Deep learning has emerged as an educational approach that emphasizes mindful, meaningful, and joyful learning processes. This study aims to examine the effect of deep learning understanding on teacher readiness among Economics Education students at the Faculty of Teacher Training and Education, Halu Oleo University. Employing a quantitative approach, this study examines deep learning understanding as the independent variable and teacher readiness as the dependent variable. The respondents comprised 100 seventh-semester students who had completed the School Field Introduction Program. Data were analyzed using normality and linearity tests, simple linear regression analysis, a partial (t) test, and the coefficient of determination. The findings indicate that deep learning understanding has a positive and significant effect on teacher readiness, as evidenced by a t-value of 7.845 and a significance value of 0.000 < 0.05. The coefficient of determination (R²) of 0.674 indicates that deep learning understanding accounts for 67.4% of the variance in teacher readiness. These findings underscore the importance of strengthening students' understanding of deep learning as a strategic foundation for preparing Economics Education students to become adaptive and professional prospective teachers.
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