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Teaching Math Through Coding and Robotics

Pennsylvania Convention Center, 118A

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Doctoral Candidate
Boise State University
This session will focus on K-12 educators aligning math standards and curriculum to coding and robotics. Educators will utilize robots to drive curriculum instruction in mathematics. Learning targets and success criteria will be integrated into the instructional model to assist educators inspired to implement coding and robotics with math instruction.
Teacher and Doctoral Student
Boise State University
Nicole is a 28 year veteran teacher primarily in fifth grade. She is continuing her educational journey by getting her doctorate in educational technology from Boise State University in Boise, Idaho.

Session description

This session will demonstrate how to align math standards with coding and robotics challenges. Success criteria and learning targets will be identified as educators develop robotics lessons in math implementation. Project-based learning, student collaboration and 21st-century skills will be addressed.

Purpose & objective

Attendees will develop coding challenges to align math standards, Learning Targets, and Success Criteria for math instruction in the classroom. Attendees will be introduced to block coding using Bee Bots, Ozobots, UBTECH Robotics and autonomous coding with Botball robots to implement math instruction. Bee Bots, Ozobots, and UBTECH robots use block coding to successfully complete challenges with the robots. Botball autonomous robots use C coding language to implement coding challenges. Instructional activities employed in this session include introduction to, and hands on practice, with Bee Bot, Ozobot, and UBTECH robots. The attendees will watch a demonstration of the autonomous Botball robot operating in C coding language before completing a math challenge. Evidence of success will be the attendees creating one Success Criteria, one Learner Target, and one coding challenge aligned with math standards to implement in the classroom.

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Presentation Outline:
5 minutes - Introductions (Peer to Peer)
15 minutes - robotics overview (Interaction)
5 minutes - retrieve state math standards (Device Based)
15 minutes - brainstorm coding challenges aligned to state math standards (Peer to Peer and Device Based)
10 minutes - Develop one Success Criteria and one Learning Target for a coding math challenge implemented in the classroom (Peer to Peer and Device Based)
10 minutes - questions/closing (Peer to Peer)

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Supporting research

Research from Barker et al. (2012) found educational robotics open a door for helping children learn about mathematics and scientific concepts through the practice of inquiry, as well as for developing technological fluency.Educational robotics can provide a learning environment rich with opportunities for using an interdisciplinary approach to integrating many disciplines, such as mathematics, writing and language, technology, science, social studies, dance, music and art (Barker et al., 2012).
Robots provide an open-ended environment for teachers to develop innovative curriculum that integrates technology with different content areas (Bers & Portsmore, 2005). This supports the findings from Ucgul & Cagiltay (2013) who stated in recent years, interest in using robots for educational purposes has increased. 
Literature on manipulatives for elementary math learning has found that the transparent nature of learning materials and direct physical interaction with these materials help build explicit bridges between informal understandings and formal mathematical concepts and symbols (Okita, 2013). Through the robotics curriculum, in C coding language, it is projected that learner outcomes will be increased.
Robotics has been shown to be a superb tool for hands-on learning, not only of robotics itself, but of general topics in science, technology, engineering, and math (Mataric et al. 2007). A fusion of project based learning (PBL) and cooperative learning (CL) will increase learner outcomes. Educational theorists such as Papert (1993) believe that robotics activities have tremendous potential to improve classroom teaching. According to Barreto (2012) educators have started to generate ideas and develop activities to incorporate robotics into the teaching of various subjects, including math, science, and engineering.

Barker, B. S., Nugent, G., Grandgenett, N., & Adamchuk, V. I. (2012). Robots in K-12 Education: A New Technology for Learning (Premier Reference Source) (1st ed.). IGI Global.
Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3), 978–988.
Bers, M. U., & Portsmore, M. (2005). Teaching Partnerships: Early Childhood and Engineering Students Teaching Math and Science Through Robotics. Journal of Science Education and Technology, 14(1), 59–73.
Clements, D.H., & Meredith, J.S. (1993). Research on Logo: Effects and efficacy. Journal of Computing in Childhood Education, 4, 263-290.
Creswell, J. W., & Creswell, D. J. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications, Inc.
Matarić, M. J., Koenig, N., & Feil-Seifer, D. (2007). Materials for enabling hands-on robotics and STEM education. AAAI Spring Symposium on Robots and Robot Venues: Resources for AI Education.
Okita, S. Y. (2013). The relative merits of transparency: Investigating situations that support the use of robotics in developing student learning adaptability across virtual and physical computing platforms. British Journal of Educational Technology, 45(5), 844–862.
Papert, S. (1993). Mindstorms: Children, computers, and powerful ideas (2nd ed.). Basic Books.
Savard, A., & Highfield, K. (2015). Teachers' talk about robotics: Where is the mathematics?. Mathematics Education Research Group of Australasia.
Ucgul, M., & Cagiltay, K. (2013). Design and development issues for educational robotics training camps. International Journal of Technology and Design Education, 24(2), 203–222.
Vollstedt, A., Robinson, M., & Wang, E.L. (2007). Using Robotics to Enhance Science, Technology, Engineering, and Mathematics Curricula.
Yelland, N. (1994). The strategies and interactions of young children in LOGO tasks. Journal of Computer Assisted Learning, 10(1), 33–49.

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Session specifications

Computer science & computational thinking
Grade level:
Skill level:
Attendee devices:
Devices required
Attendee device specification:
Smartphone: Windows
Laptop: PC
Tablet: Windows
Participant accounts, software and other materials:
Attendees should have the following available on their device before the session begins:
BeeBot app
Subject area:
Computer science, Math
ISTE Standards:
For Educators:
  • Advocate for equitable access to educational technology, digital content and learning opportunities to meet the diverse needs of all students.
  • Create learning opportunities that challenge students to use a design process and computational thinking to innovate and solve problems.