Discovering a Hidden Facet of the Impact of Deletion Order on the Comprehension of C-tests
Bibliographic record
Abstract
Cloze test is widely known as an effective technique in testing reading comprehension. However, since the validity of cloze test was questioned by some language experts, a modification of cloze procedure, called C-test, was then proposed. The present study was meant to explore the effects of the position of letters deleted in a C-test on the comprehension of the test; namely, the restoration of the deleted letters. In a standard C-test, the first half of every second word is deleted but in this study an adapted version of a C-test was employed in which the second half of every other word was deleted. A group of high intermediate students (N = 50) learning English at the Iran Language Institute (ILI) participated in this study. The two different versions of the test (the adapted version and the standard version) were randomly administered to the participants of the study so that some students received the standard version and the others the adapted version. Independent samples t-tests were run to analyze the data and the analysis of the data revealed that students taking the standard version of the test had significantly performed better on the test than those taking the adapted version. This indicated that the order of the deletion of the letters in a C-test would affect the comprehension of the text based on which the C-test was prepared. Further analysis of the data revealed that, interestingly enough, five of the highest scores obtained on the two versions of the test belonged to five students who had taken the adapted version of the test. The results of an interview with these students showed that they were used to reading extra material, especially English newspapers and English short stories a lot and that this had helped them increase their reading proficiency to a great extent compared to the other students, especially those who had taken the standard version of the test.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.175 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".