Given the increased demand for inter- and trans-disciplinary thinking, special attention needs to be given to the means by which these 21st century skills are taught. To develop broad social and scientific thinking skills, students need to engage in a range of investigations in real-world situations. A major component of learning about research practices reform has been the promotion of authentic research experiences in coursework, such as the studio workshop described above. In the NRT workshops and courses, we will help trainees to develop habits of mind that involve theory building, developing and supporting explanations, and using discipline-specific means of representing and communicating phenomena. Below we describe our theories of learning and practice.
Learning Theory. Sociocultural theory suggests that learning is mediated by the tools and products of a system of where learners interact [Palincsar, 1998; Bransford et al., 2000]. The tools and outcomes we will develop will integrate social and scientific concepts in embedded professional research practices. As learners engage in these practices, we will combine observations, among groups of students, across places, and time, which will form the basis for constructing and revising models.
Model-centered learning. In the NRT, models will function as a boundary object [Star and Griesemer, 1989]. Boundary objects are resources available to learners that provide a means to bridge ideas across disciplines. To improve learning with boundary objects, collaboration is often necessary [Akkerman and Bakker, 2011]. Throughout the courses identified in the previous section, trainees will engage in model-centered and collaborative learning. Models provide opportunities for learners to make their ideas visible and open for discussion, negotiation, revision and extension, and in supporting constructive discourse, which is associated with positive learning outcomes [Greeno, 1998; Chi et al., 2001]. Models also allow cognition to be distributed by mentally offloading parts of difficult tasks into the physical environment (e.g., computer screens and notebooks), where thinking can be organized and discussed. Furthermore, because models often include a small number of semantic representations, individuals coming from different backgrounds, once familiar with model semantics, can communicate in a similar workspace. Thus individuals and stakeholders representing different disciplines are given a common digital or in person space for discourse, which provides opportunities for learners to develop agency or capacity to act in the authentic investigations that are personally meaningful [Engle and Conant, 2002].
Modeling as a professional tool for collaboration and communication.The development of a shared conceptual model of the environmental issue [Voinov and Bousquet, 2010] is essential to community learning, problem-solving, and environmental decision-making. Vionov and Bosquet  outline two major goals that can drive shared or participatory scientific modeling: (1) learning, as outlined in the previous paragraphs [Campo et al., 2010; Lynam et al., 2010; Souchère et al., 2010]; and (2) the identification and clarification of the impacts of solutions to a given problem, usually related to supporting decision-making, policy, regulation or management [Anselme et al., 2010; Lagabrielle et al., 2010; Simon and Etienne, 2010].
Starting at the introductory workshop, trainees will use a low-overhead, intuitive online modeling interface that supports the development of dynamic conceptual models based on a Fuzzy-Logic Cognitive Map (FCM) format. A FCM is a cognitive map, much like a concept map, in which the relations between the elements can be used to compute the “strength of impact” of these elements. These models have been called simplified mathematical models of belief systems [Wei et al., 2008] and have been used to represent both individual [Axelrod, 1976] and group [Özesmi and Özesmi, 2004; Gray et al., 2012] knowledge systems. As they develop inter- and transdisciplinary knowledge, trainees will be asked to develop collective representations of the perceived salient components and causal relationships involved in coastal resilience dynamics. Subsequent coursework will provide opportunities to iteratively improve their conceptual models [Özesmi and Özesmi, 2004] and engage critically in professional practices that include participatory stakeholder modeling, scenario analyses, and joint fact-finding.
Modeling practices will culminate in the studio course and the capstone workshop, where the conceptual modeling will be linked to application-specific tools and data in a decision-support context. There trainees will learn how to use participatory modeling to generate collaborative discourse, foster teamwork, and reduce conflict. Models will form a central piece of the student portfolio. In addition, the studio course will enable trainees to experience project and personnel management and resolution of ethical issues. Other non-technical skills will include outreach and teaching, which is explained in other sections.