From Making to Computing: A Year of Growth

Essays, MSU MAET

Before beginning the Masters of Arts in Educational Technology (MAET) program at Michigan State University (MSU), I had a sense of what my interests in informal education were, but little idea on how to move forward. I had spent over five years as a museum outreach educator, but felt my mental wheels spinning a bit as I tried to break out of familiar ways of thinking. After spending just over a year working on my masters degree, the path has become clearer, not just due to guidance from my instructors, but by taking inspiration from the amazing work that my fellow classmates have exposed me to. My attitudes towards the use of technology in the museum or classroom has also changed by taking a more grounded view in connecting the use of tools to pedagogy and content being taught. As I reflect on my experience, I find that the largest changes in how I work to provide compelling experiences to learners of all ages has taken place in three key areas: maker education, transdisciplinary learning, and computational thinking.

Maker Education and Constructionism

I’ve had an interest in using maker resources to guide my interests in electronics, programming, and physical computing ever since I had an opportunity to present at the first Detroit Maker Faire. Given the sometimes specialized knowledge needed to use some of the emerging tools and the emphasis of standardized testing over innovation in classrooms, I didn’t believe there was much interest in taking the maker mindset into schools through outreach programs or including the topic in teacher workshops. Two experiences changed my thinking last year: learning about Maker Education approaches that some schools have taken at Maker Con in San Francisco, and even more meaningfully, preparing and presenting our own Maker Faire as part of the East Lansing cohort during my first semester in the MAET program.

Rather than taking an instrumental view of using maker technology in the classroom, the Adapting Innovative Technologies in Education (CEP 811) course allowed us to find ways to use these tools to allow students to have meaningful experiences. Even as we became familiar with Raspberry Pis, littleBits, conductive thread and ink, and Makey Makeys, we had to consider how students could use them within existing curriculum, such as using copper tape and conductive thread to explore simple circuit building with lower elementary students. Many of these tools have been integrated into my museum programs in the past year. Even more importantly, we considered the attitudinal changes towards learning that students can undergo when there is not step-by-step instructions or a clear end goal in mind but allowing them to develop their own ideas, a far cry from what many schools permit today.

Preparing for our mini-Maker Faire allowed me to collaborate with classroom teachers, an opportunity that I do not often have working within a museum. I found that many values found in Maker Ed are held by teachers as well, leading to increasing inclusion of making not just in extra-curricular activities, but within lessons as well. My group chose to work on a hackable Scratch game that would allow novice programmers to learn how to use the software by modifying the game by altering the code and adding their own components to the pinball table. Sharing it with visitors was an invaluable experience that showed how important it was to share our work with others, explain your approach, receive feedback, and generally celebrate student efforts as part of the learning process. In this past summer of Art and Science Teacher Workshops, we spent considerable time discussing having students curate their work, which was directly inspired by this Maker Faire experience, and many of our teacher participants included this approach in their reflective project.

Another takeaway from this course as well as Learning in School and Other Settings (CEP 800) was the educational theory that supported using Maker Ed in schools. Although we began with basic comparisons of behaviorist and constructivist approaches, the use of TPACK to consider the tension between content, pedagogy, and technology knowledge helped place some of these tools in context as to how they would be appropriate in presenting a wide range of topics using a constructivist approach. To extend this even further, we read a chapter from Invent to Learn, which introduced me to constructionism. Seymour Papert’s extension of constructivism has been a large influence in not only my studies but in lesson design. By guiding learners to create meaningful artifacts of their learning, this not only allows learning and thinking to become visible, but changes how they learn by providing an authentic context for gaining and applying understandings. My programs this past year has used constructionism as the basis for my teaching approaches, such as guiding students in developing smart objects with Arduinos in my museum’s Sparking Innovation program. I also now spend half a day exploring the maker mindset and the importance of tinkering with K-12 teachers workshops held at the museum.

