Empowering the Whole Technologist: Social and Emotional Learning to Support Computational Thinkers |
Participate and share : Poster
Laurel Ozersky
Persistence is imperative to iterative work, as is organization to data analysis. The necessary skills for computational thinking are closely related to social and emotional learning skills (SEL). This session provides actionable steps to help educators empower their students with SEL to be successful computational thinkers.
Audience: | Coaches, Professional developers, Teachers |
Skill level: | Beginner |
Attendee devices: | Devices useful |
Attendee device specification: | Smartphone: Android, iOS, Windows Laptop: Chromebook, Mac, PC Tablet: Android, iOS, Windows |
Participant accounts, software and other materials: | Participants will find a Gmail or other Google account with access to Google Classroom helpful but not required. |
Topic: | Computer science & computational thinking |
Grade level: | 9-12 |
Subject area: | Science, STEM/STEAM |
ISTE Standards: | For Students: Empowered Learner
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How has the “whole-child” approach to education evolved with the digital age?
Computational thinking and digital literacy are commonly used phrases in today’s increasingly virtual landscape. Each eliciting visions of students confidently drafting procedures, diligently conducting tests, and eagerly making revisions. But building students capable of this takes more than traditional content instruction. Many state standards already include “practice” standards that are skill-based rather than content-based and select curricula incorporate these skills, often under the umbrella of social and emotional learning (SEL).
This session provides participants with an easy-to-use/easy-to-modify process to develop and revise instructional content to intentionally build the SEL skills necessary for success in 21st century classrooms and careers. Split into two main segments, the first part of this session will review the existing research and frameworks around SEL and computational thinking, with special attention to the areas of significant overlap. In the second part, participants will review methods of supporting these competencies and practice implementing them. Participants are encouraged to bring their own instruction materials to work with in order to derive the most value from the session.
I. Introductory Activity and Debrief (Independent activity and group discussion; approx. 10 minutes)
As participants join the session, they will complete a short task using a common interactive technology (for example: a PhET Simulation). After a brief exploration, the group will share out and discuss the experience, taking into consideration the skills they employed to move through the activity. The goal of this segment is to illustrate the many varied skills that even short interactions with technology require - some of these skills are content-based but many more are related to the skills we develop as we nurture the human, not just the scientist or engineer.
II. Research Review (Approx. 10 minutes)
In a lecture format, we will move on to review the relevant research from some of the “big players” in the fields of computational thinking and social and emotional learning. We will also clarify some terminology since social and emotional learning has become an umbrella term in many instances. Please see the “Supporting Research” section for more about the research to be shared in this segment.
III. Application Overview and Model (Approx. 10 minutes)
The primary objective of this session is to provide participants with an easy-to-use/easy-to-modify process for creating and revising instructional materials to include opportunities for building the SEL that supports computational thinking. In this segment, we will review and model that process using a sample science lesson.
IV. Practice! (Approx. 20 minutes)
In this segment, participants have time to work, independently or collaboratively, on drafting or revising instructional materials to incorporate SEL using the techniques and resources shared in the session. If participants did not choose to bring personal materials to work on, they will be provided with other sample lessons and resources for practice purposes. During this time, the instructor will circulate to answer any questions and spark discussion amongst participants.
(If presenting virtually, this segment will account for approximately 10 minutes of the session.)
V. Debrief + Close (Approx. 10 minutes)
To conclude the session, led by the instructor, participants will share their remaining thoughts and questions around the goal and the process shared in the session. Additionally, this time will be used for capturing these thoughts in a discussion form on Google Classroom for participants to revisit as they continue this process back at their institutes.
Bainbridge, K., Shute, V. J., Rahimi, S., Liu, X., Slater, S., Baker, R. S., & D'Mello, S. (in press). Does embedding learning supports enhance transfer during game-based learning?. To appear in Learning & Instruction (42 pages).
Clarke, A., Sorgenfrei, M., Mulcahy, J., Davie, P., Friedrich, C. & McBride, T. (2021). Adolescent mental health: A systematic review on the effectiveness of school-based interventions. Early Intervention Foundation.
Digital Promise. (2021, March). Powerful learning with computational thinking: Our why, what, and how of computational thinking. Digital Promise.
https://doi.org/10.51388/20.500.12265/115
OECD (2021), Beyond Academic Learning: First Results from the Survey of Social and Emotional Skills, OECD Publishing, Paris,
https://doi.org/10.1787/92a11084-en.
PISA 2025 Learning in the Digital World -- First full draft of assessment framework to be published in November 2021
Laurel Ozersky is a Learning Engineer for BrainPOP Science. In this role, she focuses on design and development of inquiry-based science investigation and the supporting three-dimensional assessments. Previously, she served as a Learning Solutions Designer at ACTNext by ACT, Inc. where she designed and developed technology-enhanced courses to foster and assess higher-order thinking skills, with an emphasis on computational thinking. Prior to ACTNext, Laurel taught high school science and math in Inglewood, CA. She studied physics and education at UC Berkeley and received her M.Ed. from Pepperdine University.
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