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Comm 88 Week 8 Notes - Mullin


Comm 88 Week 8 Notes - Mullin Comm. 88

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All lecture and section notes from week 8 of Comm. 88 Research Methods with Professor Mullin
Communication Research Methods
Dolly Mullin
Class Notes
UCSB, communication, Comm88, Research Methodologies, Mullin
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This 5 page Class Notes was uploaded by on Saturday May 21, 2016. The Class Notes belongs to Comm. 88 at University of California Santa Barbara taught by Dolly Mullin in Spring 2016. Since its upload, it has received 19 views. For similar materials see Communication Research Methods in Communication Studies at University of California Santa Barbara.

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Date Created: 05/21/16
Tuesday, May 17, 2016 Week 8 Lecture 15 - May 17, 2016 - Experimental Research Key elements • - Manipulation and random assignment - Internal validity • Threats to internal validity - Not a true experiment - Not random assignment - Pre-experiments: some manipulation of IV, no RA, many threats to internal validity • One-shot case study - X O1(Group 1) • Observe one group with no control group and make assumptions - Ex: Effects of smiling on others - X(Smile at people) O1(# of smiles received) - Possible alternative explanations for data • One-group pre-test post-test design - O1(# of smiles) X(smile at people) O2 (# of smiles again) - Possible alternative explanations for data - O1(# of accidents) X(new stop sign) O2(# of accidents after) • Static Group Comparison - Post-test only with nonequivalent rout - X O1(group 1) - smile at some people O2(group 2) - no smiling 1 Tuesday, May 17, 2016 • Alternative explanations - Selection Bias: some groups will just react differently to some stimuli - History Effect: outside influences on your study (i.e. ice cream truck shows up so kids are smiling more) - Reactivity Effects: people’s reaction to being in a study —> Hawthorne Effect: productivity rates with different lighting, but participants actually had higher productivity just because the participants knew they were being watched. Productivity decreased when participants realized they weren’t being observed - Placebo Affect: people respond based on what they think the outcome is - Demand Characteristics - To remove these threats, conduct a true experiment - Threats related to pretesting (or measures over time) • Testing affect: people know they’re being tested so they change behavior for second test • Maturation: people mature/change/fluctuate opinions and ideas between pretest and posttest - Can be a seasonal fluctuation; people are happier during holidays and smile more • Statistical Regression - People at extreme hi/low end of spectrum will be less extreme the second time you test them • You get a low score on SAT and then improve • Instrumentation - If you change your scale from time 1 to time 2 Lecture 16 - May 19, 2016 - Experimental Research 2 Tuesday, May 17, 2016 • Threats to Internal Validity - Happen if you don’t have a true experiment - Selection bias - History effect - Reactivity effects • How to control/remove threats - Conduct a true experiment - Random assignment - Treat groups equally • Threats to pre-testing - Testing effect - Maturation - Statistical regression (to the mean) - Instrumentation - Mortality - people dropping out of experiment from time 1 to time 2 - Experimenter effect/bias • Experimenters behavior of attributes rather than treatment of IV, influences DV - How to control this? • Perform a true experiment • Use a double-blind: experimenter doesn’t know who groups are separated • Use a script for what you tell your participants • Quasi Experiments - When you can’t do random assignment, but try to make up for it - Nonequivalent Control Group Design • O1 X O2 (group 1) O3 O4 (group 2) 3 Tuesday, May 17, 2016 - Use pretest scores to match groups before manipulation • If your testing the effect of something on first grade reading level, use a pretest to compare their scores • You find quasi equivalent groups - Time Series designs • Track many observations over time, before and after manipulation - O1 O2 O3 O4 X O5 O6 O7 O8 (group 1) - Single-group interrupted series design - Multiple time series design - O1 O2 O3 O4 X O5 O6 O7 O8 (group 1) - O9 O10 O11 O12 O13 O14 O15 O16 (group 2) • Give comparison group treatment and keep measuring Section - May 19, 2016 - Discussion of Research Paper • Focus on the discussion section - the results are not so much what is important, mores to make sure we understand what we did and how we did it/what we could have done - Intro: why you are doing the study you are doing, setting up the story in a way that allows the reader to wade in - Literature Review Section: right after introduction, before method • Explain what each study actually is • What the study did to find the results, what the results were, and how it is important/relates to our study and hypotheses - Include hypothesis after each lit. review of the related studies (hypotheses are in lit. review) - “Given this literature, our hypothesis…” 4 Tuesday, May 17, 2016 • H1: Blah blah blah blah the hypotheses should be indented and bold, easy to find/read - Do not need an abstract - IMPORTANT: Paper template is posted on GauchoSpace! - A sample of UCSB undergrads (N=#) - DO NOT use the term “significant” unless you used statistics to analyze your data • Can use “meaningful” • Discussion section is THE MOST IMPORTANT! Relate my findings back to the literature - Mentions the strengths too, not just the weaknesses of the study (ex: we operationalized this variable very well) • Weaknesses: what we did and why is was bad? Go beyond “we used a convenient sample”, also talk about my specific study and what could have been done better and how it could have been made better AND then say what the outcome could have been Conclusion: what were the findings and why it is important to the discipline? • Followed by references page (References is NOT bolded) • Attach survey/questionnaire to paper 5


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