2 research outputs found

    A Case Study on the Efficacy of STEM Pedagogy in Central New York State: Examining STEM Engagement Gaps Affecting Outcomes for High School Seniors and Post-2007 Educational Leadership Interventions to Reinforce STEM Persistence with Implications of STEM Theoretic Frameworks on Artificial Intelligence / Machine Learning

    Get PDF
    STEM (science, technology, engineering, and mathematics) has gained significant notoriety and momentum in recent years. STEM literacy highlights the vital connection between an educated STEM workforce and U.S. national prosperity and leadership. STEM educational and job placement goals have been a national priority for over the past 20 years. However, the STEM gap is widening—contributing to increasing STEM pipeline leakage and the social injustice milieu of a noncompetitive workforce— undermining efforts to create prosperity and sustain global leadership. The pace of STEM jobs filled lags the rate of technological advancement and the surges in skilled STEM labor demand. The aggregate disparity over time has troubling implications. The purpose of the study was to examine the STEM gap touchpoints for a Central New York high school during the transition period upon entering college or the workforce. A qualitative case study used Lesh’s translation model as a research framework. A semi-structured, focus group protocol was employed to gain a fresh perspective on the STEM gap problem and identify purposeful interventions. A major finding was the slow pace of adopting institutional reforms that replaces standardscompetency-based learning with progressive application- and outcome-based pedagogy. The study has implications for school districts, secondary schools, and higher education teacher preparedness programs in STEM pedagogy and curriculum development. A knowledge-based, progressive STEM theoretic framework with pedagogical scaffolding is conceptualized rooted in artificial intelligence and machine learning. The study presents recommendations for school districts, secondary education teachers, state education and legislative leaders, higher education institutions, and future research

    A Case Study on the Efficacy of STEM Pedagogy in Central New York State: Examining STEM Engagement Gaps Affecting Outcomes for High School Seniors and Post-2007 Educational Leadership Interventions to Reinforce STEM Persistence with Implications of STEM Theoretic Frameworks on Artificial Intelligence / Machine Learning

    No full text
    STEM (science, technology, engineering, and mathematics) has gained significant notoriety and momentum in recent years. STEM literacy highlights the vital connection between an educated STEM workforce and U.S. national prosperity and leadership. STEM educational and job placement goals have been a national priority for over the past 20 years. However, the STEM gap is widening—contributing to increasing STEM pipeline leakage and the social injustice milieu of a noncompetitive workforce— undermining efforts to create prosperity and sustain global leadership. The pace of STEM jobs filled lags the rate of technological advancement and the surges in skilled STEM labor demand. The aggregate disparity over time has troubling implications. The purpose of the study was to examine the STEM gap touchpoints for a Central New York high school during the transition period upon entering college or the workforce. A qualitative case study used Lesh’s translation model as a research framework. A semi-structured, focus group protocol was employed to gain a fresh perspective on the STEM gap problem and identify purposeful interventions. A major finding was the slow pace of adopting institutional reforms that replaces standardscompetency-based learning with progressive application- and outcome-based pedagogy. The study has implications for school districts, secondary schools, and higher education teacher preparedness programs in STEM pedagogy and curriculum development. A knowledge-based, progressive STEM theoretic framework with pedagogical scaffolding is conceptualized rooted in artificial intelligence and machine learning. The study presents recommendations for school districts, secondary education teachers, state education and legislative leaders, higher education institutions, and future research
    corecore