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High- and Low-Tech Peeps! STEM CT Learning — It’s About the Teaching

,
Pennsylvania Convention Center, 120A

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Snapshots are a pairing of two 20 minute presentations followed by a 5 minute Q & A.
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Presenters

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Director
Longwood ITTIP
@ITTIPSTEM
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STEM Learning Specialist
Stephanie Playton is a STEM Learning Specialist from Longwood University in rural, Virginia. Her primarily role serves the PK-12 environment in STEM through grant funded, community partnerships. Scholarly contributions and expertise also include topics such as computational thinking, integrated learning, building STEM career knowledge/interest, and computer science.

Session description

Supporting computational thinking in classroom instruction doesn’t have to be high-tech! Come to this session to learn hands-on some of the activities that have been developed and modified through a teacher and university partnership supporting an interdisciplinary approach to teaching STEM with computational thinking through a curriculum.

Purpose & objective

The purpose of this session is to model how computational thinking (CT) can be integrated into learning experiences, including plugged and unplugged applications. Participants will get an overview of CT vocabulary, as well as the overarching purpose of integrating CT (i.e., CT dispositions, attitudes and characteristics) - to support an innovative and prosperous workforce. Participants will get to experience and discuss how other subject areas can be integrated with CT, empowering and fostering CT inspired and designed learning experiences that impact the students and teachers they work with.

The pedagogical framework for this unit focuses on integrating inquiry based science, technology, engineering, mathematics, and computational thinking learning (STEM CT). While the developed unit focuses on watershed and plant science, we will be challenging ISTE participants to think about how they can design and integrate these concepts into their own school and classroom topics and content areas. For instance, pollination is a process that our students (in Virginia) need to know. The concept of pollination can be related to CT concepts, such as algorithms and procedures (i.e., steps in a process) and simulation (i.e., modeling a process). This could also be an opportunity to dive deeper and incorporate large data sets on bee populations (data analysis). Teachers decide how to implement the concept of pollination depending on their classroom environmental factors (e.g., online, difficulty, access to materials). This could be done with a number of diverse topics, including connections to social studies and Language Arts content, which will also be illustrated within context of our STEM CT unit presentation (e.g., use abstraction and parallelism to create a class book on the importance of forests in Bookcreator).

Our experiences with this curriculum have taken place in rural schools which are often challenged with connectivity and infrastructure disparities. We will be sharing examples of lessons and activities that have been modified to meet the needs of students. This session has the following participant objectives:
Learn and identify CT (vocabulary) as embedded in activity experiences during workshop;
Practice and provide examples of how CT can be integrated into their own district/school or classroom learning;
Design classroom learning experiences that integrate STEM CT; and
Understand that student engagement in CT can include high or low-tech opportunities (i.e., CT is not just coding).

The STEM CT Unit that was developed and will be shared includes 7 lessons intended to be taught over approximately a six-week period in 3rd-5th grade. Each lesson includes a STEM CT Framework summary of NGSS and Common Core Mathematics connections, as well as CSTE and ISTE’s (2011) CT dispositions, attitudes, and characteristics. In addition, each lesson is broken down into activities (45m-1h30m) by Introduction, Materials, Teacher Preparation, Plan, and Printables. Furthermore, everything is made digital - as well as the presentation slides and other digital activities (e.g., large data sets, Google Draw).

Additionally, evidence of the STEM CT curriculum implementation will be shared through student and teacher artifacts and testimonies during the presentation.

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Outline

Who Are We? (0-5m): Introduction of audience, presenters and project

Process - direct Instruction; digital poll (e.g., grade level, content areas, knowledge of CT)

What is CT and Why is it important? (5-10m): Review CSTA and ISTE’s Framework for CT (handout); discuss CT dispositions, attitudes, characteristics, and vocabulary examples. Make connections to low-tech and high tech opportunities.

Process - direct Instruction; digital link; printable; monitored back channel

Examples of Integrated STEM CT (10-25m): Experience STEM CT activities on pollination; Discuss and make connections to CT; View lesson activities for retelling stories; Discuss and make connections; Share lesson on forest text; Discuss and make connections; View storytelling examples; Share examples of content connections made in own grade level areas; Highlight the technology in each lesson (e.g., high - Bookcreator, Bloxels; low - digital sorts).

