COM 582 Descriptive and Experimental Research in Communication
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Social Science Paper Contents
Cover page - running head
Abstract - watch formatting - give away the ending
Paper itself
Introduction -
- why should we care about this topic?
Literature Review
- synthesizes (not summarizes) the literature
- creates an argument for your study
Rationale: Given . . . in the literature, we need to . . .
Hypothesis or Research Question:
Method - described in enough detail that someone else could replicate your study
- One statement/question (no double barreled statements/questions)
- All variables should be defined either in the literature review or here
- Participants - how many? demographics? how recruited?
- Procedures or instruments -
- describe instruments here- put entire thing in the appendix
- any reliability statistics go here (Scott's pi for Paper Two, Cronbach Alpha for Paper Three, ??? for Paper Four)
- If it will not be obvious, information about data analysis can also go here
- Define and limit the population
- Decide units
- Create categories to code
- Create coding manual
- Train coders
- Sample messages
- Code the messages
- Calculate Scott's pi
- Converge their codes
Steps to analysis:
1. Put converged codes into chi-square table based on variables2. Run chi-square
3. Report chi-square, df, and p value
- Determine variables from H or RQ to be measured by scale or survey questions
- Create scale/survey questions for variables - see information above and linked from syllabus for various kinds of scales
- Add demographic questions of interest
- Be sure instructions are clear to the population of interest
- Be sure you ONLY have questions relevant to the variables under study
Steps to analysis:
1. Determine what type of relationship you are positing: signfiicant differences or correlation (as one variable increases the other increases or decreases)
2. Be sure you have at least interval data for one variable (i.e., scales produce interval data).
3. Run descriptive statistics (some of these may go in the Methods sections)
4. Run Cronbach alpha for scale reliability (this goes in Methods Section)
5. Run t-test or Pearson's r
6. Report descriptive stats, t-test/r with df and p value.
- Determine variables from H or RQ
- What is you independent variable (this variable you will manipulate/change)?
- What is your dependent variable - this variable you will measure?
- How will you control for as many of the sources of threats to internal/external validity as possible (i.e., random assignment, pre- and post-test; Solomon Four design)?
Steps to analysis:
1. Determine what type of relationship you are positing: generally signfiicant differences given different treatment conditions or treatment and control group
2. Be sure you have at least interval data for one variable (i.e., scales produce interval data).
3. Run descriptive statistics (some of these may go in the Methods sections)
4. Run Cronbach alpha for scale reliability if you used a scale (this goes in Methods Section)
5. Run t-test (two groups) or ANOVA (more than two groups).
6. Report descriptive stats, t-test/r with df and p value.
Results - restate and then answer the H or RQ
- State any descriptive statistics - means, standard deviations
- State the analytical statistics
- State what that means for the H or RQ
Discussion
- Restate what you found without using statistics
- Talk about what that means -
- what are the implications of your findings for what we know about the subject?
- how does this fit with the literature you cited earlier?
- Limitations
- What did not work?
- What changes would you make if you were to repeat this?
- Implications for future research
- What research should be done next? Why? (don't brainstorm a list here - these should be a few ideas that are substantially supported).
Conclusion -
- wrap up the paper, not the study
- tie back to introduction, if possible