Design and Implementation of a Python Based College Student Schedule Planning Program

This study presents a project concept aimed at designing software to help college students improve work efficiency and quality of life. This is achieved by integrating user data collection, schedule planning, machine learning, and learning efficiency optimization. Initially, we describe the projects fundamental steps, including generating random schedules and capturing changes in user input attributes. Then, we discuss how the program analyzes trends in student performance and physical condition in comparison with randomly generated schedules to identify optimal study times and suitable learning environments. We also explore methods to determine when students perform best, which subjects or tasks are easier for them, and factors that may affect learning efficiency. Finally, we emphasize the potential of machine learning methods in developing more effective planning for students, thereby enhancing learning efficiency. Future scalability of this software is also discussed. This research introduces innovative methods to education and learning, potentially impacting student academic performance and learning experiences positively. Zhicheng Li | Jialan Zhu | Jiapeng Bao | Hang Yu | Xinwei Dai "Design and Implementation of a Python-Based College Student Schedule Planning Program" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-6 , December 2023, URL: https://www.ijtsrd.com/papers/ijtsrd61244.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/61244/design-and-implementation-of-a-pythonbased-college-student-schedule-planning-program/zhicheng-li