Developments In Stem Educators’ Preparedness For English Language Learners In The United States

In the United States, the population of students classified as English Language Learners (ELLs) in K-12 education has increased in recent decades. As a result, teachers outside of specialized linguistic courses have needed to adapt their instruction to better meet the needs of these students. This exploratory study investigates potential indicators of Science, Technology, Engineering, and Mathematics (STEM) teachers’ preparedness to work with ELLs, in comparison with the rates of ELLs in STEM courses.   Data for this study were obtained from the national restricted-access datasets of the 2007-2008 and 2011-2012 School and Staffing Survey (SASS) Teacher Questionnaire (TQ). STEM teachers’ participation in ELL-focused professional development activities, credentialing related to ELLs, and ELL populations in STEM teachers’ courses were analyzed to quantify changes in these measures over time and among the STEM disciplines. Regional analysis of STEM teacher populations and ELL populations in STEM classes was also conducted to examine how these factors differed across the United States.   Analyses of these data indicated increases in the percentage of STEM teachers who have ELLs in their service loads and in the average number of ELLs in teacher service loads; these trends were present in all U.S. regions and in all STEM disciplines. However, the total number of STEM teachers who participated in ELL-focused professional development activities increased only slightly over the four-year span. To effectively teach the growing ELL student population, STEM teachers must develop the skills and approaches necessary to educate and engage these students

THE ROLE OF SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) EFFICACY FOR COURSE-TAKING AND HIGH SCHOOL GRADUATION OF ENGLISH LANGUAGE LEARNERS

This study examines how Science, Technology, Engineering, and Mathematics (STEM) Education may improve English language learners\u27 academic achievement and high school graduation. In particular, it highlights the plight faced by ELLs in high schools regarding quality education that allows them to graduate on time and attend college. The analysis for this study is grounded on the self-efficacy component of Albert Bandura\u27s Social Cognitive Theory (Bandura, 1977), which focuses on the hypothesis that students are motivated by positive experiences that contributes to their academic success (Hsieh & Kang, 2010). Using Albert Bandura\u27s self-efficacy framework and nationally representative data from the High School Longitudinal Study of 2009 (HSLS:09), this study will analyze: (a) To what extent do ELLs differ from non-English learners in STEM course-taking?; (b) To what extent do ELLs differ from non-English learners in high school graduation? ; (c)To what extent do ELLs differ from non-English learners in STEM efficacy?; (d) To what extent is higher STEM efficacy related to STEM course-taking for ELLs?; and (e) To what extent is higher STEM efficacy related to high school graduation for ELLs? The sample for this study consists of a subset of 546 ELLs. Two independent sample t-tests were performed to compare ELLs and non-English learners\u27 STEM participation and STEM efficacy. A chi-square test of independence will be implemented to compare ELLs and non-English learners\u27 high school graduation. A multivariate linear regression analysis was conducted to explore STEM course-taking predictability related to STEM course-taking efficacy. In addition, a logistic regression analysis will be conducted to investigate the degree to which higher STEM efficacy is related to ELLs\u27 high school graduation. This study is significant because the national graduation rate of ELLs is 69.9 %, compared to 84% for the general student population (U.S. Department of Education, NCES, 2017) (Ku & Brantly, 2020). Ensuring all our students have proper access and equitable opportunities to quality education, including ELLs and ELLs with disabilities, is a matter of social justice. As responsible and ethical leaders, we must be agents of change, ensuring all historically disadvantaged students have equitable opportunities to achieve and access academic excellence

Empowering STEM Education: Navigating Challenges and Embracing Innovations

This article exposes the main arguments of each article published in this issue. In Tara Brabazon's article, the focus is on addressing student attrition in universities, advocating for strategies like universal design and the abundance model to support student success. Lineo Lynnette Tool's study in South African universities explores underrepresented groups in STEM leadership, suggesting that targeted efforts can encourage their ascent, using a mixed-methods approach. Asmera Teshome Negeri and Jeilu Oumar's article from Addis Ababa University investigates the gap between engineering graduate skills and employers' needs in Ethiopia, emphasizing the importance of real labor market skills assessments and practical-oriented teaching. Dominic Patric G. Galdonez's research at the Philippine Science High School-Ilocos Region Campus highlights mixed perceptions of research support and strong motivation among teachers for research-related activities. Khut Sokha and Shimizu Kinya's study establishes a framework for teaching science through an integrated STEM approach (ISTEMA), identifying six elements and exploring the integration of science with engineering and technology in primary and lower secondary education. Ethel Reyes-Chua, et.al., from Paranaque City College, delve into metacognitive strategies employed by college students in the Philippines during the pandemic, emphasizing self-motivation and students' resilience. Sunil Dehipawala, et.al., address challenges in teaching measurement uncertainty in physics lab classes during the Covid-19 pandemic, providing insights into experiential learning and assessment rubrics for remote delivery. Prasart Nuangchalerm & Veena Prachagool's paper discusses the integration of AI in STEM education, analyzing transformative potential of AI-driven learning analytics, highlighting the need for ethical considerations in implementing technological innovations