Students appreciate examples that are meaningful to them. How about a little selfie research? After covering experiments in the Intro Psych research methods chapter, ask students to think about how they would do an experiment to find out if people perceived those who post a lot of selfies to Instagram differently than those who post a lot of “posies”—photos of themselves taken by other people. Emphasize that the question is not how the people actually are, but how others think they are. Give students the independent variable: the last 30 Instagram photos—mostly selfies or mostly posies. Next, ask students to jot down some dependent variables. What might those different perceptions be? For example, would your students expect those with lots of selfies to be perceived as being more self-absorbed? After students have had a couple minutes to think about these, ask students to work in pairs or small groups to come up with their list of dependent variables. Once discussion has died down, ask each group to volunteer one dependent variable that has not already been identified by a previous group. Write the dependent variables where the class can see them. After each group has given one, ask students for any other dependent variables they came up with that haven’t already been named. Explain that in an experimental study, researchers could create fake Instagram accounts and manipulate how many selfies and how many posies to show participants who would then rate the owners of those fake accounts on each of the dependent variables.  In a recent correlational study, researchers wanted to know exactly that. Do people perceived Instagram users differently depending on how many selfies or posies the users posted (Barry et al., 2019)? Participants in this study rated 30 individuals based on the last 30 photos posted to their Instagram accounts. Researchers measured 13 dependent variables. Remember, these are all perceptions people had of the Instagram users based on their last 30 photos: self-esteem, liking adventure, loneliness, extraversion, trying new things, success, likeability, dependability, would be a good friend, self-absorption, worried about being left out, emotionality, and considerate of others. Those who had more selfies were perceived to: Have low self-esteem Not like adventure Be lonely Not be outgoing Not like trying new things Not be successful Not be likeable Those who had more posies were perceived to: Have high self-esteem Like adventure Not be lonely Be outgoing Be dependable Like trying new things Be successful Be likeable Be a good friend There were no significant correlations between number of selfies or number of posies and perceptions of being self-absorbed, worried about being left out, being emotional, or being considerate of others. After sharing these results, ask students what follow-up research questions should be addressed next. Or, if students were to replicate this study, what changes would they make?   Reference Barry, C. T., McDougall, K. H., Anderson, A. C., Perkins, M. D., Lee-Rowland, L. M., Bender, I., & Charles, N. E. (2019). ‘Check your selfie before you wreck your selfie’: Personality ratings of Instagram users as a function of self-image posts. Journal of Research in Personality, 82, 103843. https://doi.org/10.1016/j.jrp.2019.07.001 ... View more

After covering experiments and correlations in Intro Psych or as a research methods booster in the Stress & Health chapter, ask your students if they have heard that you should walk 10,000 steps a day. Do they know where that recommendation comes from? Did anyone guess that it seems to come from a 1964 Japanese marketing campaign for a pedometer (“Do you really need to take 10,000 steps a day to keep fit?,” 2015)? Recent correlational research with almost 17,000 women aged 62-101 (average age 72) found that those who took about 4,400 steps per day were 41% less likely to die during the study (mean study length: 4.3 years) than those who took 2,700 per day. The more steps walked per day, the lower the mortality. Benefits maxed out at 7,500 steps; walking more than that did not reduce mortality rates. Annually, researchers asked participants for “sociodemographic characteristics, health habits, and personal and family medical history,” as well as at the start of the study, “a 131-item food frequency questionnaire.” All things being equal, those who walked more (up to 7,500 steps per day), lived longer (Lee et al., 2019). When you have this many participants who are in that age range, you can use mortality as your primary dependent measure. Experimental research using other dependent measures such as blood pressure (Moreau et al., 2001) and cholesterol (Dasgupta et al., 2017; Sugiura et al., 2002) have found benefits to increasing number of steps walked per day. With students working in small groups, ask students to design an experiment to test the effects of walking on a dependent measure of their choosing. How many levels of the independent variable would they use? How would they ensure the number of steps walked by their participants? What dependent measures would they choose? How long would they run the study? What population would they choose as participants? Visit the groups answering any questions they may have. After the groups have finished their discussion, ask each group to report their independent variable and dependent variables. Complete this activity by explaining to students the importance of understanding the theory behind the research (on what dependent measures can we expect a benefit of exercise?), the importance of reading research articles on what has already been done (what have others found and how may that inform our study?), and the importance of doing research in many different ways (such as using different operational definitions).   References Dasgupta, K., Rosenberg, E., Joseph, L., Cooke, A. B., Trudeau, L., Bacon, S., … Smarter Trial Group. (2017). Physician step prescription and monitoring to improve ARTERial health (SMARTER): A randomized controlled trial in patients with type 2 diabetes and hypertension. Diabetes, Obesity, and Metabolism, 19(5), 685–704. https://doi.org/10.1111/dom.12874 Do you really need to take 10,000 steps a day to keep fit? (2015, June 17). BBC News. Retrieved from https://www.bbc.com/news/magazine-33154510 Lee, I.-M., Shiroma, E. J., Kamada, M., Bassett, D. R., Matthews, C. E., & Buring, J. E. (2019). Association of step volume and intensity with all-cause mortality in older women. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2019.0899 Moreau, K. L., Degamo, R., Langley, J., McMahon, C., Howley, E. T., Bassett Jr, D. R., & Thompson, D. L. (2001). Increasing daily walking lowers blood pressure in postmenopausal women. Medicine and Science in Sports and Exercise, 33(11), 1825–1831. Sugiura, H., Suguira, H., Kajima, K., Mirbod, S. M., Iwata, H., & Matsuoka, T. (2002). Effects of long-term moderate exercise and increase in number of daily steps on serum lipids in women: Randomised controlled trial. BMC Women’s Health, 2(1). ... View more

One of the perennial challenges in teaching Intro Psych is helping students understand that knowing that two variables are, say, positively correlated does not tell us anything about what causes that relationship. Discussion of this study would work during your coverage of correlations or during your coverage of circadian rhythms as an opportunity to revisit correlations. The 6.5-year study of 433,268 British adults (Knutson & von Schantz, 2018) provides us with an illustrative example. The researchers asked each person “Do you consider yourself to be definitely a morning person [27%], more a morning than evening person [35%], more an evening than morning person [28%], definitely an evening person [9%].” “Increased eveningness, particularly definite evening type, was associated with increased prevalence of a wide variety of diseases or disorders, including dia- betes, psychological, neurological, respiratory and gastrointestinal/abdominal disorders.” If your Intro Psych students are like most people, they want to jump to the conclusion that being a night owl will cause a number of health problems that will eventually lead to an early death. The lead author of this study, Kristen Knutson, thinks the root of the problem is really that of a mismatch. Many of our societies are geared toward the morning chronotype. If you have an evening chronotype but are trying to work, say, 9am to 5pm, you’re fighting against your own internal clock (Khan, 2018).   Ask students to work in pairs or small groups to generate a list of factors that are associated with good health. Perhaps their list includes things like exercising, getting good sleep, eating well, and developing and maintaining strong social ties. Now ask students to consider why these things may be more difficult for night owls than morning larks. For example, how many recreational sports teams compete at 11pm? How many spin or yoga classes are offered at midnight? How easy is it to find a restaurant with healthy fare at 10:30pm? How hard is it to get enough sleep when you don’t get sleepy until 2am but have to be up at 7am to be a work by 9am? Maintaining social ties is difficult for night owls who want to hang out at 10pm when most of their friends are headed to bed (Clark, 2019). The cause of the correlation between chronotype and health may be due to this whole host of third factors. What if night owls were allowed to be night owls? Would a night owl yoga instructor, for example, teaching at 11pm have night owl students? Would night owls get more sleep if they worked, say, 2pm to 10pm? If time allows, ask volunteers to share their chronotypes and how they’ve adjusted their schedules to fit that chronotype. Or, if their schedules don’t fit, to share why that’s a struggle. In closing this activity, reiterate that knowing that there is a relationship between two variables tells us nothing about why two variables are related.    References Clark, B. (2019, May 23). No, night owls aren’t doomed to die early. New York Times. Retrieved from https://www.nytimes.com/2019/05/23/smarter-living/no-night-owls-arent-doomed-to-die-early.html Khan, A. (2018, April 11). Bad news for night owls. Their risk of early death is 10% higher than for early risers, study finds. Los Angeles Times. Retrieved from https://www.latimes.com/science/sciencenow/la-sci-sn-night-owl-death-20180412-story.html Knutson, K. L., & von Schantz, M. (2018). Associations between chronotype, morbidity and mortality in the UK Biobank cohort. Chronobiology International, 35(8), 1045–1053. https://doi.org/10.1080/07420528.2018.1454458     ... View more

