There has been a rapid growth in human motivation research in the last two decades, with a special emphasis on achievement-oriented studies. Recent research in the motivation area has focused on achievement goal orientations, as there has been an increase in achievement goal research in social, psychological and specifically educational studies. In the context of Iranian’s educational system, every year many students enter universities based on academic achievement during their high school period. Among them some find the way to enter Medical Universities with different motivation factors. Learners’ motivation to succeed as university students varies and motivation is crucial to their Performance. Taking into account the competitive nature of medical education and the responsibilities upon medical students and their critical role in patient care, it is significant to know the types of achievement goals namely “mastery-oriented goals” and “Performance-oriented goals” that medical students develop in their educational career. In addition, medical teachers’ perspective regarding these goals and what approach is adopted by them if of utmost importance in terms of learning. By the same token, as the practice of medicine is dynamic and lifelong learning is essential, mastery-oriented learning can ensure that graduates are more qualified for their future tasks as medical doctors.

Introduction: Clean, noise-free data are ideal but often unattainable in biological control systems. Filters are usually employed to remove noise. But this process also leads to the loss or alteration of information. A considerable challenge is managing the uncertain knowledge using a proper and realistic mathematical representation and staying consistent with biological patterns and behaviors. This study explores the potential of fuzzy logic as a computational paradigm to manage uncertainties in the nonlinear dynamics of human walking. This field has paid little attention to this aspect despite its considerable nonlinear and uncertain behavior due to adaptability, muscle fatigue, environmental noise, and external disturbances. Methods: We employed a fuzzy logic-based controller integrated with functional electrical stimulation (FES) and a gait basin of attraction concept to enhance gait Performance. Our controller focused on accommodating imprecision in shank angle deviation and angular velocity rather than relying on predetermined trajectories. Results: Our findings indicate that more fuzzy rules and partitions improve the similarity of the gait dynamics to those of a healthy human. Moreover, higher membership function overlaps lead to more robust gait control. Conclusion: The study demonstrates that fuzzy logic can effectively manage uncertainties in the nonlinear dynamics of human walking, improving gait Performance and robustness. This approach offers a promising direction for goal-oriented rehabilitation strategies by mimicking the human mind’s ability to handle challenging and unknown environments.