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Image source: https://www.chapman.edu/scst/graduate/phd-computational-science.aspx Pe Pedag agogical al Guidelines s an and a a Lear arning Pr Progressi ssion for CT CT Int ntegr egration Shuchi Grover, Ph.D. (@shuchig) Senior


  1. Image source: https://www.chapman.edu/scst/graduate/phd-computational-science.aspx Pe Pedag agogical al Guidelines s an and a a Lear arning Pr Progressi ssion for CT CT Int ntegr egration Shuchi Grover, Ph.D. (@shuchig) Senior Research Scientist, Looking Glass Ventures | Visiting Scholar, Stanford University

  2. Acknowledge Ac dgeme ments SRI Looking Glass International Ventures Vanderbilt University Stanford University Digital Promise Global ETR Salem State EDC University NSF # NS #1343227, # , #1543062, # , #1640199, # , #1639850, # , # 1647018 @shuchig

  3. C2STEM: VELA (Variables, Understanding Synergistic Learning of Expressions, Loops. & Computational Thinking Physics/Biology & CT Abstraction) Computational Processes and Practices in through computational Concepts for Middle School Introductory Programming modeling in secondary Programming school Foundations for Integrating CT into Advancing Science & Math Computational Thinking: activities for pre-K Balanced Designs for Deeper Learning in Intro learners in formal & Programming informal settings NSF# 1639850 / 1827293 (EDC) NSF Workshop on ‘Computational Thinking From K-12 Disciplinary Perspectives NSF#1647018

  4. C2STEM: VELA (Variables, Understanding Synergistic Learning of Computational Thinking Expressions, Loops. & Physics/Biology & CT Processes and Practices in Abstraction) through computational Introductory Programming modeling in secondary Computational school Concepts for Middle School Programming NSF#1543062 Integrating CT into Science Foundations for & Math activities for preK Advancing learners in formal/informal Computational Thinking: settings Balanced Designs for Deeper Learning in Intro Programming Understanding Implementation Factors in K-12 Computer Science (EDC) NSF Workshop on ‘Computational Thinking From K-12 Disciplinary Perspectives’ NSF#1647018

  5. VELA (Variables, Understanding C2STEM: Expressions, Loops. & Computational Thinking Synergistic Learning of Abstraction) Computational Processes and Practices in Concepts for Middle School Introductory Programming Physics/Biology & CT Programming through computational modeling in secondary school NSF#1640199 Measuring Collaborative Foundations for Computational Problem- Advancing Solving Skills Computational Thinking: Balanced Designs for Deeper Learning Foundations for Integrating CT into Science Advancing & Math activities for preK Computational Thinking: learners in formal/informal Balanced Designs for settings Deeper Learning in Intro Programming (EDC) NSF Workshop on ‘Computational Thinking From K-12 Disciplinary Perspectives NSF#1647018

  6. C2STEM: VELA (Variables, Understanding Synergistic Learning of Expressions, Loops. & Computational Thinking Physics/Biology & CT Abstraction) Computational Processes and Practices in through computational Concepts for Middle School Introductory Programming modeling in secondary Programming school Integrating CT into Science Foundations for & Math activities for preK Advancing learners in formal/informal Computational settings Thinking: Deeper Learning in Intro Understanding Programming Implementation Factors in K-12 Computer Science (EDC) NSF Workshop on NSF#1343227 ‘Computational Thinking From K-12 Disciplinary Perspectives’ NSF#1647018

  7. & STEM CT / Programming

  8. Pieces of the STEM+C Integration Curricular Puzzle Programming Unplugged Activities Activities Integrated STEM+C Non-programming Synergistic learning Digital/ Interactive activities Activities @shuchig

  9. 1. Exploit Synergies between STEM Sample Designed Mathematics Science Topics/Concepts Activities CT Skills Concepts / Practices / Practices concepts/practices City Walk Algorithms Counting, Comparing, Modeling, Representations (Physical & Digital (Sequences & (more or less than, equal (3-D spatial and 2-D activity suite) Loops) Encoding to) Spatial reasoning/ representations) visual spatial counting & Carmella’s Apple Problem Measurement (Length), Sink and float, Store Decomposition, Counting, Cardinality Ramps & pathways, CT/CS Testing and Practices: Observation, Debugging Developing & planning investigations; Cause & effect concepts/practices Grocery Store Abstraction, Counting Spatial Food & Nutrition Pattern reasoning/visual spatial Practices: Observing & Recognition describing, Classifying & sorting, Comparing & contrasting

  10. Source: 2. Code.org Engage with CT in STEM & coding concepts outside of coding Source: http://csforall.sri.com (VELA Project)

  11. 3. Begin with non- coding activities (especially if learners are unfamiliar with coding)

  12. A Le Lear arning Progression for CT Creating new Complex Co representations In Inte tegra grati tion that allow algorithmic processing by a machine for new Writing interpretations programs to only possible model, thru automation generalize, predict, Creating Simple Si e interrogate simple in integratio ion relationships/ programs that phenomena automate an algorithmic Engaging in process or aid unplugged data analysis activities in the domain addressing elements of CT (algorithmic steps, decomposition, pattern recognition, …) Grover, S. (2018). Thinking about Computational Thinking and How Learning Sciences Can Shape Deeper Learning of Computer Science in Schools. Keynote at the 26 th Annual Conference on Computers in Education, Manila, Philippines. (https://shuchigrover.com) @shuchig

  13. A Le Lear arning Progression for CT A Breakdown A wn/Progression for Co Computational Modeling in STEM Coding Identifying & Understanding Writing generalized articulating relevant variables Understanding programs to models; use in the system ß initialization: relationships in model a models to words/pseudo- Playing with Identifying phenomenon predict, code à existing initial values (hard-coding interrogate, simulations; and initial set- updating for specific understand variables using Parameter up of the scenarios is relationships/ simulation expressions sweeping OK!) phenomena with variables activities Grover, S. (2019, April 29). Computational Modeling: How Can We Manage Cognitive Load When Students Must Simultaneously Learn to Code AND Code to Learn in a STEM Classroom? (https://shuchigrover.com) @shuchig

  14. STEM Computing shuchig@cs.stanford.edu http://shuchigrover.com

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