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Data · dataset · 2026

Understanding EFL Teachers’ Affective and Cognitive Responses to ChatGPT in Higher Education

Listed in Teesside University Research Data Repository

The anonymised questionnaire dataset comprises 187 valid responses from higher-education EFL teachers collected via an online survey platform.

Description

All responses were anonymous and measured using a five-point Likert scale (1 = strongly disagree; 5 = strongly agree). The instrument was developed based on an extended Technology Acceptance Model (TAM) framework and operationalised nine latent constructs: perceived usefulness (PU), perceived ease of use (PEU), attitude towards use (ATU), behavioural intention (BI), facilitating conditions (FC), technological complexity (TC), anxiety (ANX), self-efficacy (SE), and AI experience (AIE).

Each construct was measured with three to four items. The complete questionnaire, including construct definitions and full item wording, has been provided as a supplementary “Item File.” The main dataset contains item-level coded variables (e.g., PU1–PU4, PEU1–PEU3), which correspond directly to the detailed descriptions in the Item File. Structural equation modelling (SEM), including confirmatory factor analysis (CFA) and structural path analysis, was conducted using AMOS 22.0 to evaluate both the measurement and structural models.

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Descriptive statistics (means and standard deviations) for all observed variables were calculated in RStudio. Mediation effects were examined in R using bootstrapping procedures with 5,000 resamples to estimate indirect effects and to generate bias-corrected 95% confidence intervals.

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Topics

Inferred from text
Teacher and student wellbeing 77%
Provenance · 1 source records, 11 field assertions
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