Computational Thinking,
The Humanities, and Gender
Can integrating computational thinking into the humanities close the technology gender gap?
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| “Sphero” by M. Norwood |
Alone in my classroom, I stared at the clear, round robot glowing bright blue on my desk. The Sphero, a robotic tool that can be used to teach programming, was donated to my classroom, much to my excitement. After a few hours of plugging away at the programming options on the Sphero Edu App, I managed to manipulate the robot using the draw, blocks, and javascript programming options. It’s not difficult, it’s just a path of learning that I was not as interested in pursuing until recently. Before I start to congratulate myself on my work with the Sphero, I realize I am a technology statistic. Nationwide, there is a lack of women in Science, Technology Engineering and Mathematics (STEM) careers. My current career choice as that of a Social Studies teacher seeks to broaden my students understanding of the human experience, but am I missing something by not incorporating technology? My course materials are created, shared, and graded via Google Apps for Education. My use of, and instruction around technology though is not necessarily through a computational approach, instead, my inclusion of technology utilizes apps and tools to support my students in expressing their positions on topics and exploring the human experience. My use of technology is not purposely tied to any one particular gender. What role does a humanities teacher have in supporting all learners in the development of 21st Century skills, including computational thinking? If we fail to integrate computational thinking across disciplines are we missing a larger portion of the population that could potentially gain the skills needed to later work in the technology sector? Is the lack of women in STEM a symptom of a lack of perceived variety of computational thinking, with women being the identifying marker? Integrating computational thinking in the humanities is way educators can support the development of 21st Century skills for all learners, potentially lessening the STEM gender gap.
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| "Girls learn science" by Idaho National Laboratory is licensed under CC BY 2.0 |
What is computational thinking and how could it apply to the humanities?
Computational thinking is the logical thought process we use to design a program to manipulate computers. Computational thinking is the underpinning of computer science that makes all technology use possible. Ironically, the use of many much of technology consumed depend on computational thinking to function but not to operate. This leaves users with potentially lagging computational skills. “Thinking like a computer scientist means more than being able to program a computer. It requires thinking at multiple levels of abstraction…” (Wing, 2006, p 34). Encouraging users to understand the processes that allow for their apps and devices to function alone is a reason to include it in K-12 education.
The term computational thinking was coined by Jeannette Wing in her 2006 article “Computational Thinking”. In it, she claims “computational thinking is a fundamental skill for everyone, not just for computer scientists. To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability.” (Wing, 2006, p 33). In education, we spend much of our time thinking of content, and Jeannette Wing, echoed many social and educational researchers past and present, by arguing that teaching logic is equally as important as the other subjects taught in schools. “Computational thinking is a way humans solve problems; it is not trying to get humans to think like computers. Computers are dull and boring; humans are clever and imaginative. “ (Wing, 2006, p 35). In short, computational thinking is a logical thought process that can be utilized for computer programming. The computer programs that are designed, however, are only limited by human imagination. Although computer science, not a relatively new concept, educators have been slow to adapt it to their curriculums across disciplines, such as the humanities.
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| "Riptide Went to ISTE without ME!" by F Delventhal is licensed under CC BY 2.0 |
Computational thinking is one of the many 21st century skills educators should find ways to bring into their classroom. Educators seeking to integrate 21st Century Skills might decide to consult the ISTE Student Standards, with computational thinking listed as one of the standards. Should teachers seeking to integrate technology have to do it alone? No. But by working in teams there is no reason that they cannot find ways to blend traditional humanities content and computational thinking. Stop lecturing about the centennial anniversary of World War I (WWI) and let students discover how the numbers can tell the story. Maybe students could design an education app. A possible way to integrate computational thinking and humanities is to create experiences that support the exploration of content and the learning of programming for a purpose. Teachers should always be cognizant of WHY they are doing what they are doing. This point is illustrated wonderfully in Invent to Learn, “It’s not the technology that engages or empowers, it’s the outcome of students (or anyone) doing meaningful work. Meaningful to themselves and to the community they are in. “ (Martinez & Stager, 2013).
