Introduction to Journalism Syllabus

Qualitative Data Management, Analysis, and Presentation (“QuaD-MAP”)

ADMPS 3012, Section 1250 /26644

Wednesdays, 4:30 – 7:10 5520 Wesley W Posvar Hall

Fall 2016 (2171)

Dr. Maureen K. Porter, PhD

Office: 5907 Posvar

Phone: 412-648-7041

E-mail:

Office Hours: Monday early afternoons and Wednesdays late mornings.

Direct personal communication, then phone, then mail is my preferred order of contact

Office Hours are by appointment, with additional ones for Lehrstuhl members (advisees), students working on my data sets, and active dissertators.

Course Description

This course introduces software and technologies to efficiently manage, systematically analyze, and effectively present qualitative data of diverse kinds in varied media. Students work in teams with real data in this project-based lab course, from project conceptualization to a final dialogic presentation of results. Technological skills are paired with conceptual discussions of such key operations as coding, thematic analysis, reflexive and analytical notes, framing questions, visualization and conceptualization, evidence claims, team coding, live modeling, and assessing matrices. Class sessions provide opportunities for collegial problem solving and critiques of core readings, data management strategies, skills demonstrations, vocabulary building exercises, and analytical presentations.

Full engagement in the course and all activities is assessed along with sequential completion of 1) written qualitative data analysis sections, 2) data analysis products, 3) oral presentations, and 4) teamwork contributions. The core assignments are directly linked to authentic assessment and provide elements for graduate level comprehensive exams, overviews and proposals, theses and dissertations. Emphasis on expanding students’ repertoires of professional level presentations is an important element of the course.

Contents

This syllabus includes these elements:

Ø Rational and Objectives

Ø Resources

Ø Expectations and Requirements

Ø Policies, Privileges, and Rights

A Course Plan and extensive essential and supplementary Courseweb materials are available to you. Additional course resources (i.e. bibliography and tips folder) will be accessible after add/drop and a final version will be available for download for all students who successfully complete required elements.

Rationale and objectives:

Course Rationale

This is an advanced qualitative research methods course with a focus on developing skills in analyzing, synthesizing, meaning making, and presenting complex qualitative data. Though the course covers some qualitative research concepts, students must have previously taken foundation courses in qualitative research such as Introduction to Research, Introduction to Qualitative Methods, or Field Methods to get a broad orientation to conceptualizing and conducting qualitative research. Specialty, hands-on practica and second level courses in interviewing, statistics, evaluation, focus groups, case studies, rhetoric, multimedia, or other methodologies add to a solid foundation in specific modes of inquiry. This course begins with only a basic review of students’ prior solid grounding in the ethics, principles, and hallmarks of high quality qualitative research. Together we further develop our ability to articulate the basis for evidence claims, especially the underlying strategies of generating qualitative data analysis.

This third-level research class builds upon students’ preliminary experience designing studies and generating data. This course enables students to develop greater knowledge about the iterative analysis and meaning-making cycles of qualitative research. There are several points in the graduate program when this course is most beneficial. One point is when students are getting ready to conceptualize a research project or pilot study. The knowledge and skills that can be gained in this course about what is going to be done with data once it is collected are extremely useful for students when designing qualitative research projects. Another point is when students are in the data collection phase of a research project (their own or a faculty mentor’s). Data management and analysis need not wait till data collection is completed; in fact, beginning analysis while collecting data can inform and strengthen the data gathered. The third point when this course is most useful to students is when they have gathered data on their own or a faculty member’s research project and are ready to delve into analysis. Students who wish to gain formal Supervised Research/Independent Project credit concurrently with enrollment in the course should complete this agreement process with their supervising faculty member.

Though this course benefits students prior to gathering data, and includes the option to use a prepackaged data sample project that comes software, the skills taught in this course are best developed when students bring in actual data that they have previously collected or when they are involved first hand with a data set. Sources for data could include elements of an extensive research literature review, data collected during a dissertation study, data generated as part of supervised research or pilot projects, or data previously assembled as part of fulfilling assignments in another course. Qualitative research methods classes that include data collection as part of the course include: Research Interviewing, Case Study Methods in Education, Field Methods, Meaning-Centered Approaches to Studying Development: Participant Observation, Classroom Discourse, and others. Student insight into other courses that are relevant will help add to the shared knowledge base of the course members.

