Modeling Science and Shaping Attitudes: Physical Computational Model and Mentorship in STEM+C Learning

• In Event: AERA Poster Session Saturday 1:45 pm
  In Poster Session: Computer Science Education approaches and techniques in context

Abstract

Integrating modeling and computational thinking (CT) into early education is increasingly urgent in the digital age. This study introduces PCM+M (Physical Computational Model with Mentorship), a novel instructional approach combining hands-on modeling with support from STEM-trained mentors, to enhance STEM+Computing learning in rural southern U.S. elementary schools. We examined the impact of this year-long PCM+M intervention across six instructional units on students’ performance and perceptions. Results show that students generally held positive views of both the STEM+C lessons and mentors. Further, favorable mentor perceptions positively correlated with performance. This work highlights mentorship as a key factor in learning and demonstrates how PCM+M can support equitable, hands-on STEM+C education in under-resourced communities. Future practical and research directions are also discussed.

Authors

• Jiajia Du, Texas A&M University

• Ting Liu, Texas A&M University

• Tanush Yarram, Texas A&M University

• Kirti Sagar Gadde, Texas A&M University

• Rebecca Ward, Texas A&M University

• Rebecca Jean Schlegel, Texas A&M University