Euclides Maluf Meng.
Visitor Professor @Instituto Federal De Educação, Ciência E Tecnologia De Minas Gerais - Ifmg
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WORK HISTORY
Visitor Professor @Instituto Federal De Educação, Ciência E Tecnologia De Minas Gerais - Ifmg
Visitor professor - Graduate College of Education. Taught the course Psychology of Learning and Knowledge for Education students. Designed lectures and assessments covering major learning theories and their classroom applications. Developed course materials, supported student learning, and contributed to curriculum improvement.
EDUCATION
UNIARA
Master of Engineering - MEng, Industrial Engineering
University of Nebraska-Lincoln
Doctor of Philosophy - PhD, Engineering
Morgan State University
Bachelor of Engineering - BE, Industrial Engineering
University of Arizona
Bachelor's degree, Systems Engineering
IFMG CAMPUS BAMBUÍ
Bacharelado em Engenharia, Engenharia de Produção
University of Nebraska-Lincoln
Mixed Methods Research, Educational Statistics and Research Methods
ABOUT EUCLIDES MALUF MENG.
I’m a Ph.D. student in Engineering, specializing in Engineering Education Research at the University of Nebraska–Lincoln, where I serve as a Graduate Research Assistant. My research sits at the intersection of engineering assessment and engineering learning mechanisms, examining how course experiences and assessment practices shape students’ learning, motivation, emotions, and self-efficacy in engineering education. Grounded in Social Cognitive Career Theory (SCCT), Control-Value Theory (CVT), and constructivist perspectives, I study how students engage with engineering and persist in their programs.I specialize in quantitative and mixed-methods research, using surveys, psychometric analysis, and statistical modeling to improve learning experiences and promote educational equity in engineering and STEM.My background combines Industrial Engineering, Education, and Business Administration, with over 10 years of experience teaching and training professionals in technical and higher education settings.I integrate data science, learning analytics, and machine learning to design data-informed strategies using R, Python, SEM, predictive analytics, data mining, SQL/NoSQL, and visualization tools such as Power BI and Tableau. Skilled in data wrangling, data pipelines, and experimental design, I aim to generate actionable insights that advance both research and educational practice.Currently, I contribute to the VADERs Project, applying advanced analytics and educational data to leverage virtual and augmented reality to enhance engagement, self-efficacy, and diversity awareness in Architecture, Engineering, and Construction (AEC) education.Passionate about making education more effective, inclusive, and data-driven, I’m open to collaborations in data science, engineering education, business intelligence, and learning analytics.
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