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with algorithms that guarantee success if followed correctly. 17

Computational thinking has been suggested as an analytical thinking skill that draws on concepts from computer science but is a fundamental skill used by, and useful for, all people. 28 Some have argued that computational thinking is a practice that is central to all sciences, not just computer science. 13, 28 Bundy, 4 for example, noted that computational thinking concepts have been used in other disciplines through problem-solving processes and the ability to think computationally is essential to every discipline. These powerful ideas and processes have begun to have significant influence in multiple fields, including biology, journalism, finance, and archaeology, 22 making it important to include computational thinking as a priority for K– 12 education. Wing28 said, “To reading, writing, and arithmetic, we should add computational thinking to every child’s analytical ability.” In summary, computational thinking is a set of problem-solving thought processes derived from computer science but applicable in any domain.

Embedding computational thinking
in K– 12 teaching and learning requires
teacher educators to prepare teachers
to support students’ understanding
of computational thinking concepts
and their application to the disciplin-
ary knowledge of each subject area.
Specifically, teacher educators need
to provide teachers with the content,
pedagogy, and instructional strategies
needed to incorporate computational
thinking into their curricula and prac-
tice in meaningful ways, enabling their
students to use its core concepts and
dispositions to solve discipline-specific
and interdisciplinary problems. It is
important to acknowledge that the cur-
rent lack of an agreed-upon, exclusive
definition of the elements of computa-
tional thinking makes it a challenge to
develop clear pathways for pre-service
teachers to be educated teachers—
computationally. 30 Nevertheless, it is
both important and possible to begin
taking steps in this direction.

Here, we argue that, given the cross-
disciplinary nature of computational
thinking and the need to address
educational reforms—Next Genera-
tion Science Standards and Common
Core—it is beneficial to prepare teach-
ers to incorporate computational
thinking concepts and practices into
K– 12 classrooms. While most current
efforts to embed computational think-
ing focus on in-service professional
development, we posit that pre-service
teacher education is an opportune
time to provide future teachers with
the knowledge and understanding they
require to successfully integrate com-
putational thinking into their curricu-
la and practice. The following sections
discuss the relevance of computation-
al thinking constructs in K– 12 educa-
tion. We also discuss how to embed
computational thinking into class-
rooms by using it as a methodology for
teaching programming. In addition,
we provide examples of how teachers
in various disciplines can use computa-
tional thinking to address and enhance
tional thinking and the core constructs
that would make it relevant for key
stakeholders from K– 12 education and
teacher-training programs.

Denning suggested13 that the idea of computational thinking has been present since the 1950s and 1960s “as algorithmic thinking,” referring specifically to using an ordered and precise sequence of steps to solve problems and (when appropriate) a computer to automate that process. Today, the term “computational thinking” is defined by Wing28 as “solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science.” Computational thinking also involves “using abstraction and decomposition when attacking a large complex task or designing a large complex system.” 28 A report on computational thinking by the National Council for Research suggested it is a cognitive skill the average person is expected to possess. For example, the cognitive aspects of computational thinking involve the use of heuristics, a problem-solving approach that involves applying a general rule of thumb or strategy that may lead to a solution. 28 This heuristic process involves searching for strategies that generally produce the right solution but do not always guarantee a solution to the problem. For example, “asking for directions in an unfamiliar place” from a local usually leads one to the right place, but one could also end up at a wrong place, depending on one’s understanding of local geography. 17 Heuristic processes can be contrasted

Edtech start-up pavilion at International Society for Technology in Education conference.