Electroencephalography (EEG) provides precise neural measures for brain-computer interface (BCI) applications monitoring cognitive states. This empirical study evaluates the sensitivity of established EEG spectral markers to distinguish sustained attention from cognitive engagement. Fifteen participants completed a sustained attention task (D2-R), a N-Back working memory task (2-Back), and an ecological video learning task. Results indicate that the sustained attention task induced significant modulations in the β /(α + θ ) ratio, posterior theta, and occipital beta power. Conversely, the cognitive engagement task yielded no significant spectral deviations, highlighting potential overlaps in cognitive networks and the critical impact of task-order effects on post-effort baselines. Furthermore, linear mixed models revealed distinct, non-linear temporal dynamics during the ecological task, demonstrating that aggregating EEG metrics over the entire task duration obscures critical real-time state fluctuations. This study provides a rigorous framework for selecting appropriate EEG markers, emphasizing the necessity of continuous monitoring and controlled experimental designs in educational BCI applications.