Computational thinking has become central to contemporary architectural practice, yet its integration into architectural education remains fragmented and uneven. While recent advances have expanded the computational design landscape, architecture students often enter these environments with limited programming experience and without the conceptual scaffolds needed to navigate algorithmic reasoning. Existing curricula frequently emphasize tool proficiency or isolated software workflows rather than developing computational literacy that supports multi-objective design exploration and informed decision-making. At the same time, research rarely employs systematic qualitative methods or iterative curriculum development frameworks to understand how architecture students learn computation and how pedagogy can be shaped in response.

This study addresses these gaps through a three-term Design-Based Research (DBR) investigation, grounded in the learning science literature, conducted in a graduate-level visual programming course. The curriculum was iteratively designed, implemented, analyzed, and refined using empirical evidence from semi-structured interviews, classroom observations, and thematic analysis. Thematic analysis revealed six major cognitive and metacognitive challenges: difficulties with abstraction, a lack of prior programming experience, time constraints, debugging challenges, unclear alignment with career goals, and insufficient early exposure to computational tools. These challenges directly informed targeted revisions, including explicit conceptual instruction, progressive scaffolding through incomplete recipe exercises, expanded collaborative learning structures, and differentiated self-paced instructional videos.

The refined curriculum culminated in a structured three-module sequence—parametric modeling, performance simulation, and evolutionary design exploration—supported by lectures, recorded tutorials, guided practice, and student-led discussions. Results demonstrate that when computational pedagogy is grounded in cognitive evidence and connected to students' design contexts, learners develop stronger agency, improved problem-solving strategies, and a deeper understanding of computation as a design medium rather than a technical requirement. The study contributes a replicable DBR-based model for computational design pedagogy, offering transferable strategies for architecture programs seeking to cultivate computational literacy that meaningfully supports multi-disciplinary design decisions.

Together, architects and engineers develop solutions while navigating complex design problems, resource limitations, and social interactions. However, differences in their disciplinary goals and training can influence how they approach collaboration. Understanding how designers approach cooperative strategies when negotiating their own disciplinary goals is useful in identifying opportunities for better collaboration and recognizing gaps in their understanding of cross-disciplinary design. In response, this study uses a game theory approach to measure and compare cooperative behavior and strategies of architects and engineers when engaging in collaboration. Thirty participants from architecture and engineering, and at the experience level of student or professional, played an established game within game theory, the Prisoner’s Dilemma, and a new game, made for the study, that documented their focus on disciplinary design goals or cooperation outcomes. Participants played the games online over a video meeting platform with a pre-programmed computer opponent and after playing as their own discipline, they played as the other discipline. Between each game, they verbally reported their strategies to the researcher. Disciplinary strategies, perceptions, and scoring outcomes were compared using a Chi Square analysis, and content analysis was used to code their reported strategies. Disciplinary identity related to differences in score outcomes and level of experience influenced different reported strategies. The results of the study support the varied assumptions between the disciplines and suggest an exploratory approach to study architect and engineering cooperation through strategic interaction. This research contributes to the understanding of interdisciplinary collaboration strategies through the context of game theory, which has not previously been explored in architect-engineer teams.

Architecture education seeks to prepare students for a rapidly changing profession. How can curricula and courses be structured to help students thrive in an interdisciplinary field? This study addresses that question by examining the Design the Future podcast. Since its 2020 launch, hosts Lindsay Baker and Kira Gould have interviewed more than 100 leaders across built environment fields.

To understand how narratives are shaped, we are conducting an AI-assisted pilot analysis of interviews. Our analytical lens is Legitimation Code Theory (LCT), a sociological framework that builds on Pierre Bourdieu’s work to explain how individuals and their knowledge gain recognition. LCT includes three dimensions called Specialization, Semantics, and Autonomy.

Our project has three aims.

1. Apply Specialization to investigate leaders’ paths across built environment fields. Interviewees describe diverse trajectories through and between disciplines. For example, Angie Brooks speaks of “breaking down the silos… creating these horizontal links between people and between what you might normally think are disparate disciplines.” Specialization reveals patterns in how ideas move across domains.

2. Apply Semantics to examine how leaders frame and communicate complex concepts. Interviewees often use concrete examples to illuminate abstraction. For example, Eden Brukman uses the case of an office chair to explain circularity, noting that it can be cheaper to discard surplus furniture than return it to a manufacturer. Semantics clarifies how complex ideas are made accessible.

3. Apply Autonomy to analyze how the podcast links built environment leadership to broader cultural and professional influences. For example, Marta Schantz cites inspiration from political figures and fictional characters such as Leslie Knope, who combines civic commitment with personal connection. Autonomy explains how external ideas are integrated into a field.

By analyzing narratives, this study shows how forms of knowledge shape broader patterns in design education. LCT offers a structured approach for addressing change.