Last week, I gave five examples of experiments you can use to give students practice at identifying independent and dependent variables. Here are five more. After covering these concepts, ask students to work in pairs or small groups to identify both the independent variable(s) and the dependent variable(s) in each example. Hypothesis: If people use third person pronouns to describe an event that caused anxiety, they will be more likely to report visualizing the scene as a distant observer would. Researchers asked study participants to recall a time when they were “worried about something happening to” them. Participants were then randomly assigned to either the first person condition or the third person condition. In the first person condition, participants reflected on their experience through answering questions with an I/my focus, like “Why did I feel this way?” and “What were the underlying causes and reasons for my feelings?” In third person condition, participants reflected on their experience through answering questions with an outsider’s focus by using their own name in their reflection, like “Why did Jane feel this way?” and “What were the underlying causes and reasons for Jane’s feelings?” When asked, participants in the third-person group reported seeing the imagined event unfold further away from them than reported by participants in the first-person group. In this experiment, identify the independent variable and the dependent variable.  Kross, E., Bruehlman-Senecal, E., Park, J., Burson, A., Dougherty, A., Shablack, H., … Ayduk, O. (2014). Self-talk as a regulatory mechanism: How you do it matters. Journal of Personality and Social Psychology, 106(2), 304–324. https://doi.org/10.1037/a0035173   Hypothesis: If people hear how many others who stayed in their hotel room chose to reuse their hotel room towels, they will be more likely to reuse their towels, too.   The hotel room attendant supervisor placed one of five signs in the bathrooms of randomly-assigned hotel rooms. Each sign carried a different message: (1) a general “save the environment” message, (2) a “join your fellow guests” message explaining that 75% of guests who stayed at the hotel reused their towels, (3) another “join your fellow guests” message but this one explained that 75% of people who stayed in that very hotel room reused their towels, (4) a “join your fellow citizens” message that shifted the in-group from hotel guests to the broader citizens, and (5) a “join the men and women” message that shifted the in-group to one’s own gender group. Hotel guests who received message 3 about others who stayed in their hotel room were much more likely to reuse their towels (49.3%) as compared to all of the other groups (average re-use 42.8%). In this experiment, identify the independent variable and the dependent variable.  Goldstein, N. J., Cialdini, R. B., & Griskevicius, V. (2008). A room with a viewpoint: Using social norms to motivate environmental conservation in hotels. Journal of Consumer Research, 35(3), 472–482. https://doi.org/10.1086/586910   Hypothesis: If people are given unwrapped pieces of chocolate, they will consume them more quickly than those given wrapped pieces of chocolate. Participants received six pieces of chocolate. Random assignment determined which participants received separately wrapped pieces and which received unwrapped pieces. Participants were asked to record when they ate the chocolate. Those who received the unwrapped pieces ate most of them within two days. Those with wrapped pieces took longer. In this experiment, identify the independent variable and the dependent variable.  Cheema, A., & Soman, D. (2008). The effect of partitions on controlling consumption. Journal of Marketing Research, 45(6), 665–675. https://doi.org/10.1509/jmkr.45.6.665Use the "Insert Citation" button to add citations to this document.   Hypothesis: If people receive information about available health services, they will use those services more. Researchers sampled several communities in India on their use of available health services. They randomly assigned half of the communities to receive pamphlets and community meetings that informed them of services. A year later, these residents had more prenatal examinations, more tetanus vaccinations, more prenatal supplements, and more infant vaccinations than people in the communities that did not receive the pamphlets or hold the community meetings. In this experiment, identify the independent variable and the dependent variables. Pandey, P., Sehgal, A. R., Riboud, M., Levine, D., & Goyal, M. (2007). Informing resource-poor populations and the delivery of entitled health and social services in rural India: A cluster randomized controlled trial. Journal of the American Medical Association, 298(16), 1867–1875. https://doi.org/10.1001/jama.298.16.1867   Hypothesis: If we invite girls to “do science” as compared to “be a scientist,” they will persist longer in playing a science game. Researchers randomly assigned young girls to hear that “Today we’re going to do science” or hear that “Today we’re going to be scientists” before playing a science game where the children had to make guesses based on observation. After failing at their guesses, the experimenter the child if she wanted to keep playing or do something else. The girls in the “do science” condition were more likely to persist in playing the game than those in the “be a scientist” condition. In this experiment, identify the independent variable and the dependent variable. Rhodes, M., Leslie, S. J., Yee, K. M., & Saunders, K. (2019). Subtle linguistic cues increase girls’ engagement in science. Psychological Science. https://doi.org/10.1177/0956797618823670 ... View more

Psychology students often struggle with the difference between the independent and dependent variables. After covering these concepts, ask students to work in pairs or small groups to identify both the independent variable(s) and the dependent variable(s) in each example. Hypothesis: Creating concrete examples will improve recall. "Students read a short text that introduced eight concepts. Some students were then prompted to generate concrete examples of each concept followed by definition restudy, whereas others only restudied definitions for the same amount of time. Two days later, students completed final tests involving example generation and definition cued recall." (In the definition cued recall test, the cues were the names of each of the concepts; the "recall" was the student writing down the definition.) Those who created their own examples of each of the concepts did better on the test than students who just restudied the concepts.  In this experiment, identify the independent variable and the dependent variable.  Rawson, K. A., & Dunlosky, J. (2016). How effective is example generation for learning declarative concepts? Educational Psychology Review, 28(3), 649–672. https://doi.org/10.1007/s10648-016-9377-z   Hypothesis: Attending to a phone will decrease the likelihood of seeing a unicycling clown. People, after walking across a college square, were asked if they saw a clown unicycling around a central sculpture. Only 25% of cell phone users reported seeing the clown as compared to 60% of people who were listening to music, 51% of people who were walking alone with no technological distractions, and 71% of people who were walking with another person. This type of study is called a quasi-experiment because participants weren't randomly assigned to conditions. In this experiment, identify the independent variable and the dependent variable.  Hyman, I. E., Boss, S. M., Wise, B. M., McKenzie, K. E., & Caggiano, J. M. (2010). Did you see the unicycling clown? Inattentional blindness while walking and talking on a cell phone.  Applied Cognitive Psychology, 24, 597–607. https://doi.org/10.1002/acp.1638   Hypothesis: Being sleep-deprived will increase the desire for high-calorie foods. After either get a full night’s sleep or staying awake all night, participants were asked how desirable each of 80 different foods were.  When participants were sleep-deprived, they found high-calorie foods more desirable than when they had a full night’s sleep. This type study is called a within-subjects design because the same participants got both the full night’s sleep and, on another night, stayed awake all night. In this experiment, identify the independent variable and the dependent variable.  Greer, S. M., Goldstein, A. N., & Walker, M. P. (2013). The impact of sleep deprivation on food desire in the human brain. Nature Communications, 4, 1–7. https://doi.org/10.1038/ncomms3259   Hypothesis: “Inflated praise [will] decrease challenge-seeking in children with low self-esteem but [will] increase challenge-seeking in children with high self-esteem.” Children (ages 8 to 12), after having their self-esteem measured, “drew a famous painting… and were told that that a professional painter, who in reality did not exist, would examine their drawing.”  Each child then received a handwritten note that they were told was written by the painter. The note said either, “You made an incredibly beautiful drawing!,” “You made a beautiful drawing!,” or did not address the drawing. Children then could choose to replicate two easy drawings (“If you choose to draw these easy pictures, you won’t make many mistakes, but you won’t learn much either.”) or two difficult drawings (“If you choose to draw thsese difficult pictures, you might make many mistakes, but you’ll definitely learn a lot, too.”). Children with low self-esteem who received the incredibly beautiful praise were more likely to choose the easy drawings. Children with low self-esteem who received the beautiful praise were likely to choose the difficult drawings. Those results were reversed for children with low self-esteem. In this experiment, identify the two independent variables and the dependent variable. Brummelman, E., Thomaes, S., Orobio de Castro, B., Overbeek, G., & Bushman, B. J. (2014). “That’s not just beautiful-that’s incredibly beautiful!”: The adverse impact of inflated praise on children with low self-esteem. Psychological Science, 25(3), 728–735. https://doi.org/10.1177/0956797613514251   Hypothesis: Tasters will rate vinegar-laced beer as better than regular beer if they are not first told that vinegar has been added to the beer. Participants were invited to taste two different beers and express their preference for one over the other. Participants were told that the beer was laced with vinegar either before or after tasting or were told nothing. Participants who weren’t told that the beer was laced with vinegar or were told after they tasted it preferred it over the regular beer. Those who were told it was laced with vinegar before tasting it preferred the regular beer. In this experiment, identify the independent variable and the dependent variable. Lee, L., Frederick, S., & Ariely, D. (2006). Try it, you’ll like it: The influence of expectation, consumption, and revelation on preferences for beer. Psychological Science, 17(12), 1054–1058. https://doi.org/10.1111/j.1467-9280.2006.01829.x ... View more

