Data-Driven Education Insights

Book Review 1 Rosenbaum, P. R. (2023). Causal Inference (2nd ed.) . The MIT Press.  Buy the book here: https://mitpress.mit.edu/9780262545198/causal-inference/    In the second edition of "Causal Inference," Paul R. Rosenbaum presents a multidimensional examination of determining causation amidst confounded observational studies. Published by The MIT Press, the 203-page volume expounds on philosophical and technical intricacies in nine meticulously crafted chapters. Through an expert navigation between statistical concepts and applied contexts, Rosenbaum makes an indelible case for precise methodology in cementing credible causal claims from non-experimental data. The initial chapters outline the foundational function of randomized controlled trials (RCTs), where calculated randomization in treatment assignment balances unobserved biases. This sets up the central argument – that observational analyses, despite lacking controlled randomization, can accurately estimate treatmen

Education Matters: 21st Century Teaching : Your continual engagement in our series, “Education Matters”, fills me with deep gratitude. I appreciate your time, encouragement, and most importantly, your willingness to reflect on these pivotal educational matters. As we progress, this article explores the urgency for empathetic teaching, student involvement in decision-making, interactive classrooms, critical and creative thinking skills, and the seamless integration of reading and writing across all subjects.  To Begin with Education systems around the world are evolving to meet the demands of the 21st century. With rapid advances in science and technology, there is a growing emphasis on multifaceted competencies beyond traditional academic...

Welcome to the inaugural article of “Education Matters”, a thought-provoking series that sheds light on the pressing issues within Nepal’s educational system while fostering a spirit of positive transformation. In this first installment, I provide an overview of the current state of education in Nepal, examining the general problems faced by the system. I also delve into the experiences of individuals who have pursued education abroad, exploring their struggles in utilizing their Nepalese education and credentials effectively. As I embark on this enlightening journey, I invite you to join me in uncovering the concerns within Nepal’s education system and inspiring meaningful change. Together, we can ensure that education truly matters, empowering every Nepalese child with the quality education they deserve.   Education as a Fundamental Right The right to education, including quality education, is enshrined in both international and national frameworks. Article 26 of the Universal Declar

  AUTHOR AFFILIATION Nirmal Ghimire, Ph.D.   K-16 Literacy Center at University of Texas at Tyler PUBLISHED May 19, 2023 Introduction Multiple Correspondence Analysis (MCA) is a multivariate statistical technique that is used to analyze the relationships between categorical variables. It is a generalization of correspondence analysis (CA), which is used to analyze the relationships between two categorical variables. MCA can be used to explore the associations between multiple categorical variables simultaneously. MCA works by creating a map of the categorical variables. The map is created by calculating the distances between the different categories of the variables. The closer two categories are on the map, the more similar they are. The further apart two categories are on the map, the less similar they are. MCA can be used to explore a variety of research questions. For example, MCA can be used to: Explore the relationships between different demographic variables, such as age, gender