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This study examines the test's predictive validity of English language performance and compares test constructs to identify the most effective predictors of English language performance.

Data were collected and analysed from test scores of students enrolled in the foundation year (N = 84) and level 2 (N = 127) in the faculty of English at a Saudi university using correlation and regression tests.

The findings revealed that the General Aptitude Test (GAT) is effective in predicting English performance for students in level 2 and that the error detection task is the most effective predictor of performance in English reading.

The study provides support for the validity of the GAT as a university admission requirement for English language courses in the Arabic-speaking world.

This study examines the GAT's power using a fine-grained approach by deriving scores from its breakdown constructs to predict the performance of English skills at the university level.