Learning Python in an Urban After-School Middle School Program
Suzanna Schmeelk, Columbia University (United States)
Alfred Aho, Columbia University (United States)
Stephanie Wortel-London, New York Academy of Science (United States)
Kanika Bansal, University at Buffalo (United States)
This research explores the psychology of programming and the pedagogical environment in an after school urban middle school program located in a New York City urban school. The program, sponsored by the Department of Education, is aimed at teaching under-represented middle-school students to learn how to write computer programs. Because many of the students had limited, if any, exposure to programming skills, the Python language was selected to introduce computing concepts. The computing concepts and the fostered pedagogical environment were implemented in one-hour after school sessions over 15 weeks in which the students were encouraged to develop computing communities while working on computational thinking concept strands.
The research findings that we report are threefold. First, we report on how we fostered building programming concepts into the curriculum, which is available for download, into a set of activities specifically designed for an after school middle-school program with students ranging in grades 6-8.
We found that at after school program curriculum must be flexible enough for student learning regardless of the fact that a student may miss multiple sessions. Second, we report on how an effective pedagogical environment, which fosters student-centered learning, was promoted so that the students could construct their own meanings of the programming concepts. Third, we report on implementation strategies unique to an after school program, such as after-school specific environmental constraints as well as how sessions were partitioned into components that fostered computational thinking while learning Python. Our findings provide unique insights into intervention constraints for an urban after school program which can be used to guide and inform further after school computer learning research.