Courses | MS in Higher Education Administration Data, Strategy, and Innovation | UOnline

This course introduces students to techniques of data analysis and statistical inference based on the General Linear Model (GLM). The major topics covered in this class include simple/multiple regression, one- and two-way Analysis of Variance (ANOVA) followed by multiple comparisons, Analysis of Covariance (ANCOVA), and Repeated Measures ANOVA. This course aims to provide a solid conceptual background of these topics, as well as the analytic skills for conducting educational and psychological research in practice. Knowledge of basic algebra and SPSS is required, as is an understanding of the fundamental principles of descriptive statistics and hypothesis testing. Knowledge of calculus is not required. Students will conduct statistical analyses using real datasets.

An overview of the history, nature, characteristics, strategies, and ethics of qualitative research methods. Critical analysis and evaluation of various types of qualitative studies, including design, sampling, processes of data collection and analysis, and reporting results.

Review of emerging quantitative methodological advances relevant to educational research. Allow for experimental instructional formats.

Provides an overview of selected topics in governance, administrative leadership and finance in higher education.

Emphasis on student growth and development during college and an analysis of the factors which affect development along cognitive and affective dimensions. An in-depth examination of college student development theories is included.

Comprehensive overview of principles and practices of a strategic process that begins with recruitment and continues through graduation.

Study in special interest areas in education.

Study in special interest areas in education.

Study in special interest areas in higher education.

This course will cover data analysis and presentation. More information to come.