Transdisciplinary Thinking for Creativity and Innovation

The long history of transdisciplinary thinking in education at Michigan State, including Robert Root-Bernstein and the Deep Play Group, was one of my primary reasons for choosing the MAET program. Throughout my coursework,  I developed a better working knowledge in developing creativity and innovation skills within students. This has changed how I view the intent of museum programs, by not focusing solely on content knowledge, but also developing cognitive skills applicable in many fields. Many of my programs in the past few years have focused on integrating art and science, which I now see as ultimately recognizing that both fields require creativity and inquiry, and now work on developing those skills in students.

In Applying Educational Technology to Issues of Practice (CEP 812), I joined members of my cohort in tackling a wicked problem by considering ways to address lack of innovation in schools. The intractable nature of this problem meant we struggled with effective ways to work around constraints, including the current emphasis on high-stakes testing. The most helpful understanding that would aid in tackling this problem was the work of Amabile (1996), which I adapted in creating a representation of the relationship between creativity and innovation within a school setting, as seen below.

This diagram allowed me to consider what I as an educator could do to support and develop both the individual’s creativity skills and provide a framework that would allow innovation to occur. While the focus in the school setting may be developing domain specific knowledge, I realized that creativity skills and motivation are often ignored. As my teaching began to use more of an inquiry based approach, I increasingly allowed students to have the freedom to explore their own ideas, resulting in increased motivation and developing original thoughts. I also realized that even with best teacher practices in promoting innovation, such as stressing the need for students with different strengths to work together in tackling large problems, that without a culture of trying out new approaches and treating failure as a necessary part of the process, students would find find it difficult to take the risks needed to innovate. A recent program I co-developed on using 3D printing to aid in the engineering process included walking students through the iterative nature of the development process, which includes recognizing failure part of the process. Although I did not take coursework in design thinking, I communicate one of the core tenets put forth by IDEO to students now: “Fail faster”. By getting past approaches that are dead ends more quickly, students can discover ideas that work, which is important for those who are still working on developing patience and grit.

Prior to entering the MAET program, I had read Sparks of Genius in an attempt to define creative thinking tools within a program that covered understandings of light and color in art and science called Reflect on This. I thought the book written by Robert and Michele Root-Bernstein (2009) was a good starting point for identifying aspects of the creative process, so I appreciated the opportunity to delve into deeper as part of a course on Creativity in Teaching and Learning (CEP 818). Using the transdisciplinary habits of mind identified by Mishra, Koehler, and Henriksen (2011), I was able to explore a topic of particular interest to me when considering creativity at the convergence of art, science, and technology: algorithmic art, sometimes included under the broad category of New Media. As I applied skills such as perceiving, patterning, abstracting, embodied thinking, modeling, play, and synthesizing to consider different aspects of algorithms in our daily lives and in education, several skills were important enough that I’ve begun to include in our programs. Abstraction plays an important role in any problem solving process by allowing students to focus on relevant information, such as when I introduced TinkerCAD to students across Michigan and challenged them to create a model of a real world object.. Deep play can be immensely useful when trying to find new geometric patterns that can be created through Scratch, as I recently utilized when teaching a summer camp.

I now use these terms when working with students in creating art projects, performing science experiments, or programming computers. This experience allows me to use a common vocabulary for creativity skills that the Root-Bernsteins thought was necessary in order to truly reach a multidisciplinary approach to education. I was also able to extend my work in a later course on Technology and Leadership (CEP 815) by creating a manifesto on computing and creativity with a host of resources that will guide my direction upon graduation in creating public programs on creating using computers.

Computational Thinking

The primary focus of my studies within the MAET program has been in computational thinking (CT) within both a Computational Thinking course (CEP 891)  in an Independent Study (CEP 890). Papert used the term computational thinking in his seminal Mindstorms (1980), but came into common use again due to an article by Jeanette Wing (2006) that argued that CT skills were becoming increasingly vital for all students. Part of my interest in the topic is that a comprehensive definition of CT is still being debated, but I’ve used a working definition of problem solving through computation, whether by humans, computers, or increasingly a combination of the two. Several generally agreed upon CT skills include abstracting, algorithmic thinking, problem decomposition, and data representation (Barr & Stephenson, 2011). These are seen as core skills used in computer science but are applicable to many fields, such as the importance of computational biology today.

