Weekly Paper Topics psy230 / Bizer / Fall xxarticles are available at idol.union.edu/bizerg/readings230xx

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1 Weekly Paper Topics psy230 / Bizer / Fall 2018 xxarticles are available at idol.union.edu/bizerg/readings230xx One question is listed below for each of the eight articles assigned for the term. You ll submit a minimum of five papers over the term, but you may submit as many as you want. If you submit more than five, only the five highest-scoring papers will count toward your final grade in the class. Each paper is worth 20 points (15 points for content; 5 points for clarity and style of writing). Please note: Papers should be no longer than two pages, double spaced, one-inch margins, 12-point standard typeface. Papers that exceed this limit or use small fonts will not receive full credit. There is no minimum length requirement, though, so be efficient and succinct! Short and concise is better than wordy and bloated! A printed or hand-drawn graph should be attached as a third page. Don t worry about making the graph look pretty. As long as it s legible, it s fine. Be sure to answer each part of the question. No points will be awarded for presenting other information. For example, don t waste words summarizing the article! Paper copies are due at the beginning of class on Fridays. ed papers will not be accepted, and extensions will not be granted due to misbehaving printers. Article 1: Jia et al. (2018) Last week, we discussed how our lives are impacted by the social world around us. At Union, each of you is aware of the social world on campus, and the tug-of-war that exists between the motivation to be academically successful and the motivation to have fun. Jia et al. (2018) presented a variety of studies exploring the association between academics and big-time collegiate sports. They showed that low-gpa and high-gpa students at Indiana University were equally likely to report watching IU basketball games. But they did so using different strategies. For your study, imagine that you will largely replicate Study 1: You ll ask students how likely it is that they would watch a game during a high-conflict week and then how likely they would watch a game during a low-conflict week. There will be three differences, though. First, you ll use Union College students (instead of IU students). Second, the sport will be men s hockey (instead of men s basketball). Third, you ll compare first-year students with seniors. 1. Describe the method. This is a correlational study: You ll be comparing first-year students with seniors in terms of how likely they will watch Union men s hockey games during high-conflict or lowconflict weeks. 2. Describe your hypothesized results, both with words and with a graph. The graph should look something like Figure 1, except the left panel should represent first-year students, while the right panel should represent seniors. You should present results that demonstrate one of the following: (a) first-year students show greater sensitivity to opportunity, (b) seniors show greater sensitivity to opportunity, or 1

2 (c) there is no difference between seniors and first-year students. Make sure that your description of the results clearly and explicitly corresponds to one of these three outcomes. Remember that this is correlational research, so don t use causal language! Article 2: Feldman et al. (2018) Last week, we discussed the differences between correlational research and experimental research. Recall that correlational research, in which two variables are measured, allows for correlational claims, while experimental research, in which one variable is manipulated and another is measured, allows for causal claims. Feldman et al. (2017) presented a series of correlational studies in which the association between profanity and honesty is assessed. Appropriately, they do not make causal claims in their paper. But is it possible that there is a causal effect of profanity on honesty? For your study, imagine that you will borrow upon Feldman et al. s (2017) findings by conducting an experiment rather than a correlational study. In this experiment, you ll randomly assign people into two different conditions, and you ll manipulate an independent variable (profanity). Then you will measure the dependent variable (honesty). Do you think that you ll get a significant effect of profanity on honesty? 1. Describe the method. Profanity will be the two-level independent variable (people use profane words or they do not), and honesty will be the dependent variable. Take great care to explain how you will manipulate profanity and how you will measure honesty. 2. Describe your hypothesized results, both with words and with a graph. The graph should include the dependent variable on the vertical axis and the independent variable on the horizontal axis. You should present results that demonstrate one of the following: (a) people in the profanity condition were more honest, (b) people in the profanity condition were less honest, or (c) there was no effect of profanity on honesty. Make sure that your description of the results clearly and explicitly corresponds to one of these three outcomes. Article 3: Noor et al. (2018) Last week, we discussed social perception and attribution. Noor et al. (2018) presented evidence that we tend to label violent actors as a terrorist or as mentally ill based on our own worldviews. In Study 3, they showed that participant s attitudes toward Brexit predicted attributions about a murder. But is it possible that this effect might be further explained by age of participants? In your study, you will replicate Noor et al. s (2018) Study 1, imagining that you collected data immediately after the 2016 nightclub shooting in Orlando, Florida. What variable can you assess that might help 2