Process - monitored back channel; peer to peer interaction; direct instruction

Participant Questions (25-30m): Closing Q & A

Process - Whole Group; monitored back channel

(Other Slides)

Contact Information; ISTE Connections; Research

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Supporting research

Barnes, M. B., & Barnes, L. W. (2005). Using inquiry processes to investigate knowledge, skills, and perceptions of diverse learners: An approach to working with prospective and current science teachers. In A. J. Rodriguez & R. S. Kitchen (Eds.), Preparing mathematics and science teachers for diverse classrooms: Promising strategies for transformative pedagogy (pp. 61–86). Mahwah: Lawrence Erlbaum Associates.

Colliver, J. A. (2000). Effectiveness of problem-based learning curricula: Research and theory. Academic Medicine, 75(3), 259-266. http://dx.doi.org/10.1097/00001888-200003000-00017

Concord Consortium. (2019). Common Online Data Analysis Platform (CODAP). Website: https://codap.concord.org

Crawford, B. A. (2000). Embracing the essence of inquiry: New roles for science teachers. Journal of Research in Science Teaching, 37(9), 916-937. http://dx.doi.org/10.1002/1098-2736(200011)37:9<916::AID-TEA4>3.0.CO;2-2

English, L. D. (2017). “Advancing elementary and middle school STEM education.” International Journal of Science and Mathematics Education, 15, 5–24. https://doi.org/10.1007/s10763-017-9802-x.

Friedman, Thomas L. 2005. The world is flat: a brief history of the twenty-first century. New York: Farrar, Straus & Giroux.

Frykholm, J. A., & Glasson, G. (2005). Connecting science and mathematics instruction: Pedagogical context knowledge for teachers. School Science and Mathematics, 105(3), 127-141.

Goodnough, K., & Cashion, M. (2006). Exploring problem-based learning in the context of high school science: Design and implementation issues. School Science and Mathematics, 106(7), 280-295. http://dx.doi.org/10.1111/j.1949-8594.2006.tb17919.x

International Society for Technology in Education (ISTE) and Computer Science Teachers Association (CSTA), (2011). Operational Definition of Computational Thinking for K-12 Education. Retrieved from https://id.iste.org/docs/ct-documents/computational-thinking-operational-definition-flyer.pdf

Leach, P.K., Playton, S.C. (2017). Problem-based interdisciplinary STEM learning with hummingbird robotics. Virginia Association for Supervision and Curriculum Development Journal, 14. Retrieved from http://publications.catstonepress.com/i/894646-fall-2017

Leach, P.K., Playton, S.C. & Talaiver, M. (2019, April 30). 8 STEM tools you can use for any subject. Retrieved from https://www.iste.org/explore/Toolbox/5-STEM-tools-you-can-use-for-any-subject

Lieux, E. M. (1996). A comparative study of learning in lecture versus problem-based format. About Teaching, 50, 25-27.

Loepp, F. (1999). Models of curriculum integration. Journal of Technology Studies, 25(2), 21-25

Lye, S. Y. & Koh, J.H. (2014). “Review on teaching and learning of computational thinking through programming: What is next for K-12?” Computers in Human Behavior. Vol. 41, 51-61.

Marshall, J. Horton, B. & Austin-Wade, J. (2007). Giving meaning to the numbers. Science Teacher, 74(2), 36-41.

McClure, E. R., Guernsey, L., Clements, D.H., Bales, S.N., Nichols, J., Kendall-Taylor, N., & Levine, M.H. (2017). “STEM starts early: Grounding science, technology, engineering, and math education in early childhood.” New York: The Joan Ganz Cooney Center at Sesame Workshop.

Morrison, J. A. & Roth McDuffie, A. (2007, April). Connecting science and mathematics: Using inquiry investigations to learn about data collection, analysis, and display. Poster presented at the annual meeting of the National Association for Research in Science Teaching. New Orleans, LA.

