Course Description
An introduction to the conceptual and theoretical foundations of quantitative research methods in student affairs. Provides a holistic view and makes explicit the fundamental assumptions and interests of quantitative research methods in student affairs resulting in students having a deeper understanding and increased competency.
Athena Title
Appl Quant Meth in Stu Affairs
Prerequisite
Permission of department
Semester Course Offered
Offered fall
Grading System
A - F (Traditional)
Course Objectives
Using a situated learning lens, successful engagement in this course will help students develop the following knowledge, skills, and attitudes: Knowledge: Students will articulate the philosophical and practical assumptions of quantitative research. Students will describe how quantitative methods can be used to answer practical research questions including those necessary to create a more racially and socially just and emancipatory world. Students will demonstrate familiarity with when to employ particular statistical methods aligned with theory, measurement, and research questions. Skills: Students will be able to explain the necessity of a research study and how it is connected to a problem that is important to solve. Students will be able to connect the motivation for a study with key constructs present in a theoretical framework. Students will be able to design a quantitative study that answers research questions that follow theoretical guidance. Students will be able to identify sources of data to measure constructs and will be able to identify and connect appropriate statistical methods to the types of data necessary to carry out quantitative research. Attitudes: Students will develop comfort, confidence, and competence with quantitative methods.
Topical Outline
1) Major Aims and Philosophy of Quantitative Research 2) Critical Perspectives in Quantitative Methodology 3) Introducing and Motivating a Study 4) Defining and Describing Quantitative Research Questions 5) Theoretical and Conceptual Frameworks 6) Operationalization: Constructs, Variables, Measures 7) Connecting Theory to Constructs to Measures 8) Reading and Interpreting Quantitative Outputs 9) Data Sources: Primary and Secondary Survey Construction 10) Sampling and Representation 11) Data Analysis: Frequency 12) Data Analysis: Comparing Differences 13) Data Analysis: Correlation 14) Data Analysis: Prediction 15) Data Analysis: Recap 16) Writing and Communicating Results
Syllabus