Exploring the Impact of Student Backgrounds, Learning Approaches, and AI Usage on Learning Outcomes in a Systems Thinking MOOC

Abstract

This article presents findings from a massive, free-of-charge online extension course titled Systems Thinking, which was conducted in Brazil in May and June 2024. The course engaged 345 participants. The research aimed to analyse how students’ backgrounds, learning methods, and use of AI tools influenced learning outcomes. A mixed-method approach was employed, using electronic questionnaires to collect both quantitative and qualitative data. Quantitative data was analysed with descriptive statistics, while qualitative data was assessed using AI detection software (GPTZero) and a structured rubric. The main findings were: (i) most of the people interested in taking the course were seasoned educators and mid-career professionals, interested not only in the course content, but also in improving their skills and employability; (ii) most students learned by watching the video lectures and doing the modelling exercises proposed in the case studies—few learned from interacting with their peers; (iii) almost all of the students used AI to answer the exam questions, to varying degrees. However, the majority used AI in quite limited ways, and their learning was very effective.