When learning new knowledge, it is critical for students to connect new concepts with previous learning and experiences and then be able to transfer it in multiple and creative ways. It is, therefore, essential for teachers to structure learning using what has been discovered in the learning sciences.
In a recent lesson aimed at developing the computational thinking (CT) skills of seventh graders, I had the pleasure of partnering with Jason Vest, the iNACOL 2018 Teacher of the Year, who teaches at Hungary Creek Middle School.
Our goal was to have the students learn to apply the elements of CT as a problem-solving skill to both unplugged and plugged scenarios. CT, which is standard five of the ISTE Standards for Students, can be applied by both machines and humans. We purposefully coached students using the evidence-based strategies of learning targets and the jigsaw strategy to help them create and present computational artifacts.
As we coached students, they were able to draw on familiar concepts and connect CT to foundational computer science (CS) practices that involve designing solutions that leverage the power of computing as well as improve their literacy and collaboration skills.
These are three steps we took to implement the strategies:
Step 1: The mini-lesson
To introduce students to CT, the learning targets, the jigsaw strategy and the final product they were responsible for, we conducted a mini-lesson. Mini-lessons are excellent for sparking interest in topics, generating questions and introducing strategies to learners. We strategically leveraged their power in the following ways:
Student inquiry. We showed students an artifact depicting the CT elements, which included this graphic by the BBC for generating their own questions. Their questions were then curated in the form of a "need-to-know list." Both the artifact and the list were used to launch student inquiry and also point them in the direction of both CT and coding, which we used to guide future lessons within the unit of study.
Learning targets. To scaffold their thinking, we gave students learning targets so they understood the intended learning and expectations. We answered clarifying questions and helped them define new vocabulary (i.e., CT, computational artifact, flow chart and role play) in the learning targets. The learning targets for the lesson were:
- I can investigate and understand one of the four computational thinking elements.
- I can apply one or more of the four computational thinking elements through both role play and a computational artifact.
- I can develop a step-by-step algorithm for a personal task of my choosing using a flowchart (painting my nails, walking my dog, etc.).
- We partnered students in groups of three or four in preparation of the jigsaw strategy.
Step 2: The jigsaw strategy
For the purpose of having the students learn CT in tandem with problem-solving, using higher-order thinking skills and collaborating with peers, Vest and I used the jigsaw strategy. Developed by Dr. Elliot Aronson and his students at the universities of California and Texas, the jigsaw is a cooperative learning strategy where students in a group divvy up learning by each researching one aspect and teaching it to the others.
When executed effectively there is evidence that the jigsaw strategy also aids learners with mastering topics, improving literacy skills, spurring motivation and increasing enjoyment of the learning experience. In fact, an updated version of John Hattie’s list of influences on student learning lists the jigsaw strategy in the top 10 ways students learn and has an effect size of 1.20 — which is three times more effective and quite a leap from the average effect size .40 of the other strategies found in his database.
To implement the strategy, we had the students become experts on one of the four CT elements: decomposition, abstraction, pattern recognition and algorithm design by following this process:
Learning. In homogeneous expert groups, the students read and analyzed text (using annotating text strategies) about their element in the ISTE article "How to develop computational thinkers." To help them visualize what they read, some also created concept maps to share and connect their new understanding.
Using a rubric, the expert teams then created a synthesis in the form of a computational artifact. Here the students were provided voice and choice on how they would transfer learning using edtech tools such as Canva, videos, podcasts and Google Slides (among others).
For their computational artifacts, they created definitions for their CT element and cited personal relevance to it by correlating it to an everyday familiar task or activity (i.e., making a sandwich, tying a shoelace, brushing teeth, etc.). Each team also created original graphics to represent their element.
Finally, the students read a Gliffy blog and learned about the basics of making flow charts and the universal flow chart symbols of process, input/output, decision, start/end and arrows. Some of the students created a flow chart of the steps they took during their role play and the others chose to diagram new problems altogether.
Sharing. The expert teams returned to a heterogeneous group setting and presented and discussed their learning in a mini-presentation format — no more than six minutes was allotted for each group but Q&A did run over a bit. The students displayed their computational artifacts in a professional way as they discussed their CT element and the logic in their flow-chart algorithm. However, they really came alive during their role plays. We witnessed fun, excitement and transfer of learning that Vest and I are proud of.
Deepening the learning. In this final step of jigsaw strategy, the students returned to their expert groups and discussed how their CT element fits along with the other elements their classmates presented within the broader context of computational thinking as both a problem-solving and higher-order thinking skill.
They also revisited the ISTE article we presented them in the first step of the jigsaw strategy to base their discussions in the broader context of the entire text. Our purpose here was to help them deepen their understanding of both the text and the importance of CT as a series of foundational skills needed for future CS learning. At this time, we also introduced the collaboration rubric and had them discuss three things they did right and three things they will improve next time by reviewing the indicators together.
Step 3: Student reflection
A John Dewey quote that Vest and I shared with the students is, “We do not learn from experience. We learn from reflecting on experience.” Incorporating reflection into our work with them is something that we did at various stages. We found the practice helped the students make critical connections, learn from failure and deepen their understanding of CT.
In this lesson, students reflected by writing in journals. We then followed up with them in either whole-group discussions or individual consultations. Among the reflections we asked students to make:
- Why are computational thinking concepts and practices important for me to learn and use?
- How can I correlate computational thinking to what I already know?
- How can I introduce the concept of computational thinking to others (i.e., younger peers) in a presentation?
Student responses included:
- I can use CT as a problem-solving strategy in both familiar and unfamiliar situations that I encounter in my life.
- I can use algorithm design strategies to learn the steps to solving problems with math formulas.
- I can create a YouTube video or podcast to help teach my peers about the CT elements.
By helping the students connect their new learning to specific situations in and out of school and also understand how they can use CT to help others, we gained more know-how for developing design thinkers who are also global citizens (as emphasized in the ISTE Standards for Students).
Our own teacher reflections
Vest and I learned to trust that if the conditions and classroom culture are conducive to teaching and learning — ALL students can blossom and produce beautiful performances of their work.
We also learned that as teachers our role is not to make students learn but rather to enter the classroom equipped with instructional strategies (i.e., learning targets, jigsaw strategy, etc.) that will provide them the just-right supports they need to construct new knowledge by referencing and expanding on previous experiences.
We also learned that computational thinkers are developed over time and through multiple strategically designed experiences that demand our learners perform at higher levels by having them inquire, investigate, apply, create and present.
My sincerest gratitude to Robbi Moose, Jason Vest and Mike Dunavant for this collaboration.
Jorge Valenzuela is an ISTE member, an educational coach and a graduate teaching assistant at Old Dominion University. He is the lead coach for Lifelong Learning Defined, a national faculty of PBLWorks and a national teacher effectiveness coach with the International Technology and Engineering Educators Association (ITEEA). He is also a member of the Lead Educators Team for littleBits. You can connect with Jorge on Twitter @JorgeDoesPBL to continue the conversation.