Qualitative Data Analysis: The Basics

This event has been changed to an online format, covering the basics of qualitative data analysis. Participants will learn building block techniques, such as theme identification and codebook development, which can be used across many analytic traditions. The course takes a hands-on approach, and uses both lectures and activities where participants analyze real data. While the emphasis is on building conceptual and methodological expertise, participants will also learn how to use text analysis software.

Spring 2019 - Graduate Student Poster Contest Winners

Introduction to Multilevel Modeling (Online Workshop)

Limited to 25 participants

Workshop Description

Course Proposal Support

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Communication - Sample Plan - 18 Credit Hours

Required Course - STP 533, POS 604 - Choose One

Electives:

COM 608 - Multivariate Stat Analysis Data Comm

MGT 791 - Seminar: Qualitative Research

EDP 502 - Introduction to Data Analysis

COM 691 - Seminar: Applied Experimental Design

GCU 593 - Applied Project

Criminal Justice - Sample Plan - 18 Credit Hours

Required Course - STP 533, POS 604 - Choose One

Electives Option 1:

A Socio-legal Biography of Nanotechnologies, 1994-2014

Michael Bennett, School for the Future of Innovation in Society

Engaging College Students in Analyzing Human Papillomavirus (HPV) Vaccine Messages on YouTube and Developing Public Health Education

Angela Chen, College of Nursing and Health Innovation

Inclusive Innovation in the Age of Big Data and the Internet of Things

Pauline Cheong, The Hugh Downs School of Human Communication

Video can capture a subtle, multi-layered record of situations and environments we observe and study. It captures not only what is said but how it is said, actions and reactions, the appearance of the environment and individuals and how they interact, and so much more.  This workshop will focus on techniques for analyzing video and audio data in all of its nuance and richness.

Best Practices for allocation of prize money for collaborative research posters with multiple student authors.

All ISSR prize money should be allocated to students, not faculty or staff.

On posters in which the study design, data collection, data analysis, and poster preparation was completed by a student first-author, ISSR recommends that the bulk of the prize money should go to the first-author student.

Please bring your laptops for this hands-on, full day workshop on Social Network Analysis.