Students will work in teams of 2-3 throughout the term. This requires that at least one person have data or that both are willing to work with an existing data set from a professor, sponsor, or the practice set available in NVivo. Students who bring their own data into this course find that doing so enhances their learning of the content and skills taught in the class. Students who use their data sets have the opportunity to make significant forward progress in analyzing and conceptualizing their study. They also develop effective ways to organize and manage multiple types of complex data. However, having a data set is not a prerequisite for taking the class. In fact, teammates who do not have assumptions, emotional attachments, or theoretical training with a data set are very helpful partners because of their positioning and new perspectives.

Course learning activities are designed to help all students make accelerated progress in their knowledge and skills in qualitative data management, analysis, and presentation. Many of the enrollees have tried to learn basics of the software on their own, but realize that a team setting in which we move swiftly to advanced skills is the boon that they needed to actually move to the advanced levels of analysis and composition. We start at the beginning and build a solid foundation; we have successfully run this course as with this nested iterative cycle to great student acclaim. Therefore, the first major section of the course uses the practical application of creating a literature “framework matrix” because of the new capabilities available within the NVivo 10 qualitative data analysis computer software. This component now makes this course even more useful for preparing literature reviews for qualitative research project proposals and comprehensive exams.

Course Learning Objectives

Upon completion of this course, students will be able to:

· utilize NVivo 10 qualitative data analysis computer software to facilitate qualitative data management, analysis and (re-)presentation.

· address qualitative data analysis concerns in the data analysis sections of their research studies or proposals using core concepts that they can define and apply

· create presentations that visually communicate relationships and patterns within qualitative data that are supported by easy access back to the original data.

· organize text, image, audio visual, and database data from a multitude of formats in a variety of easily retrievable ways to facilitate pattern exploration and analysis.

· design appropriate analytic queries to apply to their data that provide insights into worthwhile and researchable research questions.

· develop skills needed for effective collaboration on research teams and management of multiple coders on research projects.

· manipulate multiple software such as NVivo 10, EndNote/Mendeley, Adobe Acrobat Pro, Word, Excel, Powerpoint, and others to accomplish research project goals for literature reviews, data management, analysis, and presentation more effectively

· have fun and enjoy the satisfactions of discovery and innovation

· network and create working/writing/lab groups for further progress in graduate work

Resources:

In this course we use texts, software and freeware, and hardware. The list includes received wisdom about what you will need and suggestions for places you can get it, sometimes for free, and sometimes deeply discounted.

Textbooks

Textbooks have been ordered through the Pitt Book Center on Fifth Avenue. They have some in stock and expect the remainder by first weeks of class. Students may acquire, share, or borrow course resources in any legal and ethical manner. Students should explore the range of formats now available and might enjoy the resources in print or electronic format.

Required texts

Collecting and Interpreting Qualitative Materials by Norman K. Denzin, Yvonna S. Lincoln

Third Edition @2008, SAGE Publications ISBN: 9781412957571

Qualitative Data Analysis: Practical Strategies by Pat Bazeley

And/or

Qualitative Data Analysis with Nvivo by Pat Bazeley and Kristi Jackson

The Good, the Bad, and the Data: Shane the Lone Ethnographer’s Basic Guide to Qualitative Data Analysis by Sally Campbell Galman. @ 2013 Walnut Creek, CA: Left Coast Press. ISBN: 978-1-59874-632-7 e-book; 978-1-61132-710-6

Recommended texts

Qualitative Researching with Text, Image and Sound: A Practical Handbook for Social Research by Martin W Bauer and George Gaskell

