Using Coding Competitions to Develop STEM Skills in Graduate Education

Abstract

Contribution -We present the results of the development and implementation of an extra-curricular process to assist university students to develop skills in data analysis. We offered coding workshops in R and Python. To motivate the students to participate in learning and to practice the learned skills, we set followed a learning workshop with a contest on text data mining.Background -University credit-bearing education is often streamlined to cover increasing amounts of subject matter knowledge in class. It is not usually possible for faculty to take time from their curriculum to develop basic analytics skills, such as the use of R or Python for business analytics. Extra-curricular skills-building activities are an effective vehicle to develop these skills outside class. Research questions - Do extra-curricular workshops to learn coding result in successful learning? Would a coding contest after the workshop drive attendance? What are the elements of a successful workshop and coding contest, and what are acceptable metrics and levels of performance for these contests? Methods- Coding workshops were developed and offered as extra-curricular opportunities for students in a STEM graduate program. After the coding workshops, short-duration coding contests were launched. The goal of the contest was to develop text analytic tools that could be used by the students to advance their academic careers. Attendance in the workshop as a percent of the student body and quality and number of coding contest submissions was a metric of success. Contest participation and successful submissions were a second metric. Results - Two workshops were run with concurrent contests. An average of 10% of the student body registered, and 5% attended. Contest submissions were received, and in each case, at least one submission yielded a usable tool. The tools were subsequently used by students in their job search and to conduct research.