My exposure to CT has changed how I teach computer programming, such as in the aforementioned Sparking Innovation program or in introducing Scratch in teacher workshops. I no longer take an instrumental view, since teaching students to code is akin to teaching them to using a microscope; useful, but only in context of how these tools help us approach tasks that would otherwise be difficult or impossible to accomplish. I now introduce it as problem solving, and start to consider general, abstract solutions before working with code; look for patterns that can allow the creation or use of algorithms; work with students to break problems down into manageable chunks; and work on debugging skills that allow for solutions to be refined.

I also have begun to look for ways to include CT across the curriculum, particularly in the arts. As part of the initial course in CT, I contributed two lessons on using these skills in teaching art: creating and modifying Drawbots and abstracting kinetic art using PencilCode, the former of which I’ve adapted for use both in teacher workshops and programs with a K-8 audience. I’ve also taken inspiration from the works of Sol LeWitt in order to investigate how computation by humans and computers can result in works of art that have similarities and differences, which was also presented in teacher workshops. This fall, I plan to offer programs that allow the general public to find way to develop both CT and artistic skills through a series of community education programs, and much of this effort has been aided by my work through MAET.

My independent study in CT as it relates to using embedded devices such as the Arduino Uno and Raspberry Pi provided an opportunity to combine these thinking skills with tools that I have a particular interest in finding uses for within a classroom. My particular focus was on utilizing a new generation of cheap, low-power, network connected devices, exemplified by devices such as the Particle. During my course of reviewing research, developing lesson plans, and reflecting on my learning, I realized that I was falling into my old ways of tool-first thinking. Embedded devices have enjoyed a long history in education but have not made any appreciable impact beyond LEGO Mindstorms or the Hummingbird more recently. Late in my independent study, I shifted thinking to considering not the tool being used, but how they can aid in allowing students to not just utilize technology in STEM programs, but create technology for that use. By utilizing engineering practices, students can create the tools used in science and math investigations and well as creating interactive art installations.


Creating Maze Games in Scratch


Programming an Arduino


Algorithmic Thinking

I’m excited to continue to explore CT in future school and public programs since I view these cognitive skills as allowing learners to become effective producers of original works, not just consumers of information, when using computers. This summer, I was able to arrange a CT Camp for Flint sixth graders, which I view as the culmination of my studies in this field. We explored creating digital art and electronic music, making 3D prints, inventing new products, and designing our dream games, all by using a combination of human and computer problems solving. As we prepare students for jobs that are not even created yet, I believe those that can augment their effective intelligence with the help of computing devices will have an advantage over those who can not.

Looking Forward

While I’m passionate about continuing to apply these understandings in new ways, I realize that my interests and work responsibilities will continue to evolve. There were topics I did not have a chance to explore, such as design thinking, game design, and hybrid learning. Yet the greatest change to my professional life that the MAET program provided is that it allowed me to consider myself a leader in considering the role technology can play in learning, so that I know that any topic that I wish to pursue can be considered using the same considerations of content, pedagogy, and technology in synergy to transform learning. While I am unsure if my future lies in museum education, technology integration, or perhaps even creating new software tools for use in education, I feel inspired to continue to learn from the vast network of educators I’ve grown to know.


Amabile, T. M. (1996). Creativity and innovation in organizations (Vol. 5). Boston: Harvard Business School.

Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community?. ACM Inroads, 2(1), 48-54.

Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books, Inc..

Root-Bernstein, R., & Root-Bernstein, M. (1999). Sparks of genius. Boston and New York: Houghton Mifflin.

Wing, J. M. (2006). Computational thinking. Communications of the ACM,49(3), 33-35.

Leave a Reply

Your email address will not be published. Required fields are marked *