Cartoonists have pretty good insight into the workings of the human mind. How many of them took Intro Psych? These comics will jazz up your next research methods, cognition, personality, learning, and social psych lectures. Dilbert's boss does not have an operational definition of "employee engagement," and, thus, no way to measure it. Also, on the ethics side, no, it's not okay to make up data. Lio, having no trouble with functional fixedness, repurposes an object into a sled. Lio’s friends aren’t typical. His ingroups include monsters, aliens, and death himself. When everyone else sees those creatures as part of a threatening outgroup, to Lio, they are just his friends. Also, you don’t have to read through too many strips to see Lio’s strong internal locus of control. Rat in Pearls Before Swine can be counted on for a solid outgroup homogeneity bias. Jeremy’s mom in Zits provides a nice example of positive punishment. No, I don’t think he’ll forget his textbook at home again. Or, perhaps more likely, if he does forget it at home, he won’t ask his mom to bring it to school. After all, punishment makes us better at avoiding the punishment. Caulfield, the boy in Frazz, wonders if Santa has fallen victim to the just-world phenomenon. Pig in Pearls Before Swine, whose sweetness and innocence may be unparalleled in the comics universe, does not fall for the fundamental attribution error. Looking for more example from the comics? Here are some previous comic-focused blog posts: Spotlight effect Door-in-the-Face, classical conditioning, and operant conditioning Change blindness, priming, and positive reinforcement ... View more

Do you cover survey research in your Intro Psych course? Given the prevalence of bad surveys, I’m starting to think I should spend more time on it. For a seemingly unlimited supply of bad survey questions, check out the @BadSurveyQ Twitter account. (Thank you to Rachel Soicher at Oregon State University for directing me to this.) Point out to students that not all surveys are written by researchers who have been trained to conduct surveys. In fact, some survey questions are designed to persuade, not to actually gather data. Other survey questions are written by people with good intentions who may not have thought them all the way through. Can you students spot the difference? More importantly, can your students fix the problems? @KenFernandezPHD shared this slanted poll question. In small groups, ask students to take a crack at rewriting this question in neutral language. Do you believe the corrupt leadership of the FBI and DOJ [Department of Justice] now realize President Trump means to end their efforts to subvert his presidency? Yes No @magnatom found another slanted poll question. How would your students fix this one? Do you think the Government will ever seriously look into proven, practical and effective methods to lower vehicle emissions instead of resorting to raising yet more cash from drivers? Yes No No idea @t_mabon found this limited option question. Can students identify the problem? And then fix it? How do you read your books? Papers e-reader/tablet I don’t read Audio books @sachinsomaiya found a question that left the interpretation of the rating scale up to the reader. How do your students interpret this? How would they make it better? What priority would you assign to the candidate for this program? Choose a number between 1 to 10 for the person. @BadSurveyQ wonders about the “other” option in this question. Other what? What would your students do with this “other” option to fix the question? Which of the following have you done in the last 2 years? Rented a house Rented an apartment Rented a car Bought a house Bought an apartment Bought a car Other None of the above @t_mabon shared a poll question that had responses only a company could love. What additional options would your students add? Which of the following statements do you agree with? SELECT ALL THAT APPLY Uber is a company I’m proud to say I use Uber is a brand/service for me Uber sends me relevant communications And one last question from @BadSurveyQ, another question that only a company could love. Please select three other statements that according to you also apply to a Tassimo machine [coffee maker]. Freedom Togetherness Power Entertaining Liberating Fun Open-minded Now, with this blog post completed, I’m going to have a long over-due chat with my coffee maker. If it’s not entertaining and open-minded, it’s out of here. ... View more

No, your students will not be texting or talking/listening to a phone in a crosswalk! Instead, they will be observing others who are. A recent study (Alsaleh, Sayed, & Zaki, 2018)* found that people who were on their phones – either looking at their screens or talking/listening to their phone – took longer to cross the street. This is dangerous for a number of reasons. For example, distracted pedestrians are not on the lookout for distracted motorists. When distracted pedestrians and distracted motorists meet, distracted pedestrians always lose. Since distracted pedestrians spend more time in the crosswalk, they have a greater chance of being hit by a distracted motorist. How much time does it take? In urban areas, lanes should be 10 feet (3 meters) wide (National Association of City Transportation Officials, n.d.). That makes a four-lane road 40 feet (12 meters) wide. In the distraction study (Alsaleh et al., 2018), non-distracted pedestrians walked at a rate of 1.66 meters/second. That means it took them about 7 seconds to cross a four-lane road. In contrast, researchers found that phone-distracted pedestrians walked at a rate of about 1.5 meters/second, taking about 8 seconds to cross a four-lane road. The activity The researchers used observers on the ground to determine whether and how pedestrians were using their phones and used cameras to determine walking speed. For this activity, all measures will be done by observers. Divide students into groups no smaller than three students. One student will determine if the pedestrian is distracted by their phone or not. Since the researchers found no difference in walking speed between looking at the phone and talking/listening, let’s keep this simple and not ask students to make the distinction. One student will be the timer. Using a stopwatch app on their own phone, the student will time how long it takes the pedestrian to cross the street. The third student will be the recorder – recording whether the pedestrian was distracted and recording the time it took the pedestrian to cross the street. Students will need to make some decisions before heading out. If you would like to compile the data across groups, then you should have this discussion as a class. If you would like to discuss how each group’s decisions affected their results afterwards, then let each group decide these on their own. Consider these as starter questions. When students return from the activity, they may have other issues that should have been considered in advance. That is a great opportunity to talk about the importance of pilot studies and their role in helping sort out these issues before investing time in a larger study. Where are they going to do their observations? Ideally, it will be a street with a lot of pedestrian traffic. The wider the street, the easier it will be see differences in the time it takes to cross. If there is a group of people waiting to cross the street, how will students determine who to time? The first person to cross? The right-most person? How will the students identify the person to each other to make sure that the student noting the phone behavior and the student doing the timing are looking at the same pedestrian? When will the timing start? When the target pedestrian lifts a foot to step off the curb? When the foot first hits the street? When will the timing stop? When the target pedestrian lifts a foot to stop onto the curb? When the last foot leaves the pavement? How will the recorder record the data? How many columns will be in the data sheet? To how many decimal places will the stopwatch times be recorded? How long will they collect data? Or how many pedestrians should they time? What if all of the pedestrians are on a phone? When students return with their data, either that same class period or the next class period, have the recording student enter their data in a shared Google spreadsheet, for example. One column should be the first and last initials of each member of the group, one column is for non-distracted times, and one column is for distracted times. Calculate means for the non-distracted and distracted pedestrians. If you’d like, conduct a t-test if you want to talk about statistical significance. If some groups seem to have much slower or longer times than other groups, discuss the methodology they used. Give each group an opportunity to share with the class what they would do differently if they were to conduct this observational research study again. Conclusion To conclude the activity, explain that if the class were to submit this study for publication, the authors would summarize the research related to this topic, explain in detail how the study was conducted, reveal the results, and finally explain what the findings mean, how they add to the body of research on this topic, and identify what could be done differently or better next time. Now is also a good time to explain the peer review process and the importance of replication.   References Alsaleh, R., Sayed, T., & Zaki, M. H. (2018). Assessing the effect of pedestrians’ use of cell phones on their walking behavior. Transportation Research Record , Advance online publication. https://doi.org/https://doi.org/10.1177/0361198118780708 National Association of City Transportation Officials. (n.d.). Lane width. Retrieved August 17, 2018, from https://nacto.org/publication/urban-street-design-guide/street-design-elements/lane-width/   *Note: The full article by Alsaleh et al. is available through ResearchGate. ... View more

