Last Thursday, I headed to the SGV Linux Users Group to listen to a lecture about Summer App Space, a summer program led by Dr. Corbett Moran where LA Students and teachers were selected to participate in a coding apprenticeship program.

Application Selection
Anonymous interviews were conducted on every applicant via a interviewing platform. Those who did well, moved on to an additional platform similar to CoderPad (Google Docs for code), finally 12 applicants were selected out of 120.

All selected students were hired on at CalTech and paid minimum wage. For many of these students it was their first job.

Along with high school students, high school teachers were also selected to participate in the program. This was by design as an experience of multigenerational learning, and as a way to try to get teachers acquainted with programming as teachers who possess programming skills are rare because their skill sets can gain them a much higher pay elsewhere. This portion of the experience had mixed success as high school students often have the expectation their instructors know everything, and the teachers were learning alongside their students so they did not. There was a ratio of one teacher to every three students.

The first four weeks of the program were ran as a bootcamp. Due to facility constraints lectures were held at 8 in the morning. Dr. Corbett Moran stated if she were able to do this again, she would not hold lectures at 8 am, but rather have a flipped classroom, meaning students watch lectures at home.

The final two weeks were for projects.Special emphasis was placed on Teamwork in software engineering.

Dr. Corbett Moran said one particularly important aspect of her philosophy was to ensure the students knew they deserved to be here, we’re not going to filter you out. It was important to treat people like they’re smart and deserve to be there, people tend to rise to the challenge.

Students wrote daily learning journals.

Final Projects

Students were told to make a project using Nasa Satellite Data and human health factors. Their project compared rates of Athesma to air pollution.

Another project was to program a way to classify galaxies using machine learning. Humans still do a better job, for now.

Students also competed in Data Science Competitions on Kaggle.