In Revisiting the media generation: Youth media use and computational literacy instruction Jenson and Droumeva explore the myth that students of the 21st century are digital natives intuitively learning computational thinking skills through their technology use. Their study was conducted at a school in Toronto, Canada with roughly sixty sixth graders. They selected to work with sixth graders because that is the age frequently cited for when the gender gap emerges in STEM. By sixth grade, students are already decided what types of courses to select in high school, college majors. It is at this age, according to Jenson and Droumeva, that a disproportionate amount of females opt NOT to go into STEM-related fields.
Jenson and Droumeva’s study introduced students to a roughly week-long exploration of computation thinking through the program Game Maker Studio. Students were introduced to the concepts of computational thinking. They engaged students through the Game Maker studio because they wanted student buy-in. Many researchers suggest engaging elementary students with computational thinking through the use of games. “One primary argument for introducing game design and development as part of STEM curriculum planning concerns the need to introduce and familiarize youth from an earlier age to the principles of computation, design thinking, and procedural logic.”(Jenson & Droumeva, 2017, P 214) Perhaps game design could be a way for some humanities teachers to integrate computational thinking into their curriculum. Following their study, Jenson and Dourmeva developed three important conclusions to consider for integrating computational thinking into classrooms. The first conclusion that it is a myth and misnomer to label a generation “digital natives. (Jenson & Droumeva, 2017, p. 222). There was no statistical data to support the notion that exposure to different devices increased a student's computational thinking ability. (Jenson & Droumeva, 2017, p. 222). As early as middle school, there is a gender gap emerging in the tech fields, with girls frequently reporting they are less comfortable pursuing computer science tasks and even less likely to be willing to participate in a public display of skills. (Jenson & Droumeva, 2017, p. 222)
Although in 2018 it is generally accepted that students are exposed to technology at an early age, but not to the underpinning procedural knowledge of what makes that technology work. Jenson & Droumeva also found in their study that students who report frequent gameplay do not score higher on computational thinking assessments (Jenson & Droumeva, 2017, p 221). Although students with an interest in gameplay might be more apt to continue studying computer sciences and use computational thinking, playing games do not necessarily improve an individual's aptitude for computational thinking. Therefore, to label someone a digital native because of their age and exposure is inaccurate at best because much of the digital media consumed and utilized does not require computational thinking skills.
The last conclusion and perhaps the most startling is that by sixth grade there is a distinctive gender gap in STEM. Jenson and Droumeva noted in their study that girls were more likely to complete tasks Jenson & Droumeva, 2017, p 221-222). Does this gender gap emerge because of the types of environments girls are exposed to computational thinking in? A computer science or math course can be very abstract and feel isolating. Perhaps finding ways to integrate computational thinking skills earlier and through humanities courses could provide a variety of opportunities for all learners to feel safe exploring and learning computational skills.
In the article Computational Thinking K-12, Grover and Pea review the varying interpretations of computational thinking and how considerations for its inclusion has grown since the days of Seymour Papert’s study of students using CT with LOGO programming (Grover and Pea, 2013, 40) Grover and Pea examine several definitions of computational thinking and present the following as a more concise version rom the Royal Society, ”Computational thinking is the process of recognizing aspects of computation in the world that surrounds us, and applying tools and techniques from Computer Science to understand and reason about both natural and artificial systems and processes” (Grover and Pea, 2013, p 39 ) The definition they provided allows for a looser interpretation of CT and consideration of its possible integration in other disciplines. Educators seeking to integrate computational thinking into non-traditional stem courses, i.e. the humanities, can work within the boundaries of this definition.
Grover and Pea also highlight the growing gender gap in STEM citing the US Bureau of Labor and Statistics data that there is an underrepresentation of women in STEM related fields. Their suggestion is to consider potential changes to the way that schools plan and integrate CT K-12 to broaden access and encourage more females to participate in computational thinking formally and informal. They suggest using tools that “combine traditional arts and crafts such as sewing and sketching with computation and electronic” with the likes of the Lilypad Arduino. (Grover and Pea, 2013, p 41) Another app they suggest including is the MIT App Inventor which is deemed more “gender neutral” and lends itself to more creative inclusion. (Grover and Pea, 2013, p 41). The larger takeaway from this article is that computational thinking is an evolving field of study, and that educators should work to be aware of and find gender inclusive ways to integrate into their curriculums.
