Repeated Measures Study within Subjects with Randomizations (Python Codes)

Learning a new programming language is challenging for essentially the entirety of our population that decides to try and pick up said skill even those who have previously learned another language find it very difficult. This study investigates the difficulties students face when learning "for" loops in the Python programming language. The research utilizes an eye-tracking device to analyze pupil dilation and blinking rates as participants attempt to solve Python code problems involving "for" loops. The study includes four different code scenarios, each with varying degrees of complexity, including nested "for" loops. The results show that a significant portion of the participants struggled with the tasks, achieving a low average success rate of approximately 28%. Consistent variations in pupil dilation and blinking patterns were observed, indicating high stress levels and potential confusion. The data revealed specific areas of the code where students commonly struggled, particularly with nested “for” loops and the “print()” function. Eye-tracking data revealed consistent variations in pupil dilation and blinking patterns, indicating high stress levels among participants. Teachers should be aware of the identified areas of confusion and design teaching strategies that address them directly. Leveraging eye-tracking data to inform the development of interactive programming exercises or tools that provide more effective visual representations of code concepts can significantly improve student understanding. Therefore, the paper ends with some incipient teaching recommendations and future research directions.