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 modeling would provide deeper insight into these cross‐linguistic differences.
To conclude, it is interesting to think more widely about the place of morphology in reading. Several chapters in this volume have rightly emphasized that the computation of phonology is a vital part of reading and learning to read (Brysbaert; Castles & Nation; Savage, this volume). Yet, in many cases, what makes the computation of phonology difficult (at least in English) assists the rapid computation of meaning. It might therefore be that the ability to capitalize on morphological information is a critical part of what it means to make the transition from being a novice to a skilled reader.
References
1 Amenta, S., & Crepaldi, D. (2012). Morphological processing as we know it: An analytical review of morphological effects in visual word identification. Frontiers in Psychology, 3(232). doi: 10.3389/fpsyg.2012.00232.
2 Andrews, S., & Lo, S. (2013). Is morphological priming stronger for transparent than opaque words? It depends on individual differences in spelling and vocabulary. Journal of Memory and Language, 68(3), 279–296. doi: 10.1016/j.jml.2012.12.001.
3 Baayen, R. H., Dijkstra, T., & Schreuder, R. (1997). Singulars and plurals in Dutch: Evidence for a parallel dual‐route model. Journal of Memory and Language, 37(1), 94–117. doi: 10.1006/jmla.1997.2509.
4 Baayen, R. H., Milin, P., Đurđević, D. F., Hendrix, P., & Marelli, M. (2011). An amorphous model for morphological processing in visual comprehension based on naive discriminative learning. Psychological Review, 118(3), 438–481. doi: 10.1037/a0023851.
5 Baayen, R. H., Wurm, L. H., & Aycock, J. (2007). Lexical dynamics for low‐frequency complex words: A regression study across tasks and modalities. The Mental Lexicon, 2(3), 419–463. doi: 10.1075/ml.2.3.06baa.
6 Balota, D. A., Cortese, M. J., Sergent‐Marshall, S. D., Spieler, D. H., & Yap, M. J. (2004). Visual word recognition of single‐syllable words. Journal of Experimental Psychology: General, 133(2), 283–316. doi: 10.1037/0096‐3445.133.2.283.
7 Ben‐Shachar, M., Dougherty, R. F., Deutsch, G. K., & Wandell, B. A. (2011). The development of cortical sensitivity to visual word forms. Journal of Cognitive Neuroscience, 23(9), 2387–2399. doi: 10.1162/jocn.2011.21615.
8 Berg, K., & Aronoff, M. (2017). Self‐organization in the spelling of English suffixes: The emergence of culture out of anarchy. Language, 93(1), 37–64. doi: 10.1353/lan.2017.0000.
9 Bertram, R., Schreuder, R., & Baayen, R. H. (2000). The balance of storage and computation in morphological processing: The role of word formation type, affixal homonymy, and productivity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26(2), 489–511. doi: 10.1037/0278‐7393.26.2.489.
10 Beyersmann, E., Castles, A., & Coltheart, M. (2012). Morphological processing during visual word recognition in developing readers: Evidence from masked priming. Quarterly Journal of Experimental Psychology, 65(7), 1306–1326. doi: 10.1080/17470218.2012.656661.
11 Beyersmann, E., Grainger, J., Casalis, S., & Ziegler, J. C. (2015). Effects of reading proficiency on embedded stem priming in primary school children. Journal of Experimental Child Psychology, 139, 115–126. doi: 10.1016/j.jecp.2015.06.001.
12 Boudelaa, S., & Marslen‐Wilson, W. D. (2001). Morphological units in the Arabic mental lexicon. Cognition, 81(1), 65–92. doi: 10.1016/S0010‐0277(01)00119‐6.
13 Brysbaert, M., Stevens, M., Mandera, P., & Keuleers, E. (2016). How many words do we know? Practical estimates of vocabulary size dependent on word definition, the degree of language input and the participant’s age. Frontiers in Psychology, 7, 1116. doi: 10.3389/fpsyg.2016.01116.
14 Burani, C., Dovetto, F. M., Thornton, A. M., & Laudanna, A. (1997). Accessing and naming suffixed pseudo‐words. In G. Booji, & J. van Marle (Eds.), Yearbook of Morphology (pp. 55–72). Dordrecht, Springer.
15 Burani, C., Salmaso, D., & Caramazza, A. (1984). Morphological structure and lexical access. Visible Language, 18(4), 342–352.
16 Caramazza, A., Laudanna, A., & Romani, C. (1988). Lexical access and inflectional morphology. Cognition, 28(3), 297–332. doi: 10.1016/0010‐0277(88)90017‐0.
17 Carreiras, M., Armstrong, B. C., Perea, M., & Frost, R. (2014). The what, when, where, and how of visual word recognition. Trends in Cognitive Sciences, 18(2), 90–98. doi: 10.1016/j.tics.2013.11.005.
18 Castles, A., & Nation, K. (2006). How does orthographic learning happen? In S. Andrews (Ed.), From inkmarks to ideas: Current issues in lexical processing (pp. 151–179). Hove, UK; New York: Psychology Press.
19 Castles, A., Rastle, K., & Nation, K. (2018). Ending the reading wars: Reading acquisition from novice to expert. Psychological Science in the Public Interest, 19(1), 5–51. doi: 10.1177/1529100618772271.
20 Colé, P., Beauvillain,