This course provides students with the necessary blend of theory, best practice, and authentic problems of practice in leadership. The course provides a bridge between their thought in other courses and the practicalities involved as they prepare for the administrative leadership selection process and their first leadership assignment. Students learn how to use personal assessment tools and feedback to construct Individual Development Plans.

This module will investigate the current legal, moral, and instructional impact of special education policies in the Commonwealth of Virginia and across the nation. Response to Intervention concepts will be explored in-depth.

Research Ethics/Responsible Conduct of Research fulfills both the National Science Foundation and National Institutes of Health Responsible Conduct of Research (RCR) Mandate. The course is case-based and practical. The goal is to have course participants grapple with complex research integrity concerns, especially through cases, and to take away important points from each session as well as where to turn for more information.

This is the required course for the graduate Certificate in Digital Humanities. It entails participation in colloquia, sixty hours of experience participating in a research project uniting computation and humanities, and a portfolio.

Students will learn theoretical and practical foundations of computational methods for analysis of experimental data from various biological data types. Course will cover algorithms, statistical and computational methods, and application areas in computational biology, and will include both classical methods as well as recent advances. Prior coursework/experience in linear algebra, UNIX, and R & Python programming required.

Students will learn theoretical and practical foundations of computational methods for analysis of experimental data from various biological data types. Course will cover algorithms, statistical and computational methods, and application areas in computational biology, and will include both classical methods as well as recent advances. Prior coursework/experience in linear algebra, UNIX, and R & Python programming required.

Where do our educational practices come from? This seminar invites graduate students to explore theories and philosophies of education in order to guide their own professional development and practices as educators. We will examine topics such as psychological and social development, human rights, social justice, and civic engagement in order to determine what it means to be effective educators in 21st century institutions of higher education.

Students will learn algorithms and applications of computational methods for analysis of experimental data from genome, epigenome, and transcriptome sequencing experiments. The course will cover various biological data types (whole genome sequencing, ChIP-seq, ATAC-seq, RNA-seq, and DNA methylation profiling/bisulfite sequencing), algorithms, statistical and computational methods, and application areas in genomics and systems biology. 

This course will cover fundamental topics in statistical genetics with a focus on concepts and methods critical to a concrete understanding of the application of statistical genetics to public health genomics. Major topics covered in this course include modes of genetic inheritance, heritability analysis, linkage and association mapping, integrative analysis leveraging molecular 'omics' data, and genetic risk prediction modeling.

This course provides the opportunity to offer a new topic in the subject area of academic, professional, and creative writing. For more details on this class, please visit the department website at http://www.engl.virginia.edu/courses.