Effect of Teaching Complex Noun Phrases for Reading Comprehension Purposes in EAP Programs
Bibliographic record
Abstract
Complex noun phrases (CNPs), defined as phrases where a noun is the head modified by preceding or following lexical items, are a major vehicle of written academic English. However, CNPs are typically not explicitly addressed in English for Academic Purposes (EAP) programs for English language learners (ELLs) for reading purposes even though they present considerable challenges to ELLs in terms of processing and comprehension. This manuscript-based doctoral dissertation reports on a quasi-experimental mixed methods study that aims to investigate whether explicit instruction on the structure of CNPs and the parsing and paraphrasing strategies aimed to help the students expediently and accurately interpret them results in more accurate interpretation of sentences containing them. A two-phase mixed-methods study resulted in three publications in peer-reviewed journals. Phase 1 of the study involved designing and validating a pilot CNP comprehension test and investigating the specific challenges ELLs may have with processing and interpreting various CNPs. The results of both the CNP test and the interviews signal significant CNP parsing and interpretation challenges on the part of EAP students, identify the types of CNPs and the parsing and interpretation tasks that they find especially challenging, and underscore the need for explicit instruction on the structure of CNPs for reading purposes. Phase 2 of this study, published as two peer-reviewed articles, involved design and instruction of four teaching modules to an experimental group of 96 first-year EAP students consisting of several college- and university-based EAP classes, and measurement of their success in parsing and paraphrasing CNP through a pre- and a post-test and exit interviews/verbalization task. A comparable control group was given just the pre- and the post-test. The results of Phase 2 of the study suggest that the teaching intervention had a significant effect on the post-test scores, and that the participants considered the CNP reading strategies a useful enhancement of the academic reading curriculum and were able to apply most of the CNP parsing and interpretation strategies in the strategy verbalization task.
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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 | 0.003 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".