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The impact of technology on workforce development and socio-economic prosperity has made K-12 computing engineering and STEM in general a national educational priority. However, the integration of computing remains obstructed by resources and lack of professional development to support students’ learning. Further challenging is that students’ STEM attitudes and interest do not matriculate with them into higher education. This issue is especially critical for traditionally underrepresented and underserved populations including females, racial/ethnic minority groups, and students of low-socioeconomic status (SES). To help mitigate these challenges, we developed an unplugged (computer-less) computing engineering and robotics lesson composed of three introductory computing concepts, sequencing, debugging, and sensing/ decision- making, using a small robot-arm and tangible programming blocks. Through students’ sequencing of operations, debugging, and executing of complex robotic behavior, we seek to determine if students’ interest or attitudes change toward engineering. Nine one-hour introductory pilot lessons with 148 students, grades 6-10, at two public middle schools, and one summer camp were conducted. For 43% of students, this was their first time participating in an engineering lesson. We measured students’ engineering interest and attitudes through a 15 question pre- and post-lesson survey and calculated aggregate factor scores for interest and attitudes. We found low-SES students’ a priori interests and attitudes tend to be lower and more varied than those of their high-SES peers. These preliminary results suggest that the integration of introductory computing and robotics lessons in low-SES classrooms may help students reach similar levels of engineering interest and attitudes as their high-SES peers.
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This content will become publicly available on April 25, 2026
PhysioBots: Engaging K-12 Students with Physiological Computing and Robotics
The popularity of applications involving physiological sensing (e.g., brain and muscle activity) and robotics has continued to grow in recent years. However, empirical studies evaluating ways to expose K-12 students to physiological computing are limited. To address this gap, we present PhysioBots, an educational tool designed to introduce K-12 students to physiological computing and robotics. We evaluated PhysioBots with 27 high school students between the ages of 15 and 17 to compare the use of physiological (e.g., self-induced changes in brain or muscle activity) and conventional control (e.g., keyboard) of a robot during a STEM education activity. Our preliminary results suggest that PhysioBots may improve students’ self-efficacy and programming confidence. Observations from open-ended survey questions also indicate that PhysioBots may support students in exploring ways to gamify emotional state manipulation. We discuss these findings and offer insights for future STEM education work involving physiological sensing and robotics.
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- Award ID(s):
- 2045561
- PAR ID:
- 10585702
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400713958
- Page Range / eLocation ID:
- 1 to 8
- Format(s):
- Medium: X
- Location:
- Yokohama Japan
- Sponsoring Org:
- National Science Foundation
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