The Coding Manual for Qualitative Researchers By Johnny Saldana

Third Edition @ 2016 SAGE Publishing ISBN: 978-1473902497

Applied Thematic Analysis by Greg Guest, Kathleen M. MacQueen and Emily E. Namey

Qualitative Interviewing: The Art of Hearing Data by Herbert Rubin and Irene Rubin

Third edition @ 2012 SAGE Publications ISBN: 9781412978378

And highly recommended, but not actually required (APS students may have these from Core or from the First Year Seminar)

Destination Dissertation by Sonja K. Foss and William Waters

And

The Craft of Research by Wayne C. Booth, Gregory G. Colomb & Joseph Williams

When thinking about qualitative data analysis within the framework of a doctoral degree completion process, students may also find these helpful:

The Qualitative Dissertation: A Guide for Students and Faculty by Maria Piantanida and Noreen Garman

and

The Dissertation Journey: A Practical and Comprehensive Guide to Planning, Writing, and Defending Your Dissertation by Carol Roberts

There is a set of NVivo9 user manuals called NVivo9 Basics and NVivo9 Advanced. Although they are from the older version, they still are helpful when you need a detailed set of directions. These are only available through QSR International, who list the set for $105 on their website. I bought a reference set for use only in the computer labs. Look over the copies that are stored in the computer lab or in the tech office.

Any texts you have purchased for other qualitative research courses are certain to be applicable to this course so feel free to pull them off your shelves and use them!

Software and Freeware

More than 100 software packages are available to students at little or no cost. Software can be purchased, downloaded at no cost, as well as used at campus computing labs. For more information, go to: http://technology.pitt.edu/software/for-students-software.html You’ve already paid in the right to access these computing resources, so take advantage of them while you are still a student!

Required software:

NVivo 10 by QSR International is the qualitative data analysis computer software we are using. I am not recommending you purchase this until a) you know more about how to use it and b) you realize you will need it beyond all the ways you have access to it for free. We will discuss in class the many options for getting NVivo at discounted rates. You have free access to NVivo 10 in the SOE computer labs - which has very limited hours of access - and in the U of Pittsburgh computer labs which are open 24/7 in some locations.

EndNote bibliography software is a program we strongly recommend you have and use for managing your bibliographic references. It is available for purchase for $5 though Software Distribution Services, located at 204 Bellefield Hall, open weekdays from 8:30 a.m. to 5:00 p.m. You have free access to EndNote in the SOE and U of Pittsburgh computer labs. You may also wish to use Mendeley instead; there are free workshops (in English and several other languages) offered through Hilman Library. Check out their website for upcoming events.

Acrobat Professional by Adobe is a program for reading and editing PDF documents. Many people have the free version of Adobe Acrobat on their computers to read PDF files. That free version is not Acrobat Professional. Acrobat Professional is available for purchase for $5 though Software Distribution Services, located at 204 Bellefield Hall, open weekdays from 8:30 a.m. to 5:00 p.m. You have free access to Acrobat Professional in the U of Pittsburgh computer labs, and perhaps in the SOE labs. The most important thing is that whichever program version you use needs to be able to generate OCR (optical character recognition) .pdf formatted documents. Check to see when you copy items that the product is an OCR .pdf.

Blackboard in CourseWeb is the University of Pittsburgh's web-based course management system and instructional software package. It is accessed via www.my.pitt.edu with your University of Pittsburgh login. We use this freeware extensively in this course for communication, assignments, and resources.

Word, Excel, PowerPoint by Microsoft are word processing, spreadsheet, and presentation software respectively. Most computers have these and we expect you are all familiar with them. These and much more Microsoft software is available to you for free through Software Distribution Services. You can pick up some of this free software at any U of Pittsburgh computer lab. These include statistics (e.g. SPSS), visualization, drawing, mindmapping,and multimedia software that could prove helpful in the class. You can upload NVivo reports into those other software programs in order to transform and use the data in extended ways.

Recommended software:

Prezi is presentation software that is internet based at www.prezi.com. It allows users to create dynamic visual presentations without the restrictive boundaries of PowerPoint. Though you can purchase a subscription to it, the educator version is free if you register using your Pitt email account. They just posted many more new graphics and templates.