Examining design cognition coding schemes for P-12 engineering/technology education

Cultivating students’ design abilities can be highly beneficial for the learning of science, technology, engineering, and mathematics (STEM) concepts, and development of higher-order thinking capabilities (National Academy of Engineering and National Research Council in STEM integration in k-12 education: status, prospects, and an agenda for research, The National Academies Press, Washington, 2014). Therefore, examining students’ strategies, how they distribute their cognitive effort, and confront STEM concepts during design experiences, can help educators identify effective and developmentally appropriate methods for teaching and scaffolding design activities for students (National Research Council in standards for k-12 engineering education? The National Academies Press, Washington, 2010). Yet, educational researchers have only recently begun examining students’ engineering design cognition at the P-12 level, despite reports such as Standards for K-12 Engineering Education? (National Research Council 2010) designating this area of research as lackluster. Of the recent studies that have investigated engineering design cognition at the P-12 level, the primary method of investigation has been verbal protocol analysis using a think-aloud method (Grubbs in further characterization of high school pre- and non-engineering students’ cognitive activity during engineering design, 2016). This methodology captures participants’ verbalization of their thought process as they solve a design challenge. Analysis is typically conducted by applying a pre-determined coding scheme, or one that emerges, to determine the distribution of a group’s or an individual’s cognition. Consequently, researchers have employed a variety of coding schemes to examine and describe students’ design cognition. Given the steady increase of explorations into connections between P-12 engineering design cognition and development of student cognitive competencies, it becomes increasingly important to understand and choose the most appropriate coding schemes available, as each has its own intent and characteristics. Therefore, this article presents an examination of recent P-12 design cognition coding schemes with the purpose of providing a background for selecting and applying a scheme for a specific outcome, which can better enable the synthesis and comparison of findings across studies. Ultimately, the aim is to aid others in choosing an appropriate coding scheme, with cognizance of research analysis intent and characteristics of research design, while improving the intentional scaffolding and support of design challenges.