms that underpin the acquisition of morphemic knowledge in written language. Affix learning presents a particularly interesting challenge because affixes do not occur in their own right, and affixes are rarely taught explicitly as children learn to read. Therefore, the function of these letter groups must be discovered through experience with words that contain particular affixes. Through experience with words such as builder, banker, and teacher, one might learn that ‐er is agentive: someone who does {verb}. Knowledge of ‐er would permit the learner to generalize; for example, understanding that a tweeter is someone who tweets. The challenge may be more difficult in cases where affixes are used more frequently in idiosyncratic ways (e.g., hearth has nothing to do with hear), or where the nature of the transformation is less systematic (e.g., cyclist, racist, and Baptist all refer to an agent but in different ways). Perhaps the challenge of affix learning explains why morpheme effects in online reading tasks are typically observed only as children approach and move through adolescence (e.g., Beyersmann et al., 2012; Dawson et al., 2018).

      Recent research has conceptualized learning about affixes as a statistical learning problem (Lelonkiewicz, Ktori, & Crepaldi, 2020; Ulicheva et al., 2020). Lelonkiewicz et al. (2020) familiarized participants with a lexicon of novel words printed in a novel orthography. Each novel word contained an affix character at the beginning of the word or at the end. Following familiarization, participants were more likely to attribute a previously unseen word to the lexicon if it had an affix, and if the affix occurred in the correct position. These findings show that readers capture statistically salient chunks in language input and use this information in their analysis of new words. Ulicheva et al. (2020) selected nonwords with English suffixes that varied continuously in the consistency with which they reflect grammatical class. Performance in tests of reading, spelling, and meaning judgment showed a high degree of sensitivity to this meaningful information; and further, that this sensitivity was graded as a function of the consistency of the relationship between suffix spelling and grammatical category. Participants were more likely to judge a nonword like sedgeness as a noun than an adjective; and their eyes were more likely to regress back onto the nonword when it occurred in an adjective context than a noun context. Likewise, participants were more likely to spell a spoken word like /sEdZnƏs/ using ‐ness when it occurred in a noun context than a verb context (see also Treiman, Wolter, & Kessler, 2020 for similar findings). Together, these results suggest that morphological knowledge may increasingly mirror the writing system as readers gradually accumulate reading experience.

Thus, it seems that morphemes are salient statistical patterns relating spelling to meaning, and that knowledge of these patterns is acquired through reading experience. Tamminen and colleagues (2015) investigated how this learning might arise in a series of artificial learning experiments. They trained adults on novel words with morphological structure (e.g., sleepnule, teachnule, buildnule), and then assessed participants’ ability to generalize knowledge of the novel affix (e.g., applying knowledge of ‐nule to understand the untrained novel word sailnule). Tamminen et al. (2015) reported that knowledge of the novel affixes depended upon two aspects of the training set: 1) novel affixes needed to occur frequently in combination with multiple stems; and 2) novel affixes needed to occur with a consistent meaningful function. These findings suggest that those affixes that occur in a semantically consistent manner, and in combination with multiple stems, may be those most likely to be represented in a context‐independent manner, and segmented from their stems in visual word recognition. These conclusions are consistent with findings from skilled readers suggesting that morphological effects are largest in these conditions (e.g., Ford, Davis, & Marslen‐Wilson, 2010).

      Together, such recent findings suggest that we learn morphological statistical regularities through experience (Lelonkiewicz et al., 2020; Tamminen et al., 2015), and that the morphemic knowledge of skilled readers is graded in a manner that reflects the strength of these learned statistical regularities (Ulicheva et al., 2020). However, Treiman et al. (2020) raised an intriguing challenge. They tested adults’ sensitivity to the relationship between suffix spellings and grammatical category in a nonword spelling task, using spoken nonwords containing word‐final /Əs/ and /Ik/. They found that adults were more likely to use spellings ‐ous and ‐ic when the nonwords occurred in adjective rather than noun contexts, mirroring the relationship in English words and replicating findings of Ulicheva et al. (2020). However, use of these critical spellings was far lower than would be expected based on the strength of the statistical regularity in English words. Spoken adjectives comprising these word‐final sound sequences are virtually always spelled with ‐ous and ‐ic. Yet, when adult participants with decades of reading experience were presented with these spoken nonwords in adjective contexts, they used these critical spellings only 12% and 50% of the time, respectively. Treiman et al. (2020) argued that “even in some cases in which morphology has a strong influence on the distribution of spellings in the English writing system, it has a fairly weak influence on human spellers.” Further work is needed to understand why this is, and whether similar results are observed in the case of reading behavior.

Conclusions and Emerging Questions

      This chapter opened with the observation that research on reading has been dominated by questions regarding phonological processes. For many years, questions regarding morphological processes were seen as niche, perhaps because the major computational models of reading were focused on processing of words with a single morpheme. That period now seems to have passed and morphological analysis is increasingly recognized as a vital part of skilled reading.

The research described in this chapter provides strong evidence that skilled reading involves the analysis of morphemic information. We have a reasonably good understanding of the form of this analysis and its time‐course in the process of visual word recognition. Yet, there are many questions that require further research. One major question is how we acquire morphological knowledge. Emerging research has suggested that general statistical learning processes may be relevant (Lelonkiewicz et al., 2020; Ulicheva et al., 2020), and training experiments have identified some of the factors that influence acquisition of affix knowledge (Tamminen et al., 2015). However, we do not have a good understanding of the specific mechanism that allows readers to begin to represent morphologically structured words in terms of their constituents. It is also puzzling that after many decades of experience with text, readers’ apparent knowledge of morphological regularities is far weaker than the strength of those regularities in the writing system (Treiman et al., 2020). Computational modeling is one approach that may provide traction in answering these questions.

      Research is also needed to address cross‐linguistic differences in morphological processing. I have suggested that readers analyse morphological structure because (at least in English) it provides immediate information about meaning: whether a word is an object, property, or act. If morphological structure were only weakly associated with meaning, or required much more sophisticated analysis to uncover, then presumably it would not be such a powerful feature of the reading system. Recent work has suggested that English readers (both children and adults) show stronger morphological effects than French, German, and Italian readers (Mousikou et al., 2020). The authors of this work suggest that morphological regularities compensate for the relatively opaque spelling‐sound relationship in English. However, this difference might also reflect the salience of morphological information in the writing system (Rastle, 2019a, 2019b ). Linguistic analysis together with computational СКАЧАТЬ