“The most famous psychological studies are often wrong, fraudulent, or outdated.” With this headline, Vox joins critics that question the reproducibility and integrity of psychological science’s findings.   Are many psychology findings indeed untrustworthy? In 2008, news from a mass replication study—that only 36 percent of nearly 100 psychological science studies successfully reproduced the previous findings—rattled our field. Some challenged the conclusion: “Our analysis completely invalidates the pessimistic conclusions that many have drawn from this landmark study,” said Harvard psychologist Daniel Gilbert.   For introductory psychology teachers, those supposed failures to replicate need not have been a huge concern. Introductory psych textbooks focus on major, well-established findings and ideas. (For example, only one of the 60+ unreplicated studies were among the 5,174 references in my text at the time, necessitating a deletion of only one-half sentence in its next edition.)   But here are more recent criticisms—about six famous and favorite studies: Philip Zimbardo stage-managed the Stanford prison study to get his wished-for results, and those who volunteer for such an experiment may be atypically aggressive and authoritarian (see here and here ). Moreover, as Stephen Reicher and Alex Haslaam showed , when they recreated a prison experiment with the BBC (albeit as reality TV rather than a replication), groups don’t necessarily corrupt—people can collectively choose to behave in varied ways. For such reasons, the Stanford prison study may in the future disappear from more intro psych texts. But for the present, some teachers still use this study as a vivid illustration of the potential corrupting power of evil situations. (Moreover, Philip Zimbardo and colleagues have released responses here .) Muzafer Sherif similarly managed his famed boys’ camp study of conflict and cooperation to produce desired results (see here ). Yet my friend Stephen Reicher, whom I met over coffee in St. Andrews two weeks ago, still considers the Sherif study a demonstration (even if somewhat staged) of the toxicity of competition and the benefits of cooperation. The facial-feedback effect—the tendency of facial muscles to trigger associated feelings—doesn’t replicate (see here ). The failure to reproduce that favorite study (which my students and I have experienced by holding a pencil with our teeth vs. our pouting lips) wiped a smile off my face. But then the original researcher, Fritz Strack , pointed us to 20 successful replications. And a new study sleuths a crucial difference (self-awareness effects due to camera proximity) between the studies that do and don’t reproduce the facial feedback phenomenon. Even without a pencil in my mouth, I am smiling again. The ego-depletion effect—that self-control is like a muscle (weakened by exercise, replenished with rest, and strengthened with exercise)—also failed a multi-lab replication ( here ). But a massive new 40-lab study, with data analyzed by an independent consultant—“innovative, rigorous” science, said Center for Open Science founder Brian Nosek—did show evidence of a small depletion phenomenon. Kitty Genovese wasn’t actually murdered in front of 38 apartment bystanders who were all nonresponsive (see here ). Indeed. Nevertheless, the unresponsive bystander narrative—initiated by police after the Genovese murder—inspired important experiments on the conditions under which bystanders will notice and respond in crisis situations. Mischel’s marshmallow study (children who delay gratification enjoy future success) got roasted by a big new failure to replicate. As I explain in last week’s www.TalkPsych.com essay, the researchers did find an association between 4½-year-olds’ ability to delay gratification and later school achievement, but it was modest and related to other factors. The take-home lesson: Psychological research does not show that a single act of behavior is a reliable predictor of a child’s life trajectory. Yet life success does grow from impulse restraint. When deciding whether to study or party, whether to spend now or save for retirement, foregoing small pleasures can lead to bigger rewards later.   One positive outcome of these challenges to psychological science has been new scientific reporting standards that enable replications, along with the establishment of the Center for Open Science that aims to increase scientific openness, integrity, and reproducibility. (I was pleased recently to recommend to fellow Templeton World Charity Foundation trustees a multi-million dollar grant which will support the Center’s mission.)   The big picture: Regardless of findings, research replications are part of good science. Science, like mountain climbing, is a process that leads us upward, but with times of feeling like we have lost ground along the way. Any single study provides initial evidence, which can inspire follow-up research that enables us to refine a phenomenon and to understand its scope. Through replication—by winnowing the chaff and refining the wheat—psychological science marches forward. ... View more

The Syrian slaughter. North Korea nuclear warheads. ISIS attacks. School shootings. Social media-fed teen depression. Thugs victimizing people of color and women. Inequality increasing. Online privacy invaded. Climate change accelerating. Democracy flagging as autocrats control Turkey, Hungary, China, and Russia, and as big money, voter suppression, and Russian influence undermine American elections. U.S. violent crime and illegal immigration soaring.   For news junkies, it’s depressing. We know that bad news predominates: If it bleeds, it leads. But we can nevertheless take heart from underreported encouraging trends. Consider, for example, the supposed increases in crime and illegal immigration.   Is it true, as President Trump has said, that “crime is rising” and in inner cities “is at levels that nobody has seen”? Seven in 10 Americans appeared to agree, when reporting to Gallup in each recent year that violent crime was higher than in the previous year. Actually, crime data aggregated by the FBI (shown below) reveals that violent (and property) crime have dramatically fallen since the early 1990s. And is the U.S. being flooded with immigrants across its Mexican border—“evil, illegal immigrants who commit violent crimes,” as a 2018 DonaldJTrump.com campaign ad declared? In reality, the influx has subsided to a point where, Politifact confirms, “more illegal Mexican immigrants are leaving the United States than entering it.” (Should we build a wall to keep them in?)   But what about immigrant crime—fact or fiction? “Americans are five times more likely to say immigrants make the [crime] situation worse rather than better (45% to 9%, respectively),” reports Gallup. Not so. Multiple studies find that, as the National Academy of Sciences reports, “immigrants are less likely than the native-born to commit crimes” and are underrepresented in American prisons.   For more good news, consider other heartening long-term trends: World hunger is retreating. Child labor is less common. Literacy is increasing. Wars are becoming less frequent. Explicit racial prejudice (as in opposition to interracial marriage) has plummeted. Gay, lesbian, and transgender folks are becoming more accepted. Infant mortality is rarer and life expectancy is increasing. Such trends are amply documented in Steven Pinker’s recent books, The Better Angels of Our Nature and Enlightenment Now, and in Johan Norber’s Progress , and Gregg Easterbrooks, It’s Better Than It Looks. As President Obama observed, if you had to choose when to live, “you’d choose now.”   Yes, in some ways, these are dark times. But these are also the times of committed Parkland teens. Mobilized citizens. Machine learning. Immune therapies. #MeToo. #BlackLivesMatter. Low inflation. Near full employment. Digital streaming. Smart cars. Wearable technologies. Year-round fresh fruit. And Post-It notes.   To paraphrase Charles Dickens, it is the worst of times, it is the best of times. It is an age of foolishness, it is an age of wisdom. It is a season of darkness, it is a season of light. It is the winter of despair, it is the spring of hope. ... View more

