Abstract:

In the context of the European Higher Education Area (EHEA), engineering education is shifting from traditional lecturing toward student-centered methodologies. Strategies such as Peer Teaching have proven effective in fostering engagement and communication skills. However, a recurring limitation in implementing Peer Teaching in complex technical fields—such as Biomedical Engineering—is the "expert dilemma". When students assume the role of instructors based solely on literature reviews, they often reproduce theoretical concepts without genuine comprehension, leading to the transmission of superficial knowledge to their peers.

To mitigate this limitation, this paper presents a "Practical-First" Peer Teaching methodology. The core hypothesis is that for Peer Teaching to be valid and effective in technical subjects, the "student-teachers" must first act as practitioners. They must transition from passive readers of documentation to active verifiers of technology before stepping onto the podium.

This methodology was implemented in a Master’s Degree in Biomedical Engineering course focused on Artificial Intelligence in Omics Data. The cohort of 11 students was divided into small "expert groups," utilizing a structure similar to the Jigsaw cooperative learning method. Each team was assigned a specific stage of the genomic workflow: Sequence Alignment, Variant Calling, or Annotation & Interpretation. Unlike standard seminar preparations, the assignment required students to practically deploy the AI approaches. They were tasked with identifying, installing, and benchmarking specific AI-powered tools, analyzing technical features and performance metrics against traditional methods.

The culmination of the project was a series of Peer Teaching sessions where students took on the full role of professors. The evaluation strategy was designed to enforce the quality of this peer-to-peer knowledge transfer. The final assessment (70% instructor, 30% peer evaluation) specifically measured "Teaching Ability" and "Content Understanding," ensuring that students were accountable not just for their research, but for their ability to effectively explain complex AI concepts to their classmates.

To assess the validity of this approach, satisfaction surveys were conducted. These measured the students' perceived competence in the specific genomic stage they taught versus the stages they learned from their peers, as well as their confidence in handling complex questions. Preliminary results indicate that anchoring Peer Teaching in mandatory practical experimentation significantly raises the quality of the discourse and transforms the classroom into a collaborative research environment.

Keywords:

Peer teaching, Active Learning, Biomedical Engineering, Higher Education.