Factors Influencing Student STEM Learning: Self-Efficacy and Outcome Expectancy, 21st Century Skills, and Career Awareness

Jung Han,Todd Kelley,J Geoff Knowles

doi:10.1007/s41979-021-00053-3

Abstract

Social, motivational, and instructional factors impact students’ outcomes in STEM learning and their career paths. Based on prior research and expectancy-value theory, the study further explored how multiple factors affect students in the context of integrated STEM learning. High school STEM teachers participated in summer professional development and taught integrated STEM to students during the following school year, where scientific inquiry, biomimicry, 3D printing technology, and engineering design were integrated as instructional strategies. Surveys were conducted to measure teacher self-efficacy and outcome expectancy. Student STEM attitudes (self-efficacy and expectancy-value beliefs), 21st century skills, STEM career awareness, and STEM knowledge achievement were also measured using a survey and a custom-made knowledge test. Based on expectancy-value theory and literature, a path model was developed and tested to investigate causal relationships between these factors. The results revealed direct and indirect effects of teacher self-efficacy and outcome expectancy on students’ STEM knowledge achievements. Student STEM attitudes (self-efficacy and expectancy-value beliefs), 21st century skills, and STEM career awareness also significantly influenced STEM knowledge achievement directly or indirectly.

Highlights

The national efforts for advancing science, technology, engineering, and mathematics (STEM) education is becoming stronger as our society demands a global STEM workforce (Asunda, 2012; Keirl, 2006; Kelley & Knowles, 2016; Li et al, 2019)
The participating teachers were selected among the applicants following the criteria: (1) The teachers are required to be high school biology or physics teachers or engineering and technology education (ETE) teachers; (2) The teachers are required to be able to participate in the summer professional development (PD)
The test of the path model showed that the model was overall acceptable: χ2 (1) = 23.225, p < .001 ; Comparative Fit Index (CFI) = .940; Incremental Fit Index (IFI) = .942 ; Tucker-Lewis index (TLI) = .70; Root Mean Square Error of Approximation (RMSEA) =

Summary

Introduction

The national efforts for advancing science, technology, engineering, and mathematics (STEM) education is becoming stronger as our society demands a global STEM workforce (Asunda, 2012; Keirl, 2006; Kelley & Knowles, 2016; Li et al, 2019). To help students enhance their achievements in STEM learning, teachers and educators should create appropriate instructional and social learning contexts and develop strategies that positively influence student learning. For this purpose, understanding factors that influence student STEM learning is imperative. Motivational, and instructional factors greatly influence students’ achievements in STEM learning and their future careers. Many studies have investigated the relationships between students’ self-efficacy, motivation, and learning outcomes, few studies were reported on the multiple factors influencing student learning in STEM. The current study examined multiple factors influencing student STEM learning, which include teacher selfefficacy and outcome expectancy, student STEM attitudes (self-efficacy and expectancy-value beliefs), 21st century skills, and STEM career awareness

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Methods

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Discussion

Conclusion