How to Utilize Your Time
Author: Johnna A. Koonce
In this course, time management has been critical to balancing the complexities of building SAPIENTBOT while staying on top of other academic and professional responsibilities. I divided my workload into weekly milestones, ensuring that every task had dedicated focus and time.
One strategy that worked well for me was using Trello to organize my tasks and track progress. By prioritizing key features like NLP integration early on, I was able to allocate more time to testing and debugging during later stages. However, I did encounter moments where I underestimated the time needed for certain aspects, particularly during the implementation of contextual responses.
In hindsight, time spent on early planning paid off significantly, allowing me to remain focused and hit my project deadlines. Moving forward, I plan to improve my time estimation for more complex tasks by breaking them down even further and allocating buffer time for unexpected challenges.
Improving Productivity through Tools
Utilizing productivity tools was key to staying organized. Here are some that made a significant impact:
Trello: I set up a Kanban board to keep track of the various tasks for each phase of SAPEINTBOT’s development. Each feature had its own column, and I tracked progress by moving tasks from “To Do” to “In Progress” to “Completed.” This system provided a visual representation of my workload and helped me stay on top of deadlines.
Google Calendar: Time-blocking specific hours in my calendar for coding, testing, and meeting with my advisor helped keep my daily schedule structured and productive.
GitHub: Version control was essential to track changes and iterations in my codebase. I made sure to commit progress regularly, which allowed me to go back and review earlier iterations when bugs popped up, saving valuable time.
Balancing the Workload
One of the biggest lessons I learned was how to balance the work involved in SAPEINTBOT with other commitments. Between attending lectures, writing reports, and managing my personal life, it wasn’t always easy to keep up. By setting realistic goals and breaks between coding sessions, I was able to avoid burnout. I also learned the importance of prioritizing tasks that had the greatest impact on the project—focusing on NLP integration early on allowed me to tackle the biggest hurdle first.
Reflection on Time Management Success
Overall, I’m proud of how I handled time management throughout this project. Despite the occasional setbacks, I was able to meet my milestones and make steady progress. This has been a rewarding learning experience not just for the technical aspects but for developing my personal time management skills, which I know will be essential for future projects.
Going forward, I plan to incorporate the lessons learned from this project—especially when it comes to building in buffer time and accurately estimating how long tasks will take. Time management is an ongoing learning process, and I’m eager to apply these skills to the remaining phases of SAPIENTBOT’s development and beyond.
Future Time Management Plans
As I move into the next phases of the project, I’m already revising my time management strategy. With the upcoming focus on user testing and final optimization, I anticipate needing to dedicate more time to feedback loops and refining SAPEINTBOT based on real-world interactions. My plan is to continue with my time-blocking and buffer system, but with an increased focus on flexibility—knowing that some tests may produce unexpected results and require deeper analysis.
By applying these time management principles, I am confident that I’ll be able to bring SAPIENTBOT to full completion on time, without sacrificing the quality of the final product.
