The importance of using the CodeInsights monitoring tool to support teaching programming in the context of a pandemic

This Innovative Practice Full Paper describes the use of a monitoring tool for teachers to assess students' performance and progress, improving their ability to make decisions and interventions in programming classes, in the context of the current COVID-19 pandemic. Considering that learning programming is not an easy task as well as the social, cultural, and educational diversity of the student population, we believe it is crucial that teachers have at their disposal up-to-date information on the learners' progress, skills, and difficulties to properly support them in gaining and maintaining a positive learning momentum. Previously, we suggested the use of this monitoring tool to supplement the information teachers can obtain through direct observation in traditional face-to-face classes. However, in the context of the current pandemic, its use takes on new significance since, in most cases, face-to-face instruction has been suppressed, demanding new strategies to collect assessment data. In this paper, we introduce some features of the system and explain how they can help teachers to support their students. Key findings from a field trial, in which the system was used for about a month and a half to support more than 60 students of an introductory programming course, are also presented. Due to COVID-19 lockdowns and stay-at-home orders, classes took place almost exclusively online via Zoom. During this time, the usage of the system enabled the teacher to monitor student progress regardless of when or where they were working. In post-experiment interviews, the teacher who participated in this study stated that using the system was vital to deal with the challenges that distance learning entails. Similarly, student feedback was also very positive. Several students mentioned that they felt more confident while using the system, knowing that the teacher was able to track their work and give them personalized feedback whenever necessary.