Relevance for Complex Systems Knowledge
The problems we face in the world are complex and require the integration of multiple disciplines, concepts, and skills to solve them. In addition, meaningful learning can occur when learners make connections between prior knowledge and new experiences and skills within real-world contexts.
Drake (1991, 1998) described curriculum integration through multidisciplinary, interdisciplinary, and transdisciplinary approaches while making it clear that one position is not superior to another; instead, different approaches are more appropriate than others according to the context in which they are used.
The addition of engineering standards into the NGSS and state standards has led to a renewed focus on integration because engaging students in engineering design requires an interdisciplinary approach that incorporates knowledge from science, math, and technology (EDC, Engineering Design Challenge). Thus, engineering is broadly described through the eight science and engineering practices, as well as three disciplinary core ideas: (i) defining and delimiting an engineering problem, (ii) developing possible solutions, and (iii) optimizing design solutions. It is important to note that it is not the number of disciplines being integrated that reflects the degree of integration in a STEM curriculum. Rather, it is the connections of the relevant disciplines to the real-world problem and the connections between the disciplines that are important.
Given that integrated STEM curricular units aim to engage students in problem-based learning through engineering design tasks, which, in turn, facilitates students’ learning of STEM concepts, and their application to solving real-world problems, curricular coherence is an important consideration in determining the quality of integrated STEM curriculum.
It is also noteworthy that throughout the integrated STEM literature, science is often treated as a singular discipline without consideration of distinct subdisciplines such as physics, chemistry, and biology. Several researchers argue that integrating engineering into physical science is relatively easy, as physics concepts are readily applicable to many mechanical, electrical, and civil engineering contexts. In contrast, life science concepts are abstract and design activities in life science classes often require the use of technologies that are not commonly found in K–12 classrooms; thus, engineering lessons within the life and Earth sciences are less common.
This paper analyzed 50 STEM projects by generating a Conceptual Flow Graphic for each curriculum. The CFG includes the main concept(s) addressed within each lesson, arranged chronologically, and connected by arrows that represent the strength of the connections among the concepts and the main learning goal. After data analysis they defined four types of STEM curricula:
1) Coherent science unit with a loosely connected EDC: While there is an EDC introduced at the beginning of the unit, the engineering design is essentially a culminating project added to the end of an existing science unit, and the science content in the unit is not needed to propose possible design solutions.
2) Engineering design-focused unit with limited connections to science content: The majority of the lessons are focused on engineering content, and the coherence of the storyline is developed through students engaging in a series of engineering lessons aligned with the EDP. Science-focused lessons were interspersed throughout the units, but rarely did they provide conceptual or contextual links to inform design decisions.
3) Engineering design unit with science as context: The curricular type also included STEM units that used EDP as the structure or storyline for the unit. However, science-focused lessons were only used to provide contextual background to the ED.
4) Integrated and coherent STEM curriculum: This curricular type also included STEM units that used the EDP as the structure or storyline for the unit. However, all or almost all science-focused lessons were conceptually linked to the EDC, providing important scientific knowledge and data needed to make decisions.
Apart from that, there are two types of integration between science and engineering:
1) Conceptual: Science concepts learned were relevant and necessary to developing solutions to de EDC.
2) Contextual: the use of a client to contextualize the learning of science content and, on the other hand, the use of science content to better understand the EDC and provide a more detailed contextualization of the problem.
In the case of mathematics, the issue is that it is usually taken as a tool to analyze data in the service of science or engineering. Successful mathematics integration requires that mathematics concepts are foregrounded with explicit learning outcomes and this is better done by using multidisciplinary approaches more than transdisciplinary.