3 differentiate which people would attribute the shooting to terrorism versus mental illness? That is, Noor et al. (2018) used people s Brexit vote as a predictor. What predictor variable might you use? 1. Describe the correlational method. You ll have one predictor (of your choice) and one criterion (attribution; feel free to use the same criterion that Noor et al. (2018) used). 2. Describe your hypothesized results. This should be done both in words and using a graph. The graph should include the criterion on the vertical axis and the variable of your choice, the predictor, on the horizontal axis. Article 4: Brown-Ianuzzi et al. (2018) Last week, we discussed attitude measurement and how people often feel social pressure that prevents them from reporting their true opinions. Brown-Ianuzzi et al. (2018) used a unique implicit measure of attitudes the Unmatched Count Technique to assess attitudes toward various groups of people. They also compared how implicit and explicit measures differed, and how those differences were greater or smaller for various subsamples of their participants (see Figure 2). The researchers compared participants who differed in terms of education, age, politics, and religiosity. They did not, however, assess income level, which is often a powerful demographic predictor of attitudes. What do you think would have happened if income had been assessed? For your study, you ll simply describe a replication of Brown-Ianuzzi et al. s (2018) study, but you will include income level as the variable of interest. 1. Describe the method. You don t need to provide much detail beyond what Brown-Ianuzzi et al (2018) did, but explain how you will assess income level and explain how you ll determine what high-income is and what low-income is. 2. Describe your hypothesized results, both with words and with a graph. The graph should use the same formatting and labels as, for example, the first row of Figure 2. But, of course, you should arrange the dots, triangles, and lines so that they are consistent with your description of the hypothesis. Article 5: Voelkel & Feinberg (2017) A little while back, we discussed various aspects of how persuasion changing people s attitudes takes place. One area in which persuasion is particularly important is the world of politics. Voelkel and Feinberg (2017) presented research demonstrating that moral framing can yield differences in persuasion between politically conservative and politically liberal individuals. But do you think that all political conservatives would be equally impacted by the manipulation? you ll replicate Study 1, but to make things easier, and because Study 1 found no effect for 3

4 liberals, you ll only use conservatives in your study. You will randomly assign participants to either the fairness or loyalty arguments as was conducted in the original study. Let s also assume that you ran this study before the September 2016 election. You ll also add education level as a new moderating variable: You ll compare people who did not earn a high-school degree ( low education; roughly 10% of the US population 1 ) with those who have earned a post-graduate degree ( high education; also roughly 10% of the US population 2 ). People in the remaining middle 80% of the distribution will not be used. 1. Describe the method. The study will utilize two variables: educational attainment (low vs high; a measured subject variable) and moral framing (fairness argument vs loyalty argument; a manipulated independent variable). The DV will be likelihood to vote for Trump. This section will be relatively brief, as you ll simply replicate Voelkel and Feinberg s Study 1, but you ll assess education level. 2. Describe your hypothesized results, both with words and with a graph. When describing the results, be very sure to explain if the effect of message framing on the DV is (a) stronger for high-education participants, (b) stronger for low-education participants, or (c) equivalently strong for all participants. Make sure that your description of the results clearly and explicitly corresponds to one of these three outcomes. The graph should present the dependent variable on the vertical axis, education level on the horizontal axis, and the manipulation as separate lines or separate bars. Remember that you ll only be using conservatives in this study. Article 6: Mortensen et al. (2018) A few weeks ago, we learned about how norms can drive our behavior. Mortensen et al. (2018) conducted research demonstrating how behaviors described as non-normative (i.e., the majority of people are not engaging in such behaviors) can drive our behavior if we re led to believe that the behavior is increasing in popularity. But, as you might imagine, it s unlikely that we re all equally impacted by such trending norms. Is it possible that a person s social status defined however you wish might further explain the effect of trending norms on our behavior? In your paper, you ll replicate Study 1, but with a few changes. First, to make things easier, you ll randomly assign participants only to the minority norm or the trending minority norm conditions: you won t bother with a control condition. Second, you ll add a person s real or perceived social status as a second variable. Social status will be your moderating variable. Thus, for this paper: 1. Describe the method. The study will utilize two variables: norm (minority or trending; a manipulated independent variable) and social status (high or low; a measured subject variable). Be particularly clear in describing how you wish to define and assess social status. 2. Describe your hypothesized results, both with words and with a graph. When describing the results, be very sure to explain if the effect of the norm manipulation is (a) stronger for people high in social status, (b) stronger for people low in social status, or (c) equivalently strong for all participants. Make sure that

