This experience is the sum of 3 classes that I took while pursuing a computer science minor at UMBC. Although I was not able to completely finish the minor, all classes opened me up to the world of computer science and I was able to learn a lot about coding in both C++ and Python. The classes that I took were CMSC 201 (Fall 2017), CMSC 202 (Spring 2018), and CMSC 203 (Fall 2018). CMSC 201 was a 4 credit class, CMSC 202 was a 4 credit class, and CMSC 203 was a 3 credit class. In completing these 3 classes, the total sum of time spent through the 3 semesters taking them was 154 hours.

This experience is considered interdisciplinary because computer science is outside of my major. I had to learn how to solve problems and finish projects in a different ways. One of the pre-approved experiences on the GCSP website is completing a minor in a related area with clear alignment to my grand challenge, and another pre-approved experience is completion of a course in an area outside my major with clear alignment to my grand challenge. By completing 3 classes outside of my major, I anticipate this experience falling somewhere in between these two pre-approved experiences.

Taking these classes really taught me a lot about time management because the projects were never something I could complete in a day’s time. I constantly had to work my schedule around sitting down and completing the assignments for computer science. I also learned a lot about problem solving, and how a lot of the type of thinking used in computer science intersects with engineering. Often times I have to think broadly about the way an assignment should be started, and break the problem into smaller pieces. I do the same thing in engineering. I didn’t know a lot about coding before, but now I feel like I am capable of doing at least base level code, or even learning C++ further in future projects.

A lot of employers these days are looking for people who not only have experience with the normal mechanical engineering coursework, but also have expanded their learning to coding and programming. Because so much of the world is turning into technology, the things I learned in these courses have opened me up to a lot of opportunities and I hope it will continue to do so. For instance, I was able to work on programming a HoloLens for a previous summer research project, and this was only possible because of my broadened education.

While the experience is not completely estranged from advancing personalized learning, the experience is also not about education or learning specifically. The reason I think that these classes relate to advancing personalized learning, is because technology is a very real solution to the personalizing the student experience. Systems like ALEKS, Khan Academy, and PackBack allow for students to get the one on one attention they need as well as allow for further analyzing and understanding of their strengths and weaknesses. Technology now more than ever is necessary to keep college classes functioning (like with Blackboard Collaborate, WebEx, and Google Classrooms). Taking these computer science classes have taught me some of the skills about coding in C++ and Python that I can take into the world of coding compute programs and student user interfaces or even games to track student progress.

Flexibility was one of the program-wide learning objectives that I felt this experience contributed to the most. As far as coding is concerned, there were always obstacles that needed to be overcome. When there was a bug in my code, nothing else seemed to work. I had to learn how to adapt to these changes and obstacles quickly by going to office hours, reaching out for help, and working extra hours or long nights to fix what was broken. Additionally, the objective of having a realistic vision applied greatly to the work I did. The code I was making was meant to be used in a real world situation, with real world constraints. This required me to be mindful of the running time of the code which we learned about for a lot of the time spent in the class. If the code spent too long working out a problem that could have been done faster, this could negatively affect the application in real life.

By taking these classes, I was able to identify the different disciplines that contribute to the solution of a complex problem. When looking at my grand challenge to advance personalized learning, I payed specific attention to the way mechanical engineering and computer science played a role in this. Personalized learning programs were created nowadays to test student abilities and record data with regards to their performance.

I described and applied strategies for creating common ground between different disciplinary perspectives. In my mechanical engineering major, we were taught to solve problems by outlining what we have been given and then building off of that. Similarly, in computer science a sense of groundwork has to be created before started a big project and a plan has to be made. Both disciplines have similarities in the way that problems are laid out and I was able to realize that they have an iterative nature to their problem solving process. In future classes such as my MATLAB class, I was able to apply these methods to a mechanical engineering class that required coding.

I described and apply bridging strategies that facilitated the conscious integration of different disciplines. Computer science classes are inherently challenging, and so the challenges I faced mainly had to do with time management and study habits. If I did not have good study habits, then I would not have been able to pass the classes and this would jeopardize my completion of this grand challenge experience.