Shaping the precision of letter position coding by varying properties of a writing system

ABSTRACT

There is substantial debate around the nature of letter position coding in reading. Research on a variety of Indo-European languages suggests uncertainty in position coding; for example, readers perceive transposed-letter stimuli (jugde) as similar to their base words (judge). However, these effects are not apparent for all languages. We developed a powerful new method to delineate how specific properties of a writing system shape the representation of letter position. Two groups of 24 adults learned to read novel words printed in artificial scripts. One group learned a dense orthography (i.e. with many anagrams) and one group learned a sparse orthography (i.e. no anagrams). Following four days of training, participants showed a larger transposed-letter effect in the sparse orthography than in the dense orthography. These results challenge existing models of orthographic processing in reading, and support the claim that orthographic representations are shaped by the nature of the writing system.

KEYWORDS:

• orthography
• writing systems
• transposed letter
• letter coding
• artificial language learning

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The materials, data, and analysis scripts for this project can be found on https://osf.io/g74vp/.

ORCID

Kathleen Rastle http://orcid.org/0000-0002-3070-7555

Notes

1 We used non-adjacent transpositions of consonants and vowels for the reason that in our alphabets, the symbols associated with consonants and vowels only occur in certain positions (e.g. vowel symbols do not occur in the third position). We had no predictions about consonant-vowel status on the transposed-letter effect, and note that this comparison in any case is confounded with position of disrupted letters.

2 We chose to investigate transposed letter phenomena using standard lexical decision rather than masked priming because we judged that this would be more suitable for use with an artificial orthography training paradigm. Though there is ample evidence that participants can discriminate trained from untrained stimuli in such paradigms (e.g. Taylor et al., 2017), we are unaware of any evidence suggesting that trained items would yield masked repetition priming effects.

3 We note that there was some indication from by-item analyses that the dense orthography may have been easier to learn for some of the participants (although performance converged by the end of training). This may suggest that there are meaningful individual differences in how these types of writing systems are learned. Future higher-powered studies may wish to investigate this possibility.

Additional information

Funding

This work was supported by Global Research Network programme through the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A2A2035130).