To overcome the skills gap between industry demands and learning outcomes achieved by graduates in higher computing education, many Bachelor programs integrate some form of internship in their curriculum; students are assumed to encounter authentic tasks and recent technologies in the workplace. In practice, however, educators often do not know specifically which tasks their students perform and which technologies they use, mainly due to the distance between coach and student during the work placement and the lack of cohort-based overviews of activities performed in internships. In this study, we gathered and analyzed workplace activity data of 54 students over the course of their third-year semester-long internships in the computing industry. We performed descriptive analyses to gain insight into i) which categories of activities students performed most (programming, research and documentation) and ii) which of the activity categories they find most difficult (research, documentation (both academic and IT) and implementation/configuration). Subsequent text analysis gives us insight into students' perceptions of the categories used to label activities (testing, research, meetings, and academic documentation are congruous) and which technologies were used most by these students. Based on the results, we conclude it is feasible to use user-generated data to get insights into workplace activities of computing interns. The quality of this user-generated data does hamper us in drawing certain conclusions. Further research is needed with improved data quality and volume in order to obtain more generalizable results. © 2019 All rights reserved.
Author Keywords
Index Keywords
