Until today, in the field of motor learning and rehabilitation, haptic controllers were mostly limited to teach simple tasks such as movements along straight lines, curves, or circles. However, commonly, real-life tasks consist of more complex movements such as in writing, rehabilitation, or surgery. In this paper, a novel haptic controller for robot-assisted learning is introduced. This hybrid path controller can cope with interfering path sections, while it also incorporates the common requirements of effective motor learning: it allows freedom for making spatial errors, free timing to explore the task dynamics, and adaptation to the current skill level of the user. In a practicability study with two different robots, results confirmed the full functionality of the controller and its applicability for a broad range of complex movements.