Deeper Learning Opportunities and Expectancy-Value Beliefs in Online STEM Summer Programs

• In Event: Supporting Learning in Online Environments

Abstract

Building on Eccles’ situated expectancy-value (SEVT) theory and deeper learning framework, this study examines the associations between various first-order deeper learning opportunity (DLO) factors and adolescents’ STEM expectancy-value (EV) beliefs in online STEM summer programs. Structural equation modeling results from analyzing the longitudinal data of 737 participants indicated that various cognitive, intrapersonal, and interpersonal DLOs are positively associated with post-program EV beliefs in STEM, after controlling for demographic characteristics and pre-program EV beliefs in STEM. Specifically, opportunities for creative thinking, opportunities for complex problem solving, opportunities to learn how to learn, and opportunities to communicate in the STEM programs are generally positively predictive of STEM expectancy, intrinsic, attainment, and utility values, with varying levels of effect size and statistical significance.

Authors

• Guan Saw, Claremont Graduate University
  Presenting Author

• Ryan Culbertson, Claremont Graduate University
  Presenting Author

• Chi-Ning Chang, Virginia Commonwealth University
  Presenting Author

• Kahlí Hedrick-Romano, Claremont Graduate University
  Presenting Author

• Vicki Lynton, Alamo Colleges - Northwest Vista College
  Presenting Author

• Guillermo Lopez, Claremont Graduate University
  Presenting Author