The proliferation of digital command and control systems on the modern battlefield places a growing training requirement on Soldiers at all echelons to acquire and maintain the skills to operate those systems. With the increased demand to develop and maintain highly proficient system operators, some Army units have utilized distributed learning (dL) technologies to train digital skills. As dL instructional environments have unique training challenges and little is known about the effectiveness of training digital skills using dL, there is a critical need to know whether Soldier performance following dL instruction differs from traditional (face-to-face) classroom instruction. In this paper, we compare Force XXI Battle Command Brigade and Below (FBCB2) operator skills of Soldiers given either dL (Baseline N = 136; Retention N = 32) or face-to-face (Baseline N = 80; Retention N = 31) instruction immediately and eight weeks following the training. Although the results demonstrated some differences in proficiency on specific tasks at baseline, the declines in performance over time were very similar for both classes. For example, even though Soldiers in the traditional classes performed better on some of the tasks immediately following the course, both classes performed similarly eight weeks later. These findings provide support for dL instruction of digital skills as being comparable to that of traditional instruction. Our testing procedure also made it possible to examine performance for each step of each task (e.g., create and send a route), and these results provided a better understanding of why certain tasks were problematic (e.g., system does not cue the operator). Finally, from these findings, we suggest ways in which training developers can design courses and trainers can present materials to enhance initial performance and mitigate decrements in skill over time.