Data · dataset · 2026
ESP_DualRegister_Vocab_GenAI_ThreeArm
Listed in ScienceDB
This anonymized dataset supports a three-arm classroom study of teacher-validated generative AI for dual-register vocabulary instruction in English for Specific Purposes (ESP).
Description
Six intact undergraduate ESP classes (N = 152; 141 completing pretest, immediate post-test, and four-week delayed post-test) were assigned to one of three conditions: (A) GenAI-enabled dual-register instruction, (B) human-only dual-register instruction, and (C) human-only single-register control.
All conditions used the same 24 target words (six each in Computing, Engineering, Biomedical, and Business), lesson time, review schedule, and assessment points.The deposit includes de-identified participant records, target-word metadata, long-format assessment scores, material-development logs, GenAI draft revision logs for Condition A, and lesson-level implementation fidelity records. Direct identifiers have been removed.
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Files are UTF-8 CSV with an accompanying codebook. The dataset enables reproduction of the study’s analyses and secondary research on ESP vocabulary teaching, register awareness, and teacher-validated GenAI material workflows. Users must not attempt to re-identify participants or institutions.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.45177 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Curriculum and pedagogy 70%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.45177 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:3901 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |