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Refining Data Collection and Analysis. EDT 661/665 Summer/Fall 2005. Moving from Proposal to Implementation. Your proposal should guide your research.

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refining data collection and analysis

Refining Data Collection and Analysis

EDT 661/665

Summer/Fall 2005

moving from proposal to implementation
Moving from Proposal to Implementation
  • Your proposal should guide your research.
  • Keep your research question in mind as you implement your research, but remember that your question can change as you collect and analyze data. Keep a record of any changes.
  • Refer to your design frequently, but if the data you are collecting are not giving the information you need, you may make changes. Record in your journal.
data collection and analysis
Data Collection and Analysis
  • As you begin to collect data, you should organize and begin to analyze as soon as possible.
survey data collection
Survey Data Collection
  • Refer to Chapter 13, Creswell.
  • Pay particular attention to format in constructing a survey.
  • Have a peer who is not familiar with your survey instrument respond to your survey.
  • Make sure your questions are constructed to yield the data you want. Be able to state the reason why you are asking each question.
  • You must have draft of survey in your proposal.
survey data analysis
Survey Data Analysis
  • Make a visual representation of how you will organize data from your survey.
  • If you have questions that are closed-response, refer to Analyzing and Interpreting Quantitative Data in Creswell.
  • Data from each respondent will be entered, for each question.
survey continued
  • Each response category must be given a score, or value.
  • See table 8.1 Types of Scores used in Quantitative Analysis
  • SD=1, D=2, N=3, A=4, SA=5

Q1 Q2 Q3 Q4 Q5

J 2 1 3 2 5

M 1 1 4 3 4

survey cont d
  • Another example

Once a week=1

Twice a week=2

Three times a week=3

Four times a week=4

More than four times a week=5

What could be the problems with this example?

survey cont d8
  • Once you have entered the data for all questions, you will analyze depending on the type of scale: categorical or interval.
  • Categorical: Calculate frequencies, or the number (or percentages) of responses in each category
  • Interval: you may either calculate frequencies or the mean response for each question.
survey cont d9
  • Responses to questions that are open.
  • Organize responses by question, preferably in a word document so you can print all responses to one question.
  • You will read all responses to each question to get a sense of patterns and recurring themes.
quantitative data
Quantitative Data
  • If you are recording scores, such as chapter test, quiz, etc., each student score will be entered into spreadsheet.
  • You will likely calculate mean. Each group is the unit of analysis.
  • If you have few students, you may want to consider single-subject design. Each student becomes a unit of analysis.
observation notes
Observation notes
  • Reread H & P p. 36-59. Record observations with enough detail that you could reconstruct what you observed from your notes.
  • Begin notes with date, time, context for observation.
  • Use a ½ sheet method: record on one half of paper. You will note with memos on the other half.
  • Read notes on p. 45, H & P: What do you notice?
  • If you are observing in your study, you must include first draft of observation protocol in your proposal.
observation try it
Observation: try it!
  • Refer to Creswell pp. 214-215. We will complete the activity on p. 215. We will go to KU for the activity.
  • Discussion:
  • Compare your field notes with a partner. What do you notice?
anecdotal records
Anecdotal Records
  • These are a type of note-taking, but are usually specific to student performance in the classroom.
  • Examples: literature conference log, math class observation, class meeting journal.
  • See Fig 3-1, p. 43, H & P
some general reminders about note taking
Some General Reminders About Note Taking
  • The notes you take should not include interpretation. You should write down only what you see, not what you think about it.
  • These are called your raw notes.
  • Remember: detail, detail, detail—the detail is what will make your study come alive and how you will be able to support your conclusions.
  • Be prepared to see and write down those things you don’t expect.
beginning analysis of notes
Beginning Analysis of Notes
  • Read over your notes every day. Begin to ponder what you are reading.
  • This is what H & P refer to as cooking your notes. Refer to H & P pp. 45-57.
  • Try this with your first set of notes and bring to class to share.
student artifacts
Student Artifacts
  • Either copy, photograph, or ask to keep until research is completed.
  • Date the work samples.
  • Your analysis will depend on your question.
  • See Creswell, pp. 205-209; p. 61-63 H & P.
  • It is best to design questions prior to data collection, but remember you must be flexible an open to follow-up.
  • If you are recording, you may either transcribe (very time consuming) or take notes while listening after the interview.
  • Caution: if you are taking notes, be sure that you are not listening for what you want to hear!
  • You must include initial interview protocol with your proposal.
interview data analysis
Interview Data Analysis
  • You should read data after each interview so that you may adjust the questions if you are not getting the data that will help you answer your question.
  • Your interview notes are your raw data; you will cook these data like the examples of observation notes.
reflecting throughout the process
Reflecting Throughout the Process
  • Make sure you are thinking and asking questions throughout the process. Remember that this is an iterative process!