My colleague, Lindsay Root Luna, has new data showing that virtues correlate. People’s scores intercorrelate on scales assessing humility, justice, wisdom, forgiveness, gratitude, hope, and patience. Show her a forgiving person and she will likely show you a humble, grateful person.   Root Luna’s observations triggered my thinking about other human dispositions that come bundled. First, there are the anti-virtues.   As the concept of ethnocentricism conveys, prejudices often coexist: anti-gay, anti-immigrant, anti-Black, anti-Muslim, and anti-women sentiments often live inside the same epidermis. People intuitively know this. Thus, as Diana Sanchez and colleagues have observed, White women often feel threatened by someone who displays racism, and men of color by sexism.   Likewise, people’s tendencies on the “dark triad”—narcissism, Machiavellianism, and psychopathy—are “substantially intercorrelated.” Show Peter Muris and colleagues a narcissist (perhaps your least favorite politician?), and they’ll show you a likely Machiavellian and amoral person.   On the brighter side, some good things, in addition to the virtues, also tend to come wrapped in the same skin. Charles Spearman recognized this long ago with the concept of general intelligence (g). Those who score high in one cognitive domain have some tendency to score higher than average in other areas such as reasoning or spatial ability, or even perceptual speed.   Athleticism offers another example of packaged gifts. The ability to run fast is distinct from muscular strength or the eye-hand coordination involved in the precise pitching of a ball. Yet there remains some tendency for athletic excellence in one domain to correlate with that in another. Good tennis players may also be better than average basketball players.   Surely this does not exhaust the list. Can you think of other examples of correlated good things and bad things? ... View more

Apophenia is seeing patterns in randomness, which may be the mechanism behind conspiracy theory generation. If it feels to me like a set of random events are connected and no one is talking about the connection, then conspiracy must be afoot (Poulsen, 2012). Psychiatrist Klaus Conrad is credited with coining this term in 1958 to describe the descent into psychosis, “Borrowing from ancient Greek, the artificial term ‘apophany’ describes this process of repetitively and monotonously experiencing abnormal meanings in the entire surrounding experiential field, eg, being observed, spoken about, the object of eavesdropping, followed by strangers” (as cited in Mishara, 2010). But this isn’t a post about conspiracy theories or psychosis. While conspiracy theories and psychosis take our ability to see patterns to whole other level, seeing patterns in randomness is just how our brains work. The visual version of apophenia is pareidolia. Have you ever seen a rabbit in a cloud formation? That’s pareidolia. Have you seen a face in a piece of toast? Also pareidolia. After covering the cerebral cortex, tell students that there is an area in the temporal lobe that is especially good at detecting faces: the fusiform face area (FFA). Show students these 20 objects where faces appear. Ask students to guess whether they think that seeing these objects would cause the FFA to be activated. How could that hypothesis be tested? Give students a minute to think about it, a minute to share with a partner, and then ask for volunteers for their suggestions. This would be a nice time to review independent variables and dependent variables. When you’re ready, tell students that researchers compared such face objects with everyday no-face objects, and found that face-objects activated the FFA (Hadjikhani, Kveraga, Naik, & Ahlfors, 2009). If time allows, describe prosopagnosia (pro-soap-ag-nose-ee-ya; face-blindness). Do students think that the FFA would be activated when people with congenital prosopagnosia look at faces? Why or why not? The FFA is activated, but it doesn’t show habituation. When people without prosopagnosia are shown faces a second time, the FFA shows decreased activation; “Not interesting; I’ve seen this before.” For those with prosopagnosia, the activation is just as great the second time around; “Hey, this is new!” (Avidan, Hasson, Malach, & Behrmann, 2005). Again if time allows, do students think the FFA would be activated in people with autism. Why or why not? For the participants in the study, the severity of their autism varied. For those who had impaired face recognition (about half of their sample, 14 out of 27) , the activation of their FFA was weaker.   For 30 years, researchers have debated whether the FFA is face-specific or whether it is for detecting any complex pattern we’re expert in (Kanwisher & Yovel, 2006). Some recent research has found that the FFA is active when expert chess players look at positions of chess pieces, positions taken from actual gameplay, but not a specific chess piece (Bilalic, 2016). And researchers have also compared expert radiologists with beginner medical students. When the experts looked at X-rays, their FFAs were active (Bilalic, Grottenthaler, Nagele, & Lindig, 2016). While the jury is still out on whether the FFA is face-specific or not, this is a wonderful example of science in action. Researchers describe a finding. All researchers start thinking about what might be the cause of that finding, and they start devising experiments to test their hypothesized causes.   References  Avidan, G., Hasson, U., Malach, R., & Behrmann, M. (2005). Detailed exploration of face-related processing in congenital prosopagnosia: 2. Functional neuroimaging findings. Journal of Cognitive Neuroscience, 17(7), 1130–1149. https://doi.org/10.1162/0898929054475154 Bilalic, M. (2016). Revisiting the role of the fusiform face area in expertise. Journal of Cognitive Neuroscience, 28(9), 1345–1357. https://doi.org/10.1162/jocn  Bilalic, M., Grottenthaler, T., Nagele, T., & Lindig, T. (2016). The faces in radiological images: Fusiform face area supports radiological expertise. Cerebral Cortex, 26 (3), 1004–1014. https://doi.org/10.1093/cercor/bhu272 Hadjikhani, N., Kveraga, K., Naik, P., & Ahlfors, S. P. (2009). Early (N170) activation of face-specific cortex by face-like objects. Neuroreport, 20 (4), 403–407. https://doi.org/10.1097/WNR.0b013e328325a8e1 Kanwisher, N., & Yovel, G. (2006). The fusiform face area: a cortical region specialized for the perception of faces. Philosophical Transactions of the Royal Society B: Biological Sciences, 361 (1476), 2109–2128. https://doi.org/10.1098/rstb.2006.1934 Mishara, A. L. (2010). Klaus Conrad (1905-1961): Delusional mood, psychosis, and beginning schizophrenia. Schizophrenia Bulletin, 36 (1), 9–13. https://doi.org/10.1093/schbul/sbp144 Poulsen, B. (2012). Being amused by apophenia. Retrieved from https://www.psychologytoday.com/blog/reality-play/201207/being-amused-apophenia ... View more

Credit President Trump with consistency in cultivating public fears of immigrants: “When Mexico sends its people . . . they’re bringing drugs. They’re bringing crime. They’re rapists.” ( 2015 ) A January, 2018 DonaldJTrump.com ad offered images of an illegal-immigrant murderer while a narrator referred to “evil, illegal immigrants who commit violent crimes,” noting that “Democrats who stand in our way will be complicit in every murder committed by illegal immigrants.” “If we don’t get rid of these loopholes where killers are allowed to come into our country and continue to kill … if we don’t change it, let’s have a shutdown,” Trump said two weeks later.   Horrific rare incidents feed the narrative, as in Trump’s oft retold story of the Mexican national who killed a young woman in San Francisco (with a ricocheted bullet), or in his February 6th tweet about the unauthorized immigrant drunk driver who killed a Baltimore Colts linebacker.   The effect of this rhetoric and these publicized incidents appears in a recent Gallup survey: “On the issue of crime, Americans are five times more likely to say immigrants make the situation worse rather than better (45% to 9%, respectively).” Are they (and the President) right?   With 11 million unauthorized immigrants in the U.S., there will, of course, be ample opportunities to illustrate both immigrant horrors and heroism. Mindful that emotionally compelling stories can illustrate larger truths or deceive us, I searched for data that would answer this question: Are the President’s words illustrating a painful fact that justifies anti-immigrant views, or are they fear mongering demagoguery? Here’s what I found (drawn from my contribution to an upcoming social psychology symposium on human gullibility): Immigrants who are poor and less educated may fit our image of criminals. Yet studies find that, compared with native-born Americans, immigrants commit less violent crime ( Butcher & Piehl, 2007 ; Riley, 2015 ). “Immigrants are less likely than the native-born to commit crimes,” confirms a National Academy of Sciences report ( 2015 ). After analyzing incarceration rates, the conservative Cato Institute ( 2017 ) confirmed that “immigrants are less likely to be incarcerated than natives relative to their shares of the population. Even illegal immigrants are less likely to be incarcerated than native-born Americans.” Noncitizens are reportedly 7 percent of the U.S. population and 6 percent of state and federal prisoners ( KFF, 2018 ; Rizzo, 2018 ). Moreover, as the number of unauthorized immigrants has tripled since 1990 ( Krogstad et al., 2017 ), the U.S. crime rate plummeted .   Alas, when pitted against memorable anecdotes, data—which are merely the sum of all anecdotes—often lose. The availability heuristic—the human tendency to estimate the commonality of an event based on its mental availability (often influenced by its vividness) frequently hijacks human judgments. When data on immigrant arrest or prison population proportions are set against this 2.5 minute excerpt from the 2018 State of the Union address—highlighting the teary parents of two daughters reportedly murdered by a gang with illegal immigrant members—which will people more likely remember?   Moreover, social psychologists Leaf Van Boven and Paul Slovic recently noted that the White House has also promoted its immigrants-as-killers thesis with misleading statistics. “Nearly 3 in 4 individuals convicted of terrorism-related charges are foreign-born,” the President tweeted last month. But that statement, and the administration report on which it was based, were “deeply misleading” the psychologists explain, for two reasons. First, the report excluded domestic terrorists, whom Americans fear most, and was inflated with tenuously relevant terrorism-related activities such as perjury and petty theft. Second, the scary-sounding statistic exploited people’s statistical illiteracy. Consider, they say, that 3 in 4 NBA players are African-American. Even so, “a vanishingly small” percentage of African-American men—less than 0.01 percent—play in the NBA. Thus, knowing only that a man is African-American, the chances are 99.99+ percent that he is not an NBA player. And knowing only that someone has been born outside the U.S., you can be similarly confident that the person is not a terrorist, or a killer. Donald Trump’s fear mongering and repeated misrepresentation of truth has me thinking again of George Orwell’s Nineteen Eighty-Four—a world where repeated falsehoods come to be believed: “Freedom is slavery.” “Ignorance is strength.” “War is peace.” I do wonder: When Trump proclaims these falsehoods, does he know they are untrue, or does he believe what he proclaims?   Pope Francis offered a possible answer, quoting Dostoevsky’s The Brothers Karamazov: “People who lie to themselves and listen to their own lie come to such a pass that they cannot distinguish the truth within them, or around them, and so lose all respect for themselves and for others.”   ... View more

