Abstract:

Within the domain of scientific research, the integration of scientific inquiry with computational proficiency emerges as a cornerstone of academic excellence. As professors of an Oceanography master's degree focused on research, we observed that most of our students possess minimal or no prior programming experience. In response, a collaborative consortium of educators initiated an educational effort to cultivate proficient programming skills while imparting domain-specific knowledge from two courses within the curriculum. Coordinated by the teachers of these courses, three distinct methodologies were employed sequentially, each educator bringing their unique expertise and pedagogical approach to enrich the learning experience and accommodate diverse learning preferences and needs.

The first methodology adopts a traditional lecture-based format, wherein foundational programming concepts are systematically introduced during magisterial classes. Python is the primary instruction tool adopted due to its widespread use within the scientific community. These classes comprehensively explain Python syntax, data structures, control flow, and other fundamental programming principles. By providing a solid theoretical foundation, students clearly understand programming and Python's core concepts, setting the stage for subsequent hands-on learning experiences. A series of exercises accompany these theoretical sessions, and the students must solve them using the tools provided during the theoretical classes under the guidance of the teachers.

The second methodology embraces project-based seminars, wherein students are immersed in real-world scientific problems. At this point, students are encouraged to leverage online resources, such as forums and artificial intelligence tools, to solve the issues. These sessions serve dual purposes: refining self-learning capabilities and honing their critical thinking skills to distinguish between reliable and dubious sources. By tackling authentic scientific challenges, students deepen their understanding of Python programming and cultivate invaluable research skills for effectively navigating the scientific landscape.

Building upon the foundational knowledge and skills acquired in preceding methodologies, the third methodology introduces a series of coding projects intertwined with scientific contexts. Emphasis is placed not only on technical proficiency but also on articulating problem-solving strategies and demonstrating a clear understanding of implemented solutions. Students must present their code comprehensively, explaining their rationale and showcasing their comprehension, discouraging reliance on external aids for code completion, like ChatGPT, without understanding.

Every student exhibited notable progress in their programming skills. They tackled coding exercises, showcasing their enhanced ability to think programmatically, navigate scientific problems, and foster self-learning aptitude and critical thinking skills. Thus, this educational experience transcended the mere acquisition of technical proficiency, fostering appreciation for the relationship between oceanography and computational tools among students.

Keywords:

Critical thinking, collaborative teaching, post-graduate education, project-based learning, scientific problem-solving.