This poster presents our experimental design, which will be implemented next semester, and shares insights from a preliminary version already executed. We will describe a method for managing the diverse content requirements of groups engaged in advanced open-ended projects. Our approach, termed “micro-specialization,” involves students selecting specific tracks to acquire the knowledge needed for their chosen project. These tracks are comprised of individual activities designed to teach new knowledge that hasn’t been covered before. Each student specializes in one track, gaining expertise, and then brings this new knowledge back to their group.

The concept of individuals within a group specializing in different areas during an open-ended project is not extensively explored in the literature. While collaborative learning has been shown to benefit students in such projects, and flexible course designs with personalized objectives enhance motivation and academic performance, traditional methodologies like Jigsaw are typically applied to brief, specific activities under close faculty guidance. In contrast, our approach brings students together with the shared objective of completing an open-ended project, requiring them to collaboratively manage and execute the necessary tasks. This method introduces a novel application of collaborative strategies in a less structured educational environment.

We plan to assess the effectiveness of this methodology by analyzing students’ perceptions of their knowledge before and after completing their projects. Through a evaluation at the end of the semester, we aim to measure students’ knowledge in all specializations to verify if collaborative learning occurs. Additionally, we will analyze individual student contributions to the project code. Using git blame, we can associate each section of modified code with a student and their track specialization. This will allow us to measure how much each student is contributing to their specialization and their ability to contribute to other specializations.

Link to Presentation: https://youtu.be/5TSH7YdWYdY