Exploring the Affordances of Open-Source Sensors in Promoting Authenticity in Mathematics Learning
This chapter describes the considerations of the learner and disciplinary intuitions in teaching science, technology, engineering, and mathematics (STEM). We assert that teachers who possess well-developed STEM pedagogical content knowledge, inquiry-based approach, and the ability to surface learners’ intuitions are well positioned to engage in the process of STEM curriculum design and teaching. We documented an education intervention that incorporated a STEM learning framework based on authentic learning into the Secondary Mathematics 2 curriculum of a Singapore public school. The purpose of the intervention was to promote greater authenticity in students’ learning of mathematical data handling skills, applications, and interests using a real-world learning context and problem involving data collected from open-source sensors. We conclude that a STEM learning framework supported by open-source sensors can be used to create an authentic learning environment, which in turn can leverage learner intuitions and enhance learning.
KeywordsSTEM education Sensors Authentic learning Secondary mathematics education Real-world context Learner intuition Disciplinary intuitions
The authors would like to express their gratitude to the following persons for their invaluable part in this research project: Mdm. Goh Shwu Jun, Mr. Jeremy Chen, and Mdm. Lee Ching Fong from YCKSS for their collaboration and in shaping shared learning, and to Johnervan and Jonathan Lee for their continual encouragement and help throughout the project. The authors acknowledge the funding support for this project from Nanyang Technological University under the Undergraduate Research Experience on CAmpus (URECA) program.
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