Atlasti qda software#
This class will briefly review criteria for choosing between different QDA software packages. October 2012: Qualitative Data Analysis Using ATLAS.ti Some familiarity with ATLAS.ti is helpful, but not necessary.Īpril 2013: ATLAS.ti and Other Software Overview for JSIS 511įebruary 2013: Software Workshop for PB AF 525A: Qualitative Methods for Policy & Social Science Class We will practice coding and will explore output functions.
Atlasti qda how to#
interviews in text, audio or video format, images, etc.), how to Copy Bundle your project and other tips for keeping your Hermeneutic Unit (HU) organized. In this class we will review best practices for project management in ATLAS.ti 7, including the My Library option for importing primary documents (i.e. July 2013: ATLAS.ti – Advanced Beginner: Qualitative Data Analysis
Atlasti qda pdf#
Topics covered will include terminology, importing documents, coding, and visual analysis of multiple media formats.ĪTLAS.ti - a PDF of presentation slides from this class. This workshop will be a hands-on introduction to qualitative analysis using ATLAS.ti. This class was a special presentation to students in a qualitative methods course. We will learn best practices for data management, how to backup and share your project file and other tips for staying organized.įebruary 2014: Software Workshop for Qualitative Methods Class We will go over terminology, importing documents, coding data (text and other media types) and visual analysis. This class covers the criteria for choosing a qualitative data analysis software package and includes a hands-on demo of one of those programs: ATLAS.ti 7. The presentation slides are available here.Īpril 2014: Intro to qualitative research using ATLAS.ti Sample data for this class can be accessed here.
Atlasti qda Pc#
We will practice logging into Titus on a PC if you have a MacBook that you prefer to log in from, feel free to bring it. Those interested in this service should register specifically for Part II with their UW Net ID/UW email address. We will practice logging into Titus and CSSCR’s Computer Support Specialist will be available to answer technical questions.
Part II is intended for faculty and researchers in the Social Sciences who are interested in accessing ATLAS.ti (and other data analysis software such as Stata) via CSSCR’s new free service – the remote terminal server Titus. We will practice coding, organizing the data into families, and try several of the basic analysis functions such as networks (visualizing data and codes), various reports and outputs. A hands-on workshop will take up most of Part I – we will create a new project in ATLAS.ti with qualitative data provided by the instructor and featuring interviews, newspaper articles, policy documents, images, and a video. Attendees will review criteria to consider when choosing a QDA software program and learn the features and terminology in ATLAS.ti, a QDA package broadly used in academia. This session is open to all UW students, faculty and staff. Part I: The first hour will be an intro to qualitative data analysis (QDA) using ATLAS.ti. For information on how to access applications through, visit /vdi.August 2015: Intro to qualitative data analysis using ATLAS.ti & demo of CSSCR’s new terminal server, Titus This software is also available through ITS’s virtual desktop interface (VDI),. Click the button below to download this key:įor information on installing and using ATLAS.ti to analyze data, see /atlas-ti
Atlasti qda install#
In order to successfully install ATLAS.ti 8 on either Windows or Mac computers, you will need the USC license key. In order to successfully install ATLAS.ti 9 and 22 on either Windows or Mac computers, you will need to follow the activation instructions accessed through the buttons below:ĭownload License Instructions (Faculty/Staff) ATLAS.ti 22 for Windowsĭownload for Students ATLAS.ti 22 for Macĭownload for Stude nts ATLAS.ti 9 for Windows ATLAS.ti is qualitative data analysis (QDA) software that allows users to locate, code, and annotate findings in text-based and multimedia data and visualize the complex relationships between these data.
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