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.
Summer provides a natural opportunity to reflect and regroup for many educators. Within a museum, the time is often filled with camps, teacher workshops, and special public events, but time must still be set aside for planning. Over the next couple months, I will be transitioning to a new position at work as well as finishing my Master’s degree, so considering the future is particularly relevant at the moment. In order to continue to grow personally and professionally, my current learning goals include gaining experience in hobbyist programming, learning more about how non-profits are managed, and finding new ways to engage the public within a museum.
These goals are chosen based on the idea that I want to continue to do well in a museum environment, but may also wish to explore my own interests in another non-profit setting where much of my experience will transfer over. Of particular interest to me is how to engage a wide variety of ages in learning new technologies, including developing programming and computational thinking skills. I also want these goals to be achievable in the next year and have concrete end products that show evidence of growth.
During a recent session of our Art and Science Teacher Workshops, I engaged in action research by implementing and reflecting on a lesson on the use of computers for creative means, namely creating visual art. The participants explored the work of Sol LeWitt, who created instruction based works intended to be carried out in a variety of contexts. Brain Pickings has provided an overview that shows how various artists have approached this idea. LeWitt’s instructions can be implemented using traditional technology, but in this lesson I chose to use two newer tools, Scratch and Processing, to introduce how computers can be tools of creative expression through programming and play.
Grade level: K-12 Teachers
Common Core Math (for students – not standards for the workshop)
7.G.2 Draw (freehand, with ruler and protractor, and with technology) geometric shapes with given conditions. Focus on constructing triangles from three measures of angles or sides, noticing when the conditions determine a unique triangle, more than one triangle, or no triangle.
National Core Art Standards (for teachers/students)
CR.1.1.8 Generate ideas, goals, and solutions for original media artworks through application of focused creative processes, such as divergent thinking and experimenting.
CSTA Computer Science Standards (for teachers/students)
L1:6.CT.1 Understand and use the basic steps in algorithmic problem-solving (e.g., problem statement and exploration, examination of sample instances, design, implementation, and testing).
L1:6.CT.6 Understand connections between computer science and other fields.
A video produced to demonstrate differences in teaching approaches when presenting to large and small groups in a museum education setting.
Just over a year ago, I applied to Michigan State University (MSU) to begin the Masters of Arts in Education Technology (MAET) program. This process forced me to consider my goals not only for the degree but in my profession. I had spent the last three years coordinating an outreach program for northern Michigan schools that used an integrated approach to teaching art and science. I chose to attend MSU in large part because of its rich history in exploring transdisciplinary learning and its relationship to developing creativity skills in K-12 students, which closely matched what I was trying to achieve through our programs, so many of my goals related to further developing an understanding of these topics.
I recently interviewed fellow educators and software developers about what they thought computer science was. The results were rather interesting, as responses ranged from not being sure at all to focusing on programming and use of computers. The interviewees included:
- A second grade teacher
- An art educator
- A software developer
As you might expect, their responses varied quite widely. This demonstrates a challenge to the computer science field in communicating the nature of the discipline, although debate with the field exists on that very question.
Zweben, S. (2011). Computing degree and enrollment trends. Computing Research Association.
Since the 1990’s, the National Science Foundation has emphasized the need to improve science, technology, engineering, and mathematics (STEM) education and retain students within the STEM pipeline to propel them to related careers. This call to action is a result of an innovation-driven economy where an increasing number of careers will require STEM skills, but where the majority of students in the United States are not proficient in these fields and have fallen behind their peers on international assessments, resulting in employers who lack qualified applicants to fill STEM positions (National Research Council, 2011). Even after decades of efforts with billions of federal funds allocated to STEM programs each year, there still exists ambiguity over how to best teach STEM, including how closely to integrate the fields within instruction (Sanders, 2009).
— jkurleto (@jkurleto) December 8, 2014
Forty years ago, Donald Knuth argued that computer programming is both an art and a science, with the two aspects not at odds but complementary to each other. Writing a program “can be like composing poetry or music…programming can give us both intellectual and emotional satisfaction” (Knuth, 1974, p. 670). He perceived that it is not only the result of an algorithm that can demonstrate creativity, but the act of creating the algorithm as well. This is akin to recognizing that the techniques of a painter can be as creative as the painting itself, as the process and product are intrinsically linked. Creativity in programming has long been accepted in the computer science community, but not necessarily with the general public. One contributing factor is that the algorithms and code that implements them have often been obscured from the end user, or to borrow an art term, viewer.
A new museum exhibit, The Art of Algorithms, will pull back the curtain to reveal the spectrum of creativity used in creating and implementing algorithms and demonstrate applications of computational thinking in the arts. By participating in this interactive museum exhibit, visitors will not only be able to experience examples of digital art, but also create works to be displayed within the gallery. Museums play an important role in communities by not only elucidating difficult concepts but nurturing passions in different fields of study and showing connections across disciplines.
Playing is finding joy in open-ended exploration, without being concerned with a specific outcome. Play allows ideas to be reimagined through new representations, avoids following conventional ways of thought, and uses rules and limitations as means to creativity. Used in conjunction with other imaginative skills, it leads to the transformation of ideas, by altering modes of representation or finding connections across (and above) disciplines (Root-Bernstein & Root-Bernstein, 1999).
While I initially considered play as an underutilized skill in creating algorithms, I found that it can be one of the most useful ways to be creative in problem solving, such as with my proposed activity that uses playing with a simple programming tool to introduce algorithms to elementary and middle school students. While it uses open inquiry to allow the students to freely explore how instructions are constructed, I kept some constraints and broad goals in place to promote deep or hard play. The only way to construct the algorithm was through the blocks available in Scratch, and with each of the challenges, students were given the freedom to explore but needed to apply what they learned towards increasingly complex goals.