This week in EDCI 515 we are exploring the concept of quantitative data collection for research purposes. Some examples of quantitative data collection that could be used for research are: statistics, sampling strategies, questionnaires, and surveys. The importance of quantitative data collection allows for development of a solid conclusion to a question based on numerical findings.

See below for difference between Qualitative and Quantitative research.

Qualitative Inquiry Quantitative Inquiry
Goals
  • seeks to build an understanding of phenomena (i.e. human behaviour, cultural or social organization)
  • often focused on meaning (i.e. how do people make sense of their lives, experiences, and their understanding of the world?)
  • may be descriptive: the research describes complex phenomena such as: social or cultural dynamics, individual perception
  • seeks explanation or causation

 
Research
Question
  • Qualitative inquiry is often used for exploratory questions, such as How? or Why? questions.

Examples:

  • How do breast cancer survivors adapt to their post-mastectomy body?
  • How is bereavement experienced differently by mothers and fathers?
  • Quantitative research aims to be more conclusive and pertain to larger populations, answering questions such as What? When? Where?

Examples:

  • When should women have their first mammogram?
  • What is the relation between bereavement and clinical depression?
Data
  • may be comprised of words, behaviors, images
  • the goal is data that can enhance the understanding of a phenomenon
  • can be manipulated numerically
  • the goal is precise, objective, measurable data that can be analyzed with statistical procedures
Design
  • Because the goal is exploratory, the researcher often may only know roughly what they are looking for. Thus, the design of the project may evolve as the project is in progress in order to ensure the flexibility needed to provide a thorough understanding of the phenomenon in question
  • A central tenet of quantitative research is the strictly controlled research design in which researchers clearly specify in advance which data they will measure, and the procedure that will be used to obtain the data
Data collection
Instruments
  • researchers are themselves instruments for data collection, via methods such as in-depth interviewing or participant observation. Data are thus mediated through a human instrument
  • date often collected ‘in the field’: the researcher observes or records behavior or interviews the participants in their natural setting (e.g. a clinic, the family home)
  • tools are employed to collect numerical data (e.g., surveys, questionnaires or equipment)
  • research environment is often a controlled representation of reality
Informant Selection
  • usually collected from small non-random samples (e.g., purposive samples, convenience samples, snow-balled samples)
  • not ‘measurable’ in a quantifiable or mathematical way
  • the aim is ensure that a sample is representative of the population from which it is drawn
  • gold standard is a random sample
Analyis
  • often inductive: the researcher builds abstractions, concepts, hypotheses, and theories from the data gathered
  • often relies on the categorization of data (words, phrases, concepts) into patterns
  • sometimes this data will then be embedded in larger cultural or social observations and analyses
  • Often complexity and a plurality of voices is sought
  • often deductive: precise measurement, mathematical formula, testing hypotheses

 

 
Results
  • The goal of qualitative research is to understand participants’ own perspectives as embedded in their social context
  • contextually based and thus do not seek generalizability in the same sense as quantitative research
  • Goal is prediction, generalizability, causality

 

For our EDCI 568 course, we were looking at a quantitative research paper on “Twitter Use and its Effects on Student Perception of Instructor Credibility” by DeGroot, Young, & VanSlette (2015). Some of the findings from this study are mentioned below.

Question(s)

RQ1: Is the type of instructor Twitter use (social, professional, or a blend of the two) associated with student perceptions of instructor credibility?

RQ2: Above and beyond the content in the Twitterfeed, do perceptions of instructor credibility differ based on whether students believe it is a good idea or a bad idea for an instructor to use Twitter?

RQ3: Does student use of Twitter (ie., frequency, use of Twitter for social versus professional use) change the association between the profile content and perceptions of instructor credibility?

RQ4: How do students describe the potential positive and negative effects of an instructor using Twitter?

Process of Research

  • Researchers used both quantitative and qualitative methods to examine perceived differences in instructor credibility based on the content of hypothetical instructors’ Twitterfeeds
  • Participants were asked to gauge their own social and professional Twitter use by answering two questions on a continuum (completely social –> completely professional)*sliding response scale
  • Three hypothetical instructor Twitter accounts were created (1) an account with only social tweets, (2) an account with tweets of only academic and professional messages, and (3) an equal blend of the tweets from the social and professional tweets (social = personal life [16 total], professional = relevant to professors teaching and research [16 total], blend = alternating social and professional [22 total]
  • Names and profile photos on the accounts were all female, shared the same name, and were purposefully generic
  • Quantitative Measurement
    • Assessed using the Source Credibility Measure (McCroskey & Teven, 1999; Teven & McCroskey, 1997)
    • 3 separate subscales: competence, goodwill/caring, and trust
    • Each subscale included 6  bipolar adjectives with a 7-point response *reverse scored
    • reflect on reasons why it would be a good idea and a bad idea for their instructors to have a Twitter account (responses given)
  • Qualitative Measurement
    • Open ended questions regarding the students perception of the instructors
    • Comments were thematically analyzed

Participants

  • Were recruited by the researching posting calls (out to university Blackboard sites and on social media sites – Facebook and Twitter)
    • 239 individuals
    • Criteria:
      • Current college students
      • Twitter user (Average = user for 2.6 years)
      • Between 18-89 years old (Average = 20.5 years old)
      • 65.7% female
      • Primarily Caucasian (76.6%), 12.6% African American, 6.3% Asian, 2.5% Hispanic, 2.1% Multiracial, 1.3% American Indian
      • Range of academic majors and distributed across years of education

Results

Quantitative

  • Participants rated the professional Twitterfeed significantly more credible than the social Twitterfeed and the professional Twitterfeed was also marginally more credible than the blended Twitterfeed
  • Students rated the blended Twitterfeed as significantly more credible than the social Twitterfeed

Qualitative

  • Organized into themes
  • “It keeps the students connected with the professor”
  • “Extending the classroom”
  • “Improving student-instructor relationships”
  • “Metalearning”
  • “Student/teacher relationships should not go much further than the classroom”
  • “Violating classroom and time expectations”
  • “Breaching the student-instructor boundary”

My perspective – I agree with the general result of this study. I think Twitter has a particular advantage because of the way that the platform is set up (can follow, be followed, limited characters, can repost, and comment) for academic purposes. As  Wasin Ahmed writes in his recent article, “Using Twitter as a data source: an overview of social media research tools” , that “Twitter remains the most popular platform for academic research.” As opposed to Instagram, Facebook, and Snapchat – where they are geared towards people sharing their own personal experiences, instead of ideas.  By looking at what people post, you can make generalizations about someones professional credibility as well as pull data to gather information on a topic. I appreciate Dr. Valerie Irvine’s presence on Twitter as she not only shares information and research connected to what we are discussing in class, but also connecting us to other people to develop our Personal Learning Network, and engaging in conversation with peers in the field.

When comparing the outcomes for quantitative versus qualitative data collection for research purposes, I think that most of the information I will be collecting in relation to my area of interest will be qualitative. I am interested in the use of technology in the elementary classroom; which was excellent to hear ideas and suggestions from Alec Couros today such as digital sleuthing, targeted ads, and the use of Twitter templates before going online!

However, I could see benefits from researching quantitative data about how the use of technology and social media platforms improve information acquisition for students. This could be done through a questionnaire/survey in combination with a pre and post test on a random topic to see if it improved their understanding.