2025 ASEE Annual Conference & Exposition

Design thinking in scientific modeling emphasizes creativity, collaboration, and iteration, making it highly beneficial in education. It encourages deep engagement with scientific concepts, enhancing critical thinking and problem-solving skills. As Inkinen et al. (2020) noted, model development is a fundamental scientific practice that aids students in understanding complex phenomena by providing explanations and facilitating predictions about the natural world. This approach fosters an active learning environment where abstract concepts become more accessible (Citrohn & Svensson, 2020).

The iterative nature of design thinking allows for continuous refinement of models through feedback and evaluation. Mentzer et al. (2015) highlight that models can be visual, graphical, or mathematical, essential in engineering design processes. This flexibility helps students explore multiple solutions, deepening their understanding of scientific principles. Emphasizing feasibility and evaluation encourages students to assess their models critically, ensuring they are both theoretically sound and practically applicable.

Incorporating design thinking into science education enhances students' epistemic knowledge, which is their understanding of the nature and justification of scientific knowledge. Lee (2023) explains that experimentation and model development help students navigate scientific inquiry complexities, such as hypothesis formulation and data analysis. This process is vital for cultivating scientific literacy, empowering students to construct evidence-based arguments, and engaging in meaningful discussions. Argumentation within this framework enriches learning as students articulate reasoning and critique peers' models.

Research indicates that model-building demands critical thinking and creativity. Dauer et al. (2013) emphasize the need for genuine motivation beyond compliance with school tasks, suggesting modeling should connect molecular phenomena to broader concepts, reflecting students' understanding of scientific principles.

Selecting appropriate representations is crucial for effectively communicating scientific ideas. Peterson et al. (2021) discuss cognitive image functions that enhance comprehension through visual displays. Understanding these functions helps students articulate invisible aspects of phenomena, enriching explanations. Park et al.'s (2021) findings show that collaborative drawing activities facilitate the negotiation and refinement of visual representations.

The cognitive demands of modeling are significant as students navigate complex content and representation design. Minkley et al. (2018) note that developing representations simplify natural phenomena's complexity, requiring identifying relevant aspects and relationships akin to a design process considering functionality.

Teachers play a crucial role in supporting modeling practices. Baumfalk et al. (2018) stress the importance of creating environments for effective model construction and utilization, guiding students through iterative processes where they refine models based on feedback and evidence. Such support is essential for developing skills necessary for modeling as a practice rather than a task.

The project with preservice science teachers explored how they design models to explain phenomena. Pedagogical tools were developed to scaffold this process, with groups presenting models using meta-representations to explain occurrences while peer feedback enhanced feedback skills. Key findings included shifts in designs based on evidence or feedback across iterations, variations in initial designs, and an initial focus on objects rather than invisible components.