Business Administration: Business Ethics Syllabus

BA 476 - Business Ethics and BA 576 - Business Ethics

Provides a value analysis of the role of business and personal ethics in the organizational environment. Students are exposed to ethical theories, diverse economic systems, contemporary moral issues, actual cases, and concepts of justice and social responsibility. Open to non-admitted business students and to non-business majors.

This is an updated version. Introduction to Lifespan Development (Fall 2019)
Lifespan Development examines the physical, cognitive, and socioemotional changes that occur throughout a lifetime. This course covers the essentials in understanding human development, psychological research, and theories of growth and development. Students will come to understand the lifespan perspective and to analyze growth through each of the major stages of development: prenatal development, infancy, early childhood, middle childhood, adolescence, early adulthood (including emerging adulthood), middle adulthood, and late adulthood. The course covers key topics in each of these stages, including major developmental theories, genetics, attachment, education, learning, disabilities, parenting, family life, moral development, illnesses, aging, generativity, and attitudes towards death and dying.

Faculty members may readily adapt the course’s OER content to include new developments and research to equip students with what they need to have success in their sociological journey.

Contributors
This course, based on Lifespan Psychology by Laura Overstreet, includes additional material from the Noba Project, OpenStax Psychology, and additional noteworthy contributions by the Lumen Learning team and:

Sarah Carter
Margaret Clark-Plaskie
Daniel Dickman
Tera Jones
Julie Lazzara
Stephanie Loalada
John R. Mather
Sonja Ann Miller
Nancee Ott
Jessica Traylor

This lesson in part of Software Carpentry workshop and teach novice programmers to write modular code and best practices for using R for data analysis. an introduction to R for non-programmers using gapminder data The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation. Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. The lesson contains more material than can be taught in a day. The instructor notes page has some suggested lesson plans suitable for a one or half day workshop. A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability.