Assessing Students’ Computational Thinking Application in Core Subject Areas
Computational thinking (CT) is becoming widely recognized by educators as a powerful tool students can use in learning across all subject areas — science, language arts, mathematics, and social studies — rather than exclusively associated with computer science.
Teachers that are implementing CT integration are more frequently defining CT as a metacognitive strategy that deepens learning opportunities and helps students think systematically about their problem-solving approaches. Because the emphasis of CT integration is on providing students with metacognitive strategies and less of a focus on stand-alone content based in coding, it’s also being seen as a possible mechanism for improving student achievement on assessments in core subject areas. We are seeing this to be especially the case in elementary classrooms. However, unlike most subject-area assessment practices, there is an emerging trend of teachers shifting away from using standardized assessments and instead creating their own, individualized assessment practices that examine student mastery of CT within subject areas.
Over the past three years, funded by the Robin Hood Learning + Technology Fund, my colleagues and I have been documenting the pathways, practices, and other educational efforts of over 20 high-poverty elementary schools in New York City in an effort to develop clear models of effective school-wide CT integration. In this work, we routinely ask educators to explain why they believe CT is important for students to learn, how they envision students using CT in core subject work, and what their practices are for assessing evidence of CT knowledge and application.
We often hear educators express that their primary concern with integrating CT into subjects is taking time away from test preparation. However, after spending at least one full school year integrating CT, the majority of participating educators interviewed saw evidence of CT integration as having a positive impact in their students’ learning. Teachers described it as a mechanism for encouraging collaboration, fostering persistence and a growth mindset, helping to address a targeted area that students typically struggled with. For example, a participating teacher stated, “[In the beginning,] I didn’t see [CT] in every subject area, but now I see how it’s being applied to more than just the math curriculum. It’s also being applied to the language arts…and I see how it’s being integrated across all of the areas”. While educators are seeing evidence of students applying CT, what’s not agreed upon is how to measure and formally assess evidence of students’ computational thinking knowledge within subject areas.
When beginning this work, the participating schools examined different standardized CT assessments, to determine if the assessment could effectively provide teachers with evidence of students’ CT application. While there are currently numerous assessments available that exclusively measures either CT or subject-area knowledge separately, there aren’t assessments that address the application of CT within a subject area and how CT may shift student’s mastery of a subject. Exclusively having tests that look at CT or core subject knowledge isn’t enough to answer the growing hypothesis that the most impactful implementation model is one that looks at computational thinking in math and literacy. This matters because teaching is fundamentally different when doing integration versus teaching one subject exclusively.
Another challenge we are seeing in regards to assessing CT is that teachers frequently describe CT being a “problem-solving” process or as a metacognitive strategy, i.e. that it is less about how it is implemented on paper or on a computer and more about the thinking behind how the problem was solved. Educators repeatedly expressed that they were unsure as to how you would replicate the thought process students are using when solving problems on subject area assessments. Because CT is a fairly new concept in education, in general the lack of concrete performance indicators per grade level and lack of existing curriculum examples leaves teachers questioning what these kinds of assessment should look like. Assessing CT integrated into subject areas is not a one size fits all solution.
However, these challenges don’t mean that educators aren’t implementing assessments; in fact, it’s the opposite. Rather than relying on existing assessments, the educators we are working with have taken the initiative to develop their own assessment practices that target both the subject-area skills and the CT concepts and practices. The assessment strategies we are seeing most commonly used in practice fall into three specific categories:
Authentically using CT Vocabulary in Classwork
A common theme that emerged in our work showed that effective CT integration started with unplugged experiences that scaffolded student understanding by introducing CT vocabulary before students engaged in computational activities that used computers or digital devices. When integration started by presenting CT as problem solving strategies for math and ELA, rather than CS and coding, it not only increased teachers’ confidence to try, adapt and, in some cases, create CT curricular materials on their own, it also provided students with a foundational understanding of CT concepts. This allowed students to approach CT integration as a metacognitive strategy that can be applied across multiple concepts and subject areas, rather than as a standalone content area.
Student CT Self-Reflections
The second most commonly used assessment practice implemented is asking students to complete a self-reflection where they describe what CT concepts and practices they used during problem solving. This is happening both informally, by teachers asking students to verbally respond to specific questions during and after completing work, or formally by completing self-reflection checklists or writing descriptions of how they applied CT practices when completing their work.
School or Teacher Created CT Rubrics
Finally, teachers are creating CT rubrics that they distribute before completing work that provides students with performance indicators for the five major concepts in CT: decomposition, abstraction, algorithm design, debugging, and evaluation. As with traditional rubrics, each concept includes a four-point scale that rates student performance at above grade level, meeting grade level, approaching grade level or below grade level.
While each of the above strategies have their own strengths for implementation and provide educators with easily identifiable evidence of students’ CT knowledge and application, a common challenge between them is the inability to provide school systems with the necessary standardized achievement data that is traditionally required as evidence of impact. Yet, computational thinking education and integration is still an emerging field, leaving many of the educators currently leading this initiative feeling as though they are “paving the road while driving”. Over the next two years, our work will continue to examine the pathways and practices elementary schools undertake in order to shift existing practices to be inclusive of computational thinking and the impact it may have on improving student achievement.
About the Author: Heather Sherwood is currently a Research Associate at EDC’s Center for Children and Technology, where she works on a variety of research projects examining the role of CT integration in elementary curricula. She is currently Co-Principal Investigator on Building CT Readiness: A Framework for Integrating Computational Thinking Across Subjects in High-Poverty Elementary Schools, an NSF-funded project investigating and refining a set of resources designed to help elementary schools integrate CT. She also applies her expertise in computational thinking on the current project IdentifyingEffective Models for Integrating Computational Thinking into NYC Elementary Schools, funded by the Robin Hood Learning + Technology Fund, in conducting case studies about effective models for integration of computational thinking in New York City elementary schools. Before her career in education research, she was an elementary grade teacher and taught Computer Science classes for after-school programs, including Scratch and Lego Robotics. She also worked as a freelance curriculum writer for a major publisher, developing lesson plans that integrated coding into science content.