Moseley, C., & Utley, J. (2006). The effect of an integrated science and mathematics content based course on science and mathematics teaching efficacy of preservice elementary teachers. Journal of Elementary Science Education, 18(2), 1-12. http://dx.doi.org/10.1007/BF03174684

Paige, K., Lloyd, D., & Chartres, M. (2008). Moving towards transdisciplinarity: An ecological sustainable focus for science and mathematics pre-service education in the primary/middle years. Asia-Pacific Journal of Teacher Education, 36(1), 19-33. http://dx.doi.org/10.1080/13598660701793350

Park-Rogers, M., Volkmann, M., & Abell, S. (2007). Science and mathematics: A natural connection. Science and Children, 45(2), 60-61.

Perez, A. (2018). “A framework for computational thinking dispositions in mathematics education.” Journal for Research in Mathematics Education, 49(4), 424-461. DOI: 10.5951/jresematheduc.49.4.0424

Qualls, J.A.& Sherrell, L.B. (2010). “Why computational thinking should be integrated into the curriculum.” Journal of Computing Sciences in Colleges. 25(5), 66-71.

Stroud Water Research Center. (2019). WikiWatershed Toolkit. Website: https://wikiwatershed.org

U.S. Bureau of Labor Statistics. (2017) Spotlight on Statistics. https://www.bls.gov/spotlight/2017/science-technology-engineering-and-mathematics-stem-occupations-past-present-and-future/pdf/science-technology-engineering-and-mathematics-stem-occupations-past-present-and-future.pdf

Venville, G., Rennie, L., & Wallace, J. (2004). Decision making and sources of knowledge: How students tackle integrated tasks in science, technology, and mathematics. Research in Science Education, 34(2), 115-135. http://dx.doi.org/10.1023/B:RISE.0000033762.75329.9b.
.

Voogt, J., Laferrière, T., Breuleux, A., Itow, R. C., Hickey, D. T., & McKenney, S. (2015). “Collaborative design as a form of professional development.” Instructional Science, 43(2), 259–282. https://doi.org/10.1007/s11251-014-9340-7

Webb, M., Davis, N., Bell, T, Katz, Y.K., Reynolds, N., Chamber, D.P., Systo, M.M. (2017). “Computer science in K-12 school curricula of the 21st century: why, what and when?” Education and Information Technologies, 22: 445-468. https://doi.org/10.1007/s10639-016-9493-x

Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016). “Defining computational thinking for mathematics and science classrooms.” Journal of Science Education and Technology, 25,127-147.

West, L., & Straub, F.C. (2003). Content-Focused Coaching: Transforming Mathematics Lessons. Portsmouth, N.H.: Heinemann.

Wing, J.M. (2006). “Computational thinking.” Communications of the ACM, 49(3), 33-5.

Wing, J. M. (2008). “Computational thinking and thinking about computing.” Philosophical Transactions of the Royal Society, 366, 3717–3725.

Yadav, A., Hong, H. & Stephenson, C. (2016). “Computational thinking for all: pedagogical approaches to embedding 21st centruy problem solvin gin K-12 classrooms.” TechTrends, 60(6), 565-568. https://doi.org/10.1007/s11528-016-0087-7

Yadav, A., Zhou, N., Mayfield, C., Hambrusch, S., & Korb, J.T. (2011). “Introducing computational thinking in education courses.” Proceedings of the 42nd ACM technical symposium on Computer science education, 465-470. New York: ACM.

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Session specifications

Topic:
Computer science & computational thinking
Grade level:
PK-5
Skill level:
Beginner
Audience:
Curriculum/district specialists, Principals/head teachers, Teachers
Attendee devices:
Devices required
Attendee device specification:
Smartphone: Android, iOS, Windows
Laptop: Chromebook, Mac, PC
Tablet: Android, iOS, Windows
Subject area:
Computer science, STEM/STEAM
ISTE Standards:
For Educators:
Learner
  • Set professional learning goals to explore and apply pedagogical approaches made possible by technology and reflect on their effectiveness.
Designer
  • Explore and apply instructional design principles to create innovative digital learning environments that engage and support learning.
For Students:
Computational Thinker
  • Students collect data or identify relevant data sets, use digital tools to analyze them, and represent data in various ways to facilitate problem-solving and decision-making.