Over lunch recently, a friend told about taking a firearm course, which enabled her to carry a concealed pistol and thus, she presumed, to live at less risk of harm.   Isn’t it obvious: If more of us have guns, and if gun-toting criminals therefore fear our having a gun, then they will be less likely to rob or attack us? The NRA likes to remind us that “the only thing that stops a bad guy with a gun is a good guy with a gun.”   But two new Science reports indicate quite the opposite.   It’s no secret, as Stanford researchers Philip Cook and John Donohue report, that some 36,000 Americans a year die of gunshot, and that the U.S. gun suicide rate is eight times that of other high-income countries, and the gun-murder rate is 25 times higher. More newsworthy is their reporting an “emerging consensus,” using sophisticated statistical analyses, that right-to-carry laws “substantially increase violent crime.”   For example, from 1977 to 2014, U.S. violent crime rates fell by 4.3 percent in states that adopted right-to-carry laws, but by a whopping 42.3 percent in states that did not adopt such laws. In tense situations, from car accidents to barroom and domestic arguments, guns enable deadly responses. Anecdotes of private guns deterring violence are offset by many more incidents of innocent deaths.   In the second report, economists Phillip Levine and Robin McKnight studied firearm sales after the Sandy Hook Elementary School massacre of 20 children and six adults. They associated a spike in firearm sales after the massacre with a corresponding spike in firearm deaths—in the very places where firearm sales had significantly increased. “We find that an additional 60 deaths overall, including 20 children, resulted from unintentional shootings in the aftermath of Sandy Hook.”   These new findings confirm what other evidence tells us: Guns purchased for safety make us less safe. ... View more

I recently finished Sam Kean’s (2012),  The Violinist’s Thumb the history, the present, and the future of DNA research. Kean writes, “Genes don’t deal in certainties; they deal in probabilities.” I love that – and I’m using it the first day of Intro Psych next term: “Psychology doesn’t deal in certainties; it deals in probabilities.” I already talk about correlations as probabilities. The stronger the correlation, the higher the probability that if you know one variable, you can predict the other variable. In the learning chapter, it’s not unusual for a student to say, “I was spanked, and I turned out okay.” Now I can repeat, “psychology doesn’t deal in certainties; it deals in probabilities.” When children are spanked, it increases the probability of future behavioral problems (Gershoff, Sattler, & Ansari, 2017). It is not a certainty. Whenever aggression comes up as a topic, a student will say, “I play first-person-shooter games, and I’ve never killed anybody.” Again, “psychology doesn’t deal in certainties; it deals in probabilities.” Playing violent video games increases the chances of being aggressive. Watching violent movies increases the chances of being aggressive. Listening to violent-themed music increases the chances of being aggressive. (List is not exhaustive.) The more of those factors that are present, the greater the probability of behaving aggressively (Anderson, C, Berkowitz, L, Donnerstein, E, Huesmann, L, Johnson, J, Linz, D, Malamuth, N, & Wartella, 2003). It is not a certainty. A student says, “I was deprived of oxygen when I was being born, and I haven’t developed schizophrenia” (McNeil, Cantor-Graae, & Ismail, 2000). (Okay, I have never had a student say this, but I wanted one more example.) Being deprived of oxygen at birth increases the probability of developing schizophrenia. It is not a certainty. Any time a student reports an experience that does not match what most in a research study experienced, I can say “Like genetics, psychology doesn’t deal in certainties; it deals in probabilities.”   References Anderson, C, Berkowitz, L, Donnerstein, E, Huesmann, L, Johnson, J, Linz, D, Malamuth, N, & Wartella, E. (2003). The influence of media violence on youth: . Psychological Science In The Public Interest (Wiley-Blackwell), 4(3), 81–110. https://doi.org/10.1111/j.1529-1006.2003.pspi_1433.x Gershoff, E. T., Sattler, K. M. P., & Ansari, A. (2017). Strengthening Causal Estimates for Links Between Spanking and Children’s Externalizing Behavior Problems. Psychological Science, 95679761772981. https://doi.org/10.1177/0956797617729816 Kean, S. (2012). The Violinist’s Thumb. New York City: Little, Brown, and Company. McNeil, T. F., Cantor-Graae, E., & Ismail, B. (2000). Obstetric complications and congenital malformation in schizophrenia. In Brain Research Reviews (Vol. 31, pp. 166–178). https://doi.org/10.1016/S0165-0173(99)00034-X ... View more

One of psychology’s most reliable phenomena is “the overconfidence phenomenon”—the tendency, when making judgments and forecasts, to be more confident than correct. Stockbrokers market their advice regarding which stocks will likely rise while other stock brokers give opposite advice (with a stock’s current price being the balance point between them). But in the long run, as economist Burton Malkiel has repeatedly demonstrated, essentially none of them beat the efficient marketplace.   Or consider psychologist Philip Tetlock’s collection of more than 27,000 expert predictions of world events, such as the future of South Africa or whether Quebec would separate from Canada. As Nathan DeWall and I explain in Psychology, 12 th Edition, His repeated finding: These predictions, which experts made with 80 percent confidence on average, were right less than 40 percent of the time. Nevertheless, even those who erred maintained their confidence by noting they were “almost right.” “The Québécois separatists almost won the secessionist referendum.”   My fellow Worth Publishers text author and Nobel laureate economist, Paul Krugman, has described similar overconfidence and reluctance to admit error among economists and politicians. When Bill Clinton raised taxes on the rich, conservative politicians and economists predicted economic disaster—but the economy instead boomed, with 23 million jobs added during the Clinton years. When Kansas politicians passed large tax cuts with the promise that growth would pay for them, the result was an unexpected state funding crisis. When, in 2008, the Federal Reserve responded to the recession by cutting interest rates to zero, conservative economists and pundits published an open letter warning of soaring inflation to come. But it hasn’t.   When none of the predicted economic outcomes happened, did the forecasters own their error and change their thinking? Contacted by Bloomberg, not one of the inflation open letter signatories acknowledged error. Instead, they offered (in Krugman’s words) “some reason wrong was right … and never, ever, an admission that maybe something was wrong with [their] initial analysis.” Overconfidence—the human bias that our own Nobel laureate, Daniel Kahneman, would most like to eliminate—feeds another potent phenomenon, “belief perseverance”—our tendency to cling to our beliefs in the face of contrary evidence. The more we explain why our beliefs might be true, the more they persist. Thus we welcome belief-supportive evidence—about climate change, same-sex marriage, or the effects of today’s proposed tax cuts—while discounting contrary evidence. To believe is to see.   Perhaps, then, we should all aspire to a greater spirit of humility. Such recognizes, as I have written elsewhere, that We are finite and fallible. We have dignity but not deity. [Thus] we should hold our own untested beliefs tentatively, assess others ’ ideas with open-minded skepticism, and when appropriate, use observation and experimentation to winnow error from truth. ... View more

