Adjusting for 21st century learning by asking questions and modeling computational thinking

With so many current unknowns circulating on the physical environment and access to resources, how can educators effectively teach 21st century skills and standards? How can peer-coaches help teachers navigate this difficult year, with possibly transitioning between online, in-person, and hybrid teaching?

Strategy 1: Ask questions!

As part of peer coaching or team collaboration, by asking probing questions about the overall essential learning standards and the lesson development, teachers can intentionally create engaging lessons with a strong purpose that promote 21st century skills (learn more about 21st century skills).

In this Covid-era of learning, a clear purpose and learning objectives are essential. So are explicit directions. The connection between the learning standard and task directions need to be accurate in order to guide students (and assisting family members) towards the desired learning outcomes. By asking two specific questions, coaches and educators can determine if the directions lead students to the appropriate skill development:

To help bridge the potential gap between directions and standards, educators need to review both and then answer two questions: What skills, particularly 21st-century skills, do you want students to develop? If students follow your directions, will they develop these skills? (Meyer et al., 2011x).

Les Foltos. (2013). Peer Coaching : Unlocking the Power of Collaboration. Corwin.

These two questions provide a start for educators to assess the clarity between the purpose and the task, and can potentially reveal a disparity between the intention of developing 21st century skills and the reality.

Strategy 2: Understand and Model Computational Thinking Problem-Solving

In addition to asking these specific questions, coaches and educators need to repeatedly incorporate and model 21st century skills and computational thinking skills. This video by Google Online Open Education can be a great third data point for educators to better understand what computational thinking is, examples, and why this thinking is important for students to develop:

Research over the last decade had demonstrated the significance and need in incorporating the different elements of computational thinking in the classroom. In addition, specific research assessing educators (specifically, preservice teachers) reveals a superficial understanding and only a rudimentary notion of how to incorporate into lessons (Yadav, Gretter, Good and McLean). Conversations about computational thinking, understanding the different elements, and modeling computational thinking for teachers and students is critical in encouraging the normalization of computational thinking in educational practices.

What are the four problem-solving elements of Computational Thinking?

Decomposition – breaking down complex problems into smaller, more manageable parts

Pattern Recognition – identifying or mapping similarities or differences (often based upon experiences or models)

Abstraction – the filtering of important or unimportant information, often to make a problem easier to understand or to solve

Algorithm – using steps to organize or plan (often towards a solution)

Peer coaches then can use the two questions above and apply the four different problem-solving skills of computational thinking into intentional questions on lesson design, holistically or targeted on specific components. Developing questions for educators to think critically about the students’ learning or the lesson design can help apply these same processes into intentional lesson design. Specific examples on “How to develop computational thinkers” by Jorge Valenzuela, ISTE 2020 and “Early learning strategies for developing computational thinking skills” by Kristen Thorson, Getting Smart 2018.

While asking questions and modeling computational thinking are essential in developing educators who are equipped to model lessons centralized around these learning skills, peer coaches and teacher teams need to recognize that these conversations may or may not be appropriate given current circumstances with Covid. Coaches and peers should start meetings with check-ins to determine the relevancy. Conversations about the effectiveness of directions in achieving the necessary learning standard may greatly benefit the teacher (and the students). Realizing student could benefit from small group conversations modeling pattern recognition might alleviate frustrations with empty worksheets.

How are computational problem solving skills incorporated into your lessons or coaching conversations? Does the district or school require a specific template to organize the directions between a learning standard and the assessment?

Resources and References

“6 The Design of Learning Environments.” National Research Council. 2000. How People Learn: Brain, Mind, Experience, and School: Expanded Edition. Washington, DC: The National Academies Press. doi: 10.17226/9853.

21st Century Skills Framework for Developing Leadership PDF by OSPI

“Computational Thinking.”

Foltos, L. (2013). Peer Coaching : Unlocking the Power of Collaboration. Corwin.

Foltos, L. (2018). Coaching Roles. Peer-Ed, Mill Creek.

Harvard, Blake. “How parents can help their kids with studying.” 31 Oct 2019. Viewed Oct 2020. Parent Partnership, Edutopia.

ISTE Standards for Coaches | ISTE. (n.d.). Retrieved October 2, 2020, from

National Research Council. 2010. Report of a Workshop on the Scope and Nature of Computational Thinking. Washington, DC: The National Academies Press. Chapter 5 & 6.

Thorson, Kristen. “Early learning strategies for developing computational thinking.” 18 Mar 2018.

Valenzuela, Jorge, “How to develop computational thinkers.” 22 Sep 2020 updated from post 22 Feb 2018.

Yadav, Aman; Gretter, Sarah; Good, Jon; & McLean, Tamika. “Computational Thinking in Teacher Education.” Uploaded by Yadav 2017 Research Gate. Springer International Publishing AG 2017 205. P.J. Rich, C.B. Hodges (eds.), Emerging Research, Practice, and Policy on Computational Thinking, Educational Communications and Technology: Issues and Innovations, DOI 10.1007/978-3-319-52691-1_13

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