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Table 1 Mean Sample Difficulty on English Language Features

From: An enduring lens for a continuing problem: Close analysis of conceptually scored cloze items

Student Sample No. of pupils Noun At’cle Verb Prp’n Tchlty Word Stacks Pas’ve Voice Cohsv Device Overall D’fclty
% % % % % % % % %
wrong wrong wrong wrong wrong wrong wrong wrong wrong
n=18 n=5 n=12 n=5 n=10 n=6 n=3 n=15 n=50
U/G Chinese 114 53.17 (SD=13.73) 39.30 (SD=21.27) 51.90 (SD=21.12) 47.19 (SD=18.65) 47.81 (SD=20.51) 32.02 (SD=19.97) 42.98 (SD=28.65) 37.60(SD=17.87) 48.63 (SD=15.09)
Rank @ 1 4 2 3 1 4 2 3  
Secondary EALD # Rank 2 4 3 1 3 4 2 1  
679 42.89 (SD=18.06) 28.19 (SD=26.93) 39.80 (SD=25.84) 48.22 (SD=23.80) 31.69 (SD=20.29) 18.14 (SD=18.63) 36.38 (SD=33.19) 46.55 (SD=19.03) 43.41 (SD=19.83)
Secondary English 127 47.55 (SD=23.18) 30.08 (SD=28.72) 40.16 (SD=29.55) 41.10 (SD=26.94) 39.29 (SD=26.49) 25.33 (SD=26.05) 34.12 (SD=34.75) 45.88 (SD=23.36) 44.38 (SD=24.34)
Rank 1 4 3 2 2 4 3 1  
  1. Notes:
  2. @ Rank = Rank within category, most difficult = 1.
  3. #EALD = English as an Additional Language or Dialect.
  4. Table 1 is based on analysis of student responses on a single cloze test.
  5. *Student data was recoded so that a clear error = 1 and acceptable replacement = 0.
  6. *Cloze test deletions were classified by language category.
  7. *Two SPSS routines were written (“dictionary categories” & “modern grammar categories”).
  8. These did the following:
  9. 1 count number of items representing a particular language category (eg., nouns) coded as clear error.
  10. 2 divide that number by the number of items representing that category (eg., nouns) deleted (in this case, 18) to give the mean category (in this case, noun) difficulty.
  11. 3 multiply that mean by 100 to yield a percentage.
  12. 4 average that mean across the particular student sample (114 students for the undergraduate Chinese group: 53%).
  13. The top row language descriptors are discussed previously, in Deletion categorization. The number at the base of each heading refers to the number of deletions categorized as reflecting that descriptor.
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