Designing Institutional Research Studies

Catalog description

Develop skills to design and execute IR studies using quantitative and qualitative research methods. HIED 830 Designing Institutional Research Studies (3) This course acquaints students with best practices and necessary skills in quantitative and qualitative research design including sampling and basic measurement issues, research methods, survey research, interviews, focus groups, and selecting appropriate statistical tools. Upon completion of this course, students will be able to: 1. Define and explain the following concepts/tools of social science research: The scientific method Theory and its role Constructs and variables Experimental designs Hypotheses and relations Ethical Principles and practices Survey designs and methods Sampling theory and designs Approaches to data collection Quasi-experimental designs Measurement reliability and validity Ex post facto designs Quantitative analytical designs Focus Groups & Interviews Qualitative analytical designs 2. Apply these concepts/tools in designing a study relating to education research or policy analysis; 3. Effectively critique and evaluate both the theoretical bases (if any) and methods of a journal article or report of a piece of research or policy analysis. This course has established start and end dates and includes interaction with other students throughout the course. Use of the course Web site is required (the central area for accessing class notes and postings, e-mail communication, ANGEL, downloading files). The course is structured around learning units, each roughly corresponding to one week of a Penn State semester. Learning units are self-contained and built around a single theme or topic. Each contains an introduction , objectives, reading assignments, professor's content, and learning activities. While it is possible to accelerate or vary the reading and research schedule, the discussion components among peers should adhere roughly to the time frame (the week) within which each Unit is presented. As a pre-requisite for this course, students are expected to: * Know the definition of a "variable" and the distinctions among dependent, independent, and control variables. * Know basic descriptive statistics (e.g., mean, median, variance, standard deviation, percentage distributions), basic inferential statistics (chi-square test of association and goodness-of-fit test, t-tests, one-way analysis of variance, correlations); the concepts underlying ordinary least-dquares (OLS) multiple regression and the basic multiple regression statistics (R2, R2-change, b-weights, and beta weights).