Courses | Education Leadership Data Analytics | Teachers College, Columbia University

Courses

Leading with Evidence in Schools: Data and Research Literacy

This 4-week, interactive online course is designed to help current or aspiring teachers, school leaders, and district or state leaders enhance their skills and capacity to inform their decisions with valid and reliable forms of data and to select the best forms of assessments and the best practices for their students.

ORLA 5025: Ecology of Data-Driven Leadership

This course relies upon systems theory and its application to school systems. The course teaches prospective leaders the use of databases of various kinds to pursue a systematic inquiry in the health and productivity of the ecology of the school. It explores various approaches to data mining, model building, and ultimately the "art of improvisational leadership." The course teaches students how to distinguish the different purposes for which data can be used and misused and relies heavily on the use of cases, simulations and exercises, including those with complex feedback systems. Familiarity with spreadsheets and simple statistics is helpful.

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ORLA 5530: Action Research in Organizational Behavior

Techniques and methods of designing and conducting action research on organizational problems. Various methodological and organizational issues are addressed regarding the use of action research to foster organizational learning and problem solving through systematic inquiry and reflection. Students conduct an action research project.

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ORLA 6541: Applied Data Science in Organizations and Leadership

This course focuses on the applied aspects of data science in organizations and leadership using open source software, including data visualization and effective communication with organizational stakeholders, pattern and classification analysis, early warning prediction accuracy, unstructured data and text analysis, issues of algorithmic bias and fairness, and emerging topics in applied data science and visualization.

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ORLA 6525: Using Evidence, Data, and Research Methods in Education Leadership

This course helps prepare school system leaders to use evidence, data, and research in their practice as school and district leaders as well as in preparation for doctoral dissertation-level research. In this course students learn how to access, understand, and apply peer-reviewed education research to their practice and in writing literature reviews; apply foundational quantitative, qualitative, and survey research methods to problems of practice in their organizations; and learn how to build, facilitate, and lead collaborative discussions to inform evidence-based improvement cycles around specific organizational instructional goals.

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ORLA 6552: Research, Theory, and Practice in Education Leadership

This course focuses on major theoretical perspectives on administrative leadership in education, how these perspectives are studied and advanced through empirical research, and how the theory and research are connected to leadership practice. Students will examine theory and empirical research on topics such as leadership effects on student learning; challenges in leading learning organizations; and the relationships among leaders' knowledge, skills, and dispositions and their leadership preparation and effectiveness.

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ORLA 6641: Advanced Topics in Research Methods and Design

This course provides students the opportunity to explore advanced topics in research design and analytic methods, especially as they relate to studies of educational contexts and policies. The purpose of ORLA 6641 is for students to be able to apply recent innovations in quantitative methods to their research questions using a public national database of their choice, with the potential outcome of the course being a proposal for a national meeting, such as the annual meeting of the American Association for Educational Research (AERA). Throughout the course we discuss issues of database selection and use, as well as specific recent research methods such as hierarchical linear modeling (HLM), hierarchical growth modeling, survival and discrete-time hazard modeling, and latent class analysis (LCA), as well as how to honestly present visual quantitative information to multiple audiences. Over the past few years many students have taken their final paper from the course and submitted and presented it at AERA, submitted and received grants, as well as turned their projects into full research articles and/or their dissertation.

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