5 your description of the results clearly and explicitly corresponds to one of these three outcomes. The graph should present the dependent variable on the vertical axis, social status on the horizontal axis, and the manipulation as separate lines or separate bars. Article 7: Thurmer et al. (2018) Last week, we discussed group processes and some of the ways in which groups and group membership can behave in a suboptimal manner. Thurmer et al. (2018) presented research showing that people waste time performing tasks when their group affiliation is threatened by an outgroup member. Let s imagine that you were to base a new study off of Thurmer et al. s Study 1. Imagine that you run the study here at Union using Union College students. The manipulation is basically the same participants learn that another person provides a negative comment about students at Union College. That person is either a fellow Union student or a student at a rival College. In addition, participants loyalty to Union College is assessed: this will be your moderating variable. That is, some Union students probably feel a deep loyalty to the College, while others probably don t. How will these variables interact to predict the number of anagrams solved? 1. Describe the method. Be sure to explain the manipulation (whether the negative comment comes from a Union student or a student at a rival school) and your moderating variable (loyalty to Union: high or low), as well as the dependent variable. 2. Describe your hypothesized results. This should be done both in words and using a graph. When describing the results, be very sure to explain if the effect of the manipulation on the DV is (a) stronger for high-loyalty participants, (b) stronger for low-loyalty participants, or (c) equivalently strong for all participants. Make sure that your description of the results clearly and explicitly corresponds to one of these three outcomes. The graph should present number of anagrams solved on the vertical axis, loyalty on the horizontal axis, and the manipulation as separate lines or separate bars. Article 8: Johnson & Chopik (2018) Last week, we discussed prejudice, while earlier in the course, we described the Implicit Association Test and how it can be used to assess implicit attitudes. Johnson & Chopik s (2018) research relates to both of these areas, in that it assessed people s implicit associations between African Americans and violence. What implicit associations do you think that people have about college students? That is, whereas Johnson & Chopik (2018) found implicit associations between African Americans and violence, can you imagine an 5

6 implicit association between college students and some other concept? Your first task, thus, is to think of a concept (either positive or negative) that people implicitly associate with college students. Next, you ll think of a variable that determines which people hold this association with college students and which do not. This is your moderating variable. That is, Johson & Chopik (2018) found evidence that the implicit association between African Americans and violence was moderated by geography: People from some states showed a stronger implicit association than people from other states. Your task will be to think of a variable that explains which people have a stronger implicit association regarding college students. 1. Describe the method. No need to describe the IAT in much detail, but be sure to describe the concept that you think people will implicitly associate with college students, be sure to describe your moderating variable, and be sure to clearly describe how you ll assess it. 2. Describe your hypothesized results. This should be done both in words and using a graph. The graph should present the dependent variable ( IAT score in the same way that Johnson & Chopik (2018) did) on the vertical axis and your moderating variable on the horizontal axis. Unlike the past few weeks, you ll only have two data points here. 6