The “T” in STEM: Moving from Stuff to Skills in the Learning Ecosystem

Among many other things, the term “STEM” brings to mind requisite skills such as critical thinking, making connections to the real world, and competency in interfacing with technology. Recent months have put into stark relief the nature of problems in our world, as well as the role of digital technology in helping us to navigate these challenges. In a sudden and unexpected way, all of our students became virtual learners and all of our educators became virtual teachers. It may be the case that STEM-focused schools were better prepared for the COVID-19 pandemic, but it is certainly the case that all of us will now be better prepared if and when the next wave of disruption crests. However, a more pressing question is the extent to which our children will be prepared for a world that poses complex problems with very real consequences.

However, a more pressing question is the extent to which our children will be prepared for a world that poses complex problems with very real consequences.

One of the major challenges facing our schools in preparing our children for their futures is the gap in available courses, curricula, and common practices associated with two major elements of STEM: technology and engineering. A part of the problem in our approach to technology as a STEM discipline has been the focus on hardware, software, and “stuff” in defining technology integration in schools and systems. While tremendous progress has been made in integrating educational technology into schools, the problem still remains that we are not completely sure how to integrate technology, as a core discipline, into our programs of study. This is a complex problem with many systemic factors contributing to our lack of technology learning opportunities for students, including a need for comprehensive computer science pathways, but teacher perceptions of preparedness and comfort with teaching technology concepts is at the core. (For example, Horizon Research [2019] Highlights From the 2018 NSSME+.)

A part of the problem in our approach to technology as a STEM discipline has been the focus on hardware, software, and “stuff” in defining technology integration in schools and systems.

An important solution to the relative lack of disciplinarity of engineering in K–12 schools, especially at elementary levels, has been the introduction of the Engineering Design Process (EDP). The implementation of Design Thinking in schools has provided a paradigm for integrating engineering concepts, and this has been fueled by the inclusion of the Science and Engineering Practices in the Next Generation Science Standards®. Whereas engineering was once the bugaboo of many a classroom STEM teacher, Design Thinking now forms the basis for many project-based learning experiences that represent a core foundation for STEM integration in schools. The transition may not be happening quickly enough for advocates of K–12 standards for engineering, but we have seen promising progress across the nation. A similar progression is inevitable for technology, as well.

One imperative for future readiness is fluency in developing and improving solutions, which is the fundamental problem at the heart of technology as a discipline. We also have the immediate need to ensure that all stakeholders in the educational community are comfortable with and proficient in relating to machines. What has perhaps been lacking until relatively recently is a sufficiently “sticky” mental model to get us going in the same way that the EDP has moved K–12 engineering education forward, nor have we had this sort of societal imperative as a driving force behind the cause. Computational Thinking represents just the sort of process-oriented framework to support a low-threat entry point for teachers across grade levels and content areas.

The goal of this brief article is not to define computational thinking (there are some links here that will do a better job of that) but to advocate for some consistency in defining essential skills in technology education. For the past several years, Cognia has worked with hundreds of schools and systems in strengthening STEM implementation. One of the enduring challenges has been to determine just how STEM-focused schools should go about the work of promoting the development of, and tracking growth in, skill areas outside of those learning objectives that form the basis of standardized accountability tests. Within the ecosystem defined in Cognia’s STEM Certification Standards, we measure readiness through the lens of STEM literacy, a composite of content knowledge, discipline-specific skills, and cross-cutting competencies. We have found that schools overwhelmingly lack measures of content knowledge acquisition and student skill development in technology. Using computational thinking as a framework can help school leaders identify the curricular, instructional, and assessment development needs required to support technology skill development for all learners.

To be clear, integrating computational thinking does not supplant the need to address computer science for STEM students. Many leaders and educators may not be aware of the benefits offered by the K–12 Computer Science Framework. The Framework is an excellent resource for computer science education and the integration of computer science into all schools. The challenge associated with this approach is that it allows policy makers, state departments, and local education agencies to relegate technology education to the special areas most often associated with elective and career technical education (CTE) courses. As an aside, we should be engaging students in CTE courses and pathways at a much higher rate, but we also need to ensure that technology as a discipline is the norm in our schools. This means that all teachers in STEM-focused schools should have the development, support, and opportunity to integrate technology skills into the curriculum, whether this happens in collaboration with other department teachers or just in their own classrooms. The processes, skills, and habits of mind embedded in the computational thinking model are good places to start.

So, what can you do right now as a first step toward integrating computational thinking? Here are a few suggestions:

• Read a digestible article on the subject (I like this one)
• Watch a video
• Enroll in a course (this is just one cost-efficient option)

You can learn more about Cognia STEM Certification at Cognia.org or reach Scott Davidson via email at scott.davidson@cognia.org.

Scott Davidson is Senior Director, Improvement Services at Cognia. In this leadership role, Davidson supports the Cognia Learning Community. In previous roles at Cognia, he has served as content developer and program manager. Davidson has had the unique opportunity to work with leaders, educators, and students representing diverse schools and systems across the Cognia network. He has also led and supported review teams for schools, systems, and organizations around the world. Davidson has undergraduate degrees in history and secondary education, as well as graduate degrees in adolescent literacy and teacher education. In addition to working as a classroom teacher and building-level administrator, he has also worked as a content specialist and program manager for school improvement projects across the U.S. His current professional interests include professional learning in virtual environments and innovative instructional designs (e.g., STEM, CBE).