Peer learning in higher education: An effective active methodology to mitigate the university students’ dropout rate

Since the early 2000s the process of globalisation has shown that countries can be competitive and play a key role on the international stage provided that their citizens are given the opportunity to build a significant background in science, technology, engineering and mathematics (STEM). One of the critical issues with regard to the low number of degrees in STEM faculties is that these programmes experience a considerable dropout rate in the first years of higher education. In this context, Italy is no exception with about 20% of its university students who drop out within the first two academic years. In a recent study based on administrative data from the Italian Politecnico di Milano, it has been pointed out that the most important factor which allows to predict Politecnico di Milano student dropout is the number of university educational credits gained across the first term of the first academic year. Since active methods employed in academic courses appear to enhance students’ learning more than traditional lectures even in the context of large size classes, their use could lead to a decrease in the dropout rate. In the academic year 2021-2022 the course “Fisica Sperimentale A+B” at Politecnico di Milano was selected to investigate this hypothesis. We carried out a case study which involved about two hundred freshmen attending the first year of both Chemical Engineering and Materials and Nanotechnology Engineering. In addition to traditional lectures and drills, seven peer learning sessions were provided to these freshmen. During each peer learning session, the learners took a questionnaire consisting of three multiple choice items based on some Physics topics and whose provision was implemented by using the students’ response system Socrative. Considering the documented positive results of the Bring Your Own Device (BYOD) approach, students were allowed to use their own electronic devices, like smartphones, tablets, and laptops. Immediately after the questionnaire and without getting any feedback on the accuracy, freshmen in the classroom would discuss the quizzes in small groups for few minutes. At the end of this debate, they retook the same questionnaire. Finally, the instructor briefly illustrated the correct as well as the incorrect alternatives of each item and the percentage of answers ascribed to each possible option were shown to the students. On account of the fact that some students attended the overall course in person while others attended lessons on line, we had both an experimental and a control group. Their initial level of knowledge in Physics was checked and compared through a questionnaire based on multiple choice items on some Physics topics administered to them at the beginning of the academic course. These items were completely different from the ones employed during the peer learning sessions. In order to evaluate the effectiveness of this education methodology, we considered the freshmen’s achievement in their Physics course final examination during the first exam session. Data related to both the experimental and the control group were collected and analysed through descriptive and inferential statistics. Our findings show that the success rate of the experimental group was higher than the control group and this difference is statistically significant. Moreover, the calculated effect size highlights that the association between the final examination pass rate and the peer learning sessions attendance is relatively strong. On balance, these results appear to confirm that our innovative educational methodology seems to be effective in the mitigation of university students’ dropout rate