Data: The Good, the Bad, and the Ugly, Making Sense of It All Dr Data: The Good, the Bad, and the Ugly, Making Sense of It All Dr. Cheryl Burleigh

You may be asking… How do I collect data? Once I have start collecting data, how do I organize the information so that data makes sense later on? Learn tips and tricks of organizing and analyzing data that will make sense for your research study.

Topics Data Collecting Data Recruiting Participants Data…Now What How to Collected Organize Data Interpretation of Data Programs for Data Manipulation Analysis Validation of Data

Data What is data? Used as the basis of reasoning or calculation Data is measured, collected, reported, and analyzed Visualized using graphs, images or other analysis tools   Refers to the fact that some existing information or knowledge is available Represented or coded in some form suitable for better understanding

Data can be in the form of Raw Data (more data) Data can be in the form of Raw collection of numbers or characters before it has been "cleaned" and corrected by researchers Field collected in an environment, generally uncontrolled Experimental context of a scientific investigation by observation and recording

Prior to collecting data, you need to determine your data sources. What types of sources are you planning to use? Primary the researcher is the first person to obtain the data Secondary the researcher obtains the data that has already been collected by other sources, such as data disseminated in a scientific journal

Recruiting Participants Where to find participants Networks: Professional, personal Social Media Workplace Recruiting mechanisms Email Professional Snowball Word of mouth

Collecting Data Surveys Survey Monkey Demographic Open-ended Interviews Face-to-Face Telephone Email Semi-structured, open-ended Tape Recording, Field Notes One-on-One, Focus Groups; Live or virtually

Collecting Data (continued) Observations Can be done during interviews Documents Journal, Personal/Professional/Public Documents, Autobiographies, Biographies Audiovisual Photos, Videos, Film, Websites, Social Media Statistical Professional Snowball

Data….Now What You have collected your data, now what!?! Organize your data Use of tools to help review emerging themes Interpretation of the data

How to Organize Collected Data Find a system that works best for you Google Docs Word Hard Copies Binders, File Folders, File Cabinet Chronological Order Site Based or Organization Based

Programs for Data Manipulation NVivo organize and analyze non-numerical or unstructured data. The software allows users to classify, sort and arrange information; examine relationships in the data; and combine analysis with linking, shaping, searching and modeling. Can be used with various research methodologies 14 day free trial $85 to 114.00/24 months for student Requires practice

Programs for Data Manipulation DeDoose Alternative to NVivo Mixed Methods, Import Articles, Research Notes, Images Collaborative Research Inexpensive Developed from EthnoNotes 30 day free trial $10.95/active month for student Requires practice

Programs for Data Manipulation Using what you may have Word and Excel Word Use ctrl + F to find; Navigation Words Short Phrases Excel Keep tables of data: words, phrases, numerical Translate to visuals Process maps, basic flowchart program, PivotTables

Interpretation of Data Making sense of it all Time to share you findings and draw conclusions from your research data How do you relate the data collected to chapters 4 of you dissertation?

Reading and Noting Emerging Themes Analysis Reading and Noting Emerging Themes Coding: Describing and Classifying Themes Developing and Assessing Interpretations Representing and Visualizing Data Depending on Methodology-Determines the level of detail needed Grounded Theory and Phenomenology most detailed Narrative least structured (Creswell & Poth, 2018)

Analysis (continued) Key Words or Phrases Themes Subthemes Awareness, Connections, Relationships, Empowerment Subthemes Empathy, Compassion, Healthy Relationships Overarching theme Building Bridges: Looking Back, Looking Forward

Data analysis methodologies vary Validation of Data Data analysis methodologies vary Researcher’s Lens: Check the accuracy and use validation strategies (Creswell & Poth, 2018) Triangulation Discovering negative case analysis Clarifying researcher bias or engaging in reflexivity

Validation (continued) Participant’s Lens Member checking or seeking participant feedback Reviewing transcripts for accuracy Prolonged engagement and persistent observation in the field Prior to data collection, familiar with site and participants Collaborating with participants Community based participatory research practices

Validation (continued) Reader’s Lens Enabling external audits Create tracking document at beginning of study detail key decisions; rationale and potential consequences Generating a rich, thick description Review raw data to add further descriptions; ie. Context descriptions Peer review or debriefing of data and research process Colleagues, friends in the role as “devil’s advocate” Keeps the researcher honest

Triangulation Data triangulation, most frequently used Commonly used: method of collecting, classifying and analyzing data using five possible angles of analysis (at least three) in order to maximize the research's objectivity and permit an understanding of the phenomena under investigation as complete as possible Commonly used: Semi-structured Interviews Observations Documents Member checking

QUESTIONS Thank you for attending the workshop!

References Creswell, J.W. & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Thousand Oaks, CA: SAGE Publications, Inc.

Contact Information Dr. Cheryl Burleigh Associate Faculty, College of Humanities and Sciences Lead Faculty Area Chair College of Humanities and Sciences, Mathematics and Science Faculty Supervisor, College of Education Research Fellow-CEITR and Associate Faculty, School of Advanced Studies Certified Advanced Facilitator direct  925.997.0258 email  cburleigh@email.phoenix.edu