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.

RET Site: Cyber Security Initiative for Nevada Teachers (CSINT), National Science Foundation PI: Shamik Sengupta, co-PI: David Feil-Seifer, Amount: $540,000, Sept. 1, 2015 - Aug. 31, 2018

Center for Integrative Neuroscience: Using Socially Assistive Robot Assistants to Augment NeuroRehabilitation Exercise Therapy, National Institutes of Health (NIH) PI: Michael Webster, co-PI: David Feil-Seifer, Amount: $150,000, Sept. 1, 2017 - May 31, 2018

Robot Problem Solving for Elementary, Middle, and High-School Students: Programming Without Computers, Nevada Space Grant Consortium (NV-SGC) PI: David Feil-Seifer, Amount: $4,889, Feb. 1, 2016 - April 30, 2016