Phonological and Visual Mapping of Letters of a Foreign Alphabet for Educational Software
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2017-08-18
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en
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Abstract
Similarity coding is dominant in the human lexicon. The educational game MindSort is based on
this idea and therefore constitutes a psychologically plausible game for learning vocabulary. Not
only words, also letters are coded based on similarity. MindSort could therefore be extended to
learning foreign alphabets if a distance measure for the letters is found. The present paper
established a distance measure for the Indian script Devanagari by fitting phonological and visual
features on similarity judgement data obtained by ten native Hindi-speakers. The analysis showed
that for both sets of features, all but seven features constituted a significant contribution to the
distance measure. An individual distance measure has also been found for each individual subject.
For almost all subjects, the phonological features were a good explanation of their similarity
judgements and for the visual features it was a good explanation for most of the participants. As the
weights for the features varied per subject, an individual arrangement should be obtained from
MindSort users after they familiarized themselves with the letters such that the game suits the
individual learner’s brain best.
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Faculteit der Sociale Wetenschappen