“It’s official: Dog owners live longer, healthier lives” reads the headline on Time’s website. The refreshing change is that the headline – and the article – carefully explain that the data are correlational, not causal (MacMillan, 2017). When this article appeared in my local paper, The Seattle Times, it came with a sub-headline: “It may be correlation, not causation, but the risk of death was about 33 percent lower for dog-owners than non-owners, a study found.” You won’t be surprised to hear that the journalist, Amanda MacMillan, has a BA in journalism/science writing with minors in “science, technology, and society” and physics [shout out to Lehigh University, her alma mater.] Researchers looked at national records for 3.4 million people in Sweden over a 12-year span. Those records included whether the people registered a dog and their health reports. “Dog ownership registries are mandatory in Sweden, and every visit to a hospital is recorded in a national database.” Researchers learned that “[p]eople who lived alone with a dog had a 33% reduced risk of death [over that 12-year span], and an 11% reduced risk of cardiovascular disease, than people who lived alone without a dog.” The findings were less pronounced for people who lived with other people, I’m going to put this study into my correlation lecture. After sharing these results, I’ll ask students to work in pairs to generate possible reasons for these relationships and then share their ideas with the class. This is a nice opportunity to show that while correlations do not tell us about cause and effect, they provide a goldmine of hypotheses for future research. One possibility, the article points out, is that owning a dog causes better health in the owner: owning a dog causes people to be more active (“gotta walk the dog”). Or dogs may share their microbiome with their owners, giving their human immune systems a boost – as I reflect on how I woke this morning with my dachshund standing on my head and licking my face. Or by walking our dogs, we meet people, extending our social network; social networks are also correlated with better health. Another possibility, the article also points out, is that more active (read “healthy) people are more likely to get a dog. And then there are the third variables. For example, “[o]ther studies have suggested that growing up with a dog in the house can  decrease allergies and asthma  in children.” It may be that having a dog growing up made people more likely to get a dog as an adult and that the exposure to dogs as children gave us a stronger adult immune system. As instructors of psychological science, let’s continue to help our students understand what research does and does not tell us, so that when they get jobs as journalists, they can accurately interpret research findings for the general public as this journalist has done.   References MacMillan, A. (2017, November). It’s official: Dog owners live longer, healthier lives. Retrieved from http://time.com/5028171/health-benefits-owning-dog/ ... View more

Here are some survey data your students may find interesting. This will be most compelling for your psychology majors. The American Psychological Association (APA) mined the data from the 2015 National Survey of College Graduates (NSCG) and learned some interesting things about psychology’s bachelor’s degree recipients (American Psychological Association, 2017). The NSCG estimates that there are about 58 million people in the United States with a bachelor’s degree; that probably includes you. The NSCG sampled 135,000 of them in 2015 (National Science Foundation, 2017).    After covering survey research in, say, Research Methods, ask students to work in groups to take a few minutes and think of what variables they would include in such a survey and why. Ask each group, in turn, for one variable that no other group has yet mentioned. Write the variables on the board (or computer screen) as groups report out. Keep rotating through the groups until all variables have been reported or as time allows. Next, share with students this list of key variables (scroll to 2.h.) included in the NSCG survey. Ask students if there are any groups they would exclude from the survey. The NCSG excludes people who are institutionalized, who live outside the U.S., and who are 76 years old or older (scroll to 3.b). Ask students what kind of sampling design they would use. The NCSG used stratified sampling on “demographic group” (with “an oversample of young graduates), “highest degree type,” and “occupation/bachelor’s degree field” (scroll to 3.c.). Researchers started with a web survey. For those who didn’t respond to that, researchers sent them a survey in the mail. And for those who didn’t respond to that, they got a phone call for “computer-assisted telephone interviewing” (scroll to 4.a.). What did APA find in that 2015 survey data about those of us with bachelor’s degrees in psychology (American Psychological Association, 2017)? 4 million people in the U.S. have at least a bachelor’s degree in psychology 2% got a master’s degree in psychology 8% got a master’s degree in psychology first and then went on to complete a doctorate/professional degree in psychology 3% got a master’s degree in something else and then a doctorate/professional degree in psychology 7% directly earned a doctorate/professional degree in psychology, bypassing the master’s degree   Adding up those numbers, that’s 13%. What about the other 87% of psychology bachelor’s degrees holders? 30% earned a masters or doctorate/professional degree in something other than psychology 57% did not earn a graduate degree Those 30% who earned a graduate degree in something else is nice evidence that a psychology degree is a good all-purpose sort of degree. The father of one my students took his bachelor’s in psychology to law school. He is now a judge. I wish all judges had degrees in psychology! Those 57% who did not earn a graduate degree are undoubtedly putting their psychology degrees to good use, no matter what they are doing. Although some of them aren’t fully cognizant of what their education is doing for them now. Give students a copy of the American Psychological Association Guidelines for the Major. Divide students into groups, and give each group two possible jobs a person might have. Drew Appleby’s list is a nice one to choose from. Ask each group to put a checkmark for each job on their Guidelines for the Major the knowledge and skills (outcomes) that would be useful to have in their assigned jobs. For each outcome have one person in each group raise their hand if the group thought the outcome was important for one of their jobs. Have two persons in each group raise their hands if they the outcome was important for both of their jobs. Tally the number of hands for each outcome. Give students an opportunity to share why they thought particular knowledge and skills (outcomes) is important and how the psychology major is helping them achieve that knowledge and skills. For any holes in your students' observations, let them know where in the curriculum students are gaining that knowledge and those skills. ... View more

