Decisions about effort are a part of everyday life and have important implications for survival. While several studies have explored effort learning tasks and investigated the underlying mechanisms, a critical aspect remains unexplored - the reliability of effort learning over time. Uncovering whether effort learning rates are trait- or state-based is an important step in fully understanding the mechanisms involved. The aim of this study was to identify the test-retest reliability of a well established effort learning task. A cohort of 28 participants completed an adapted version of the task, with at least one week between sessions. At each session, participants learned to associate cues with dynamically changing physical effort level targets and corresponding reward magnitudes. Task performance was incentivized using monetary rewards. Employing a mixed regression model, our analysis revealed that the force exerted in the previous trial (p = > 0.001), along with previous points (p = 0.013), but not previous failures (p = 0.08), significantly predicted the force applied in the current trial. The ICC was calculated, and preliminary findings indicate reasonable test-retest reliability over two timepoints for previous effort (R = 0.58), previous failure (R = 0.63), and previous points (R = 0.49). These results indicate that effort learning seems to be stable over time and contribute to the broader comprehension of the mechanisms involved in effort learning.