TY - GEN
T1 - Understanding Multidimensional Concepts through Game-Based Learning in the K-12 Curriculum
AU - Samaras, Ted
AU - Herbert, Katherine G.
AU - Anu, Vaibhav K.
AU - Hagiwara, Sumi
AU - Goldstein, Rebecca
AU - Robila, Stefan A.
AU - Wang, Jason T.L.
AU - Oria, Vincent
AU - Marlowe, Thomas J.
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Spaces of dimension higher than three occur regularly in computing and data science (CADS), in linear algebra and statistics, and in modern physics. But the concept of higher dimensions can be confusing, especially for middle school students. They spend many hours in their mathematics, science, and art classes discussing the concepts of Two Dimensional (2D) and Three Dimensional (3D) spaces, but when they are introduced to multidimensional applications in CADS, the concept of higher dimensionality is not understood with ease. Introducing the concept in a hands-on, game-based way can help students begin to understand its application, and support acquisition of further concepts, such as dimensional redundancy. We here propose that as students are provided with more relatable experiences in their academic careers, they will be able to break through the unintentionally constructed constraints of their early learning. We have chosen to leverage the subject of space weather because of the number of dimensions in the available large data sets, and because its topical and futuristic nature allows for extended thinking. Students can then bring greater confidence and efficiency to CADS and other subjects when working with larger data sets and establishing machine learning protocols in their work.
AB - Spaces of dimension higher than three occur regularly in computing and data science (CADS), in linear algebra and statistics, and in modern physics. But the concept of higher dimensions can be confusing, especially for middle school students. They spend many hours in their mathematics, science, and art classes discussing the concepts of Two Dimensional (2D) and Three Dimensional (3D) spaces, but when they are introduced to multidimensional applications in CADS, the concept of higher dimensionality is not understood with ease. Introducing the concept in a hands-on, game-based way can help students begin to understand its application, and support acquisition of further concepts, such as dimensional redundancy. We here propose that as students are provided with more relatable experiences in their academic careers, they will be able to break through the unintentionally constructed constraints of their early learning. We have chosen to leverage the subject of space weather because of the number of dimensions in the available large data sets, and because its topical and futuristic nature allows for extended thinking. Students can then bring greater confidence and efficiency to CADS and other subjects when working with larger data sets and establishing machine learning protocols in their work.
KW - - Computer and Data Science
KW - Education
KW - Game-Based Learning
KW - Multidimensional
KW - Neural Networks
UR - https://www.scopus.com/pages/publications/105017595265
U2 - 10.1109/ISEC64801.2025.11147388
DO - 10.1109/ISEC64801.2025.11147388
M3 - Conference contribution
AN - SCOPUS:105017595265
T3 - 2025 15th IEEE Integrated STEM Education Conference, ISEC 2025
BT - 2025 15th IEEE Integrated STEM Education Conference, ISEC 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE Integrated STEM Education Conference, ISEC 2025
Y2 - 15 March 2025
ER -