As if cell phone use in cars isn’t bad enough, car manufacturers are building distractions into our automobiles, which I affectionately call Built-in Automotive Driving Distraction Systems TM . Automakers now include more options to allow drivers to use social media, email and text. The technology is also becoming more complicated to use. Cars used to have a few buttons and knobs. Some vehicles now have as many as 50 buttons on the steering wheel and dashboard that are multi-functional. There are touch screens, voice commands, writing pads, heads-up displays on windshields and mirrors and 3-D computer-generated images (Lowy, 2017). In an attempt to save lives, I have been hammering pretty hard on our inability to multi-task in my Intro Psych course. While this topic comes up in greater detail when I cover consciousness, I also embed examples of attention research in my coverage of research methods. Correlation example After I introduce the concept of correlations, I give my students 5 correlations, and ask them to identify the correlation as positive, negative, or no correlation. One of those correlations comes from a 2009 Stanford study reported by NBC News: people who multitask the most are the worst at it (“memory, ability to switch from one task to another, and being able to focus on a task”) (“Multitaskers, pay attention -- if you can,” 2009). Experiment example In talking about experimental design, I discuss David Strayer’s driving simulation research at the University of Utah. His lab’s research is easy for students to understand and the results carry a punch. I give this description to my students and ask them to identify the independent variable and the dependent variables. In an experiment, "[p]articipants drove in a simulator while either talking or not talking on a hands-free cell phone." Those who were talking on a cell phone made more driving errors, such as swerving off the road or into the wrong lane, running a stoplight or stop sign, not stopping for a pedestrian in a crosswalk, than those who were not talking on a cell phone. Even more interestingly, those who were talking on a cellphone rated their driving in the simulator as safer as compared to those who weren't talking on a cellphone. In other words, those talking on the cellphone were less likely to be aware of the driving errors they were making (Sanbonmatsu, Strayer, Biondi, Behrends, & Moore, 2016).   Class demo When Yana Weinstein of LearningScientists.org posted a link to a blog she wrote on a task switching demo (Weinstein, 2017) to the Society for the Teaching of Psychology Facebook page, I thought, “Now this is what my research methods lecture was missing!” I encourage you to read Weinstein’s original demo once you’re done reading mine.   I randomly divided my class into two groups. To do that I used a random team generator for Excel, but use whatever system you’d like. Weinstein does this demo with a within subjects design which, frankly, makes more sense than my between subjects design, but in my defense I’m also using this demo to help students understand the value of random assignment.   One group of students recited numbers and letters sequentially (1 to 10 and then A to J). The other group recited them interleaved (1 A 2 B 3 C, etc.). In your instructions, be clear that students cannot write down the numbers/letters and just read them. That’s a different task! Students worked in small groups. While one student recited, another student timed them with a cellphone stopwatch app. (You don’t have to know anything about cellphone stopwatch apps. Your students can handle it.) I didn’t bother dividing students into groups by task. In one group, there might have been three students who recited sequentially and a fourth student who recited interleaved. I asked students to write down their times, and then I came around to each group and asked for those times. I just wrote the times on a piece of paper, and displayed the results using a doc camera. Almost everyone in the sequential condition recited the numbers/letters in under 6 seconds. Almost everyone in the interleaved condition took over 13 seconds. In addition to talking about the independent variable (and experimental and control conditions) and the dependent variable, we talked about the value of random assignment. I had no idea who could do these tasks quickly or slowly. If 20% of them could do these tasks quickly, then random assignment would likely create two groups where the percentage of fast-task participants would be the same in each group. Is it possible that all of the fast-task participants ended up in the sequential task condition? Yep. And that’s one reason replication is important. Oh. And when you’re studying or writing a paper, students, this is why you should keep your phone on silent and out of sight. If you keep looking at your phone for social media or text notifications, it’s going to take you a lot longer to finish your studying or finish writing your paper. Perhaps even twice as long. And driving? As you switch back and forth from driving to phone (or from driving to Built-in Automotive Driving Distraction Systems TM ), it’s not going to take you twice as long to get to your destination. You’re traveling at the same speed, but you’re working with half the attention. That increases the chances that you will not get to your destination at all.   A lot of what we cover in Intro Psych is important to the quality of students’ lives. Helping students see our inability to multitask is important in helping our students – and the people they are near them when they drive – stay alive.   References Lowy, J. (2017, October 5). Technology crammed into cars worsens driver distraction. The Seattle Times. Seattle. Retrieved from https://www.seattletimes.com/nation-world/new-cars-increasingly-crammed-with-distracting-technology-2  Multitaskers, pay attention -- if you can. (2009). Retrieved from http://www.nbcnews.com/id/32541721/ns/health-mental_health Sanbonmatsu, D. M., Strayer, D. L., Biondi, F., Behrends, A. A., & Moore, S. M. (2016). Cell-phone use diminishes self-awareness of impaired driving. Psychonomic Bulletin & Review, 23 (2), 617–623. https://doi.org/10.3758/s13423-015-0922-4 Weinstein, Y. (2017). The cost of task switching: A simple yet very powerful demonstration. Retrieved from http://www.learningscientists.org/blog/2017/7/28-1  ... View more

In an earlier blog post , I reported on an analysis of 34,000+ Americans’ health interviews with the Centers for Disease Control and Prevention (CDC). To my astonishment, Megan Traffanstedt, Sheila Mehta, and Steven LoBello found no evidence that depression rises in wintertime, or that wintertime depression is greater in higher latitudes, in cloudy rather than sunny communities, or on cloudy days. Moreover, they reported, even the wintertime “dark period” in northern Norway and Iceland is unaccompanied by increased depression.   Given the effectiveness of light therapy and the acceptance of major depressive disorder “with seasonal pattern” (DSM-5), I suspected that we have not heard the last word on this. Indeed, criticism (here and here) and rebuttals (here and here) have already appeared. Reading Seth Stephens-Davidowitz’s wonderful new book on big data mining inspired me to wonder if Google depression-related searches increase during wintertime. (To replicate the CDC result, I focused on the United States, though further replications with Canada and the UK yielded the same results.)   First, I needed to confirm that Google Trends does reveal seasonally-related interests. Would searches for “basketball” surge in winter and peak during March Madness? Indeed, they do: We know that Google searches also reveal seasonal trends in physical illnesses. And sure enough, “flu” searches increase during the winter months. So, do searches for “depression” (mood-related) and “sad” similarly surge during wintertime? Nope, after a summer dip, they remain steady from mid-September through May: Ditto for Google entries for “I am depressed” and “I am sad.” My surprise at the disconfirmation of what I have taught—that wintertime depression is widespread—is like that experienced by my favorite detective, Agatha Christie’s Miss Marple : “It wasn’t what I expected. But facts are facts, and if one is proved to be wrong, one must just be humble about it and start again.”   [Note to teachers: you can generate these data in class, in real time, via Trends.Google.com.] ... View more

Looking for a great summer read? If you like Nate Silver’s quantitative assessments of politics and sports, you will love Seth Stephens-Davidowitz’s new book on big data revelations about our human interests, traits, and behaviors. By drilling down through millions of data points, often from people’s anonymous Google searches, he offers insights into racial prejudice, sexual orientation, child abuse, and even the age at which people’s long-term sports loyalties crystallize.   With data science he can also test popular ideas. Was Freud right to suppose that phallic symbols in dreams, and innuendos in word slips, reveal our unconscious sexuality? Is the man who dreamed of eating a banana on his wedding day “secretly thinking of a penis”? Is typing “lipsdick” when you meant “lipstick” an eruption of your hidden desire?   In search of answers, Stephens-Davidowitz analyzed whether phallic-shaped foods “sneak into our dreams with unexpected frequency.” His answer: They do not. In dreams, bananas are the second most common fruit . . . and they also are the second most consumed fruit. Cucumbers are the seventh most dreamt vegetable, and the seventh most consumed vegetable.   In search of Freudian slips, he analyzed 40,000 typing errors collected by Microsoft. A few were sexually tinged—“sexurity” instead of “security,” and “cocks” instead of “rocks.” But then there also were innocent slips such as “pindows,” “fegetables,” and “aftermoons.” After analyzing the frequency of various errors in random typos, Stephens-Davidowitz concludes that “People make lots of mistakes.” And when you make enough, you can expect an occasional and statistically predictable miscue. Searching the quarter million e-mails I’ve received since 2000, for example, I see that friends have written me about their experiences with “Wisconsin Pubic Radio,” with hearing access in “pubic venues” and with “pubic access,” and in their work as a national organization’s “Director of Pubic Policy.”   Thus, “Freud’s theory that errors reveal our subconscious wants is indeed falsifiable—and, according to my analysis of the data, false.” ... View more

On rare occasion, I have reported startling findings that challenge current wisdom: Brain training games do NOT boost intelligence. Traumatic experiences are NOT often repressed. Seasonal affective disorder (wintertime blues) is NOT widespread.   The just-arrived lectures from the 2016 Bial Symposium on Placebo Effects, Healing and Meditation, offers another shocker: In an update on his meta-analyses, Irving Kirsch concludes that antidepressant drug effects are close to nil.   Here’s Kirsch’s gist: Many, many studies, including unpublished drug trials made available by the FDA, consistently show that Antidepressants work. They produce clinically significant benefits (using a standard depression scale). Placebos work, too. In two large meta-analyses, placebos produced 82 percent of the antidepressant effect. Moreover, “the difference between drug and placebo is . . . so small that clinicians cannot detect it.” Side effects can “unblind” a drug. The statistically (but not clinically) detectable drug effect may be attributable to antidepressants’ detectable side effects. The FDA only counts “successful trials.” Kirsch reports that despite meager evidence of antidepressant efficacy, the drugs gain approval because of a stunning FDA policy—which ignores trials that find no drug effect and reports only successful trials. “All antidepressant drugs seem to be equally effective.” As one would expect from a placebo effect, the benefits of various antidepressant drugs are “exactly the same regardless of type of drug.” Various serotonin-increasing drugs relieve depression, but so does a drug that decreases serotonin! “What do you call pills, the effects of which are independent of their chemical composition?,” asks Kirsch. “I call them ‘placebos.’”   Given that antidepressants work, even if they are hardly more than active placebos, what’s a clinician to recommend? Kirsch notes three considerations: Antidepressants have side effects, which can include sexual dysfunction, weight gain, insomnia, and diarrhea. Antidepressant use increases the risk of relapse after recovery. Cognitive behavioral therapy, acupuncture, and physical exercise also effectively treat depression. Ergo, “When different treatments are equally effective, choice should be based on risk and harm, and of all of these treatments, antidepressant drugs are the riskiest and most harmful. If they are to be used