Creating a Framework for Computational Thinking in the Humanities
There are numerous reasons why schools might seek to find ways to integrate computational thinking across disciplines k-12. Educators seeking to consider ways to integrate computational thinking into the humanities should consider the standards and skills they are teaching and assessing in their courses and use backward planning to find ways to authentically integrate computational thinking skills and tasks into their courses.
For many American humanities teachers, this means reflecting on the standards and skill that are taught in their curriculums. Although state standards vary, the Common Core State Standards Initiative is a reasonable place to start. Through backward planning, teachers can find areas of their curriculum that could be supported through computational thinking skills. Another avenue for meaningful integration in the humanities would be for technology and humanities teachers to collaborate on in-depth projects. Bringing computational thinking into the classroom that is traditionally “low-tech” teachers are bringing a new skill set to their students.
Suggestions for Integrating Computational Thinking
In my research, I found that successful technology integration relied on the “low floor, high ceiling” approach. (Grover and Pea, 2013, p 40). This means that teachers should select tools that are readily accessible to all learners. The tools are intuitive, instructions are clear and easily understood and the user can begin engaging in the technology quickly. The “high ceiling” aspect must also apply to the technology, meaning that there is the potential for the learner to increase the complexity of their skills using the same features.
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| "Learning about programming" by Kevin Jarrett is licensed under CC BY 2.0 |
One suggestion is to start engaging students with computational thinking skills at a young age through computerless tasks. One such site that offers instructions on how to do so is CS Unplugged. This resource is geared for learners age 5-12. Data, algorithms, procedures, intractability, and more are taught through physical printouts, cards, string, crayons, and graphs. More importantly, CS Unplugged is team oriented presented as a game. One strategy for integrating computational thinking and encouraging more girls to pursue STEM is to introduce them to the concepts at an earlier age.
High Tech/ High Engagement: Bringing Gaming into the Humanities
Another solution suggested by Grover and Pea was to make computational thinking fun and engaging through the use of games. From an early age, students engage in games through a variety of devices and platforms but seldom are required to consider how they operate. Why not teach computational thinking through a classroom app that integrates all class content as a game? One such option is Classcraft, Engagement Management System for K-12 Educators. This app is customizable and linked with Google Classroom.
Another game app that could support humanities integration would be Game Maker Studio. This app focuses more on computational thinking and design. It would be an awesome adaptation of the traditional book report for Language Arts, or perhaps to reconstruct the biography of a historical figure in Social Studies. Several authors, including Grover and Pea, emphasized the importance of bringing authentic, context-driven opportunities into the classroom to teach computational thinking and increase engagement of all genders.
Lastly, the MIT App Inventor was cited by Grover and Pea as another authentic, content-driven way to inspire more female students to engage in computational thinking. The design of an app would give students the power to create a platform to share their learning with a broad audience in a meaningful way.
Conclusion
Although computational thinking lends itself most easily to STEM-related courses, teaching it in isolation does a disservice to all students. Computational thinking is a 21st Century Skill that drives our economy. When designing a curriculum, it is important to think about how to incorporate computer science with equity, meaning that we design all courses to teach and utilize skills that will be relevant in future jobs and careers. For varying reasons, the data consistently demonstrates that women are disproportionately represented in STEM careers and that by middle school they are often turned away from taking courses that develop computational thinking skills. As educators, it is our job to expose students to a variety of experiences to develop skills with equity. This means that we need to design technology integration with equity in mind. Providing low-risk opportunities to gain computational thinking skills throughout out curriculums is one approach to limit the gender gap in STEM.
References:
Grover, S., & Pea, R. (2013). Computational Thinking in K–12: A Review of the State of the Field. Educational Researcher, 42(1), 38–43. https://doi.org/10.3102/0013189X12463051
Jenson, J., & Droumeva, M. (2017). Revisiting the media generation: Youth media use and computational literacy instruction. E-Learning and Digital Media, 14(4), 212–225. https://doi.org/10.1177/2042753017731357
Martinez, S. L., & Stager, G. S. (2013). Invent To learn: Making, tinkering, and engineering in the classroom. Torrance, CA: Constructing Modern Knowledge Press.
Patterson, S. (2014.). Learning with robots: content mastery and social skills. Edutopia, Retrieved from https://www.edutopia.org/blog/learning-robots-content-mastery-sel-sam-patterson
Wing, J. M. (2006). Computational Thinking. Communications of the ACM,49(3), 33-35.
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