This observational analysis reveals that mastery-focused goals enhance academic achievement through deep learning strategies.
This study investigates how task-focused, self focused, and other-focused goal orientations influence academic achievement thtough deep and surface learning strategies among engineering students, drawing from the 3 × 2 achievement goal framework and the Students' Approaches to Learning (SAL) model. Data from 294 participants revealed that mastery-focused goals (task and self-focused) are positively associated with deep learning strategies, which in turn predict higher academic achievement. Conversely, surface learning strategies negatively impact academic achievement, with limited mediation effects for achievement goals. Interestingly, other-focused goals are linked to deep learning but fail to significantly predict academic outcomes, suggesting that external motivations may lack the depth needed for sustained academic achievement . The findings highlight the critical role of fostering mastery-oriented goals and deep learning strategies to enhance academic achievement. These insights provide actionable implications for educators, emphasising the importance of promoting task engagement and mastery-driven classroom environments to optimise learning outcomes in engineering contexts.
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Fabiyi et al. (2025) studied this question.
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