Abstract:

Teaching basic programming to engineering students has proven to be a difficult endeavor, especially when having an heterogeneous population with different backgrounds and previous knowledge on the topic. Among the most pressing issues, keeping the student’s motivation and interest during the course is the one we strongly believe could make a difference in the overall development of computational thinking skills.

In this work we propose the use of a technological platform that provides students with programming exercises and mini-challenges that are automatically graded and feedback is given to students immediately. Exercises are drawn from a large pool previously created and reviewed by several instructors. The platform allows students to practice with exercises from different programming topics and levels, anytime, anywhere, without a tutor overseeing their performance. Each exercise has been defined with test cases, thus, in case the student fails to provide a correct answer, the system is able to identify the specific case for which it failed, and pinpoint the errors. The main purpose of the platform is to foster personalized learning and provide feedback whenever the student requires it. We believe that providing this personalized attention will increase the student's motivation to learn programming and acquire computational thinking skills.

In order to test our initial hypothesis, we had 66 users from 8 introduction to programming courses using the platform during the Autumn 2023 semester at Tecnologico de Monterrey Campus Puebla. Students started the course with the traditional curricula and usual programming activities, and used the platform after their mid-term exam. A motivational questionnaire was applied after the first half of the course, and then again at the end of the semester after using the platform. Data obtained from both questionnaires was paired in order to analyze the changes in each student’s perception about the course.

In this paper, we discuss the findings of interest obtained from the analysis of the collected data. Although the outcome was not what we expected, we obtained interesting insights into what triggers students’ motivation while learning programming topics. In the conclusions, we include these insights and propose changes to the experiment that will allow us to further pinpoint the impact of the platform use without drawing attention from other variables or circumstances.

Keywords:

Computational thinking skills, adaptive mentoring, automatic feedback.