70 international university students participated in a study examining relationships among generative AI acceptance, human-AI collaboration behavior, and second language writing development. The dataset contains questionnaire responses and pre-post AI-assisted writing performance measures. It was authored by Xie, Jingyi and last updated on 2026-04 14.
Use Cases
- Modeling the relationship between AI acceptance and writing performance based on questionnaire responses and performance measures
- Analyzing human-AI collaboration behavior patterns based on the RD, LAS, and ID measures mentioned in the description
- Studying the impact of AI assistance on multidimensional L2 writing development based on syntactic complexity, lexical richness, and accuracy metrics
Strengths
- Dataset includes responses from 70 participants.
- Measures multiple dimensions of writing development: syntactic complexity, lexical richness, and accuracy.
- Includes both questionnaire data and pre-post performance measures for analysis.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- Data may reflect geographic bias inherent to the specific international student sample.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Likely collected via questionnaires and academic writing assessments from university students.
- Time Range
- null
- Freshness
- Last updated 2026-04-14 01:33:25; freshness should be verified.
- Geography
- International university students; specific countries are not detailed.