ABSTRACT
This study documents and assesses the Tool for Automatic Measurement of Morphological Information (TAMMI), which calculates measures related to basic morpheme counts, morphological variety, morphological complexity, morpheme type-token counts, and variables found in the MorphoLex database (Sánchez-Gutiérrez et al., 2018) including morpheme frequency/length, morpheme family size counts and frequency, and morpheme hapax counts. These measures are assessed in two studies that include a word frequency measure as a control variable. The first study examined links between morphological variables and judgements of reading ease in a corpus of ~ 5000 reading excerpts, finding that variables related to derivational variety, word frequency, affix frequency, and morpheme counts explained 40% of the variance in the reading scores. The second examined links between morphological variables and human assessments of vocabulary proficiency in a corpus of ~ 7000 essays written by English-language learners (ELLs), finding that the number of morphemes, morpheme variety, and the number of roots explained 21% of the variance in the human assessments.
ABSTRACT
This paper introduces the CommonLit Ease of Readability (CLEAR) corpus, which provides unique readability scores for ~ 5000 text excerpts along with information about the excerpt's year of publishing, genre, and other metadata. The CLEAR corpus will provide researchers interested in discourse processing and reading with a resource from which to develop and test readability metrics and to model text readability. The CLEAR corpus includes a number of improvements in comparison to previous readability corpora including size, breadth of the excerpts available, which cover over 250 years of writing in two different genres, and unique readability criterion provided for each text based on teachers' ratings of text difficulty for student readers. This paper discusses the development of the corpus and presents reliability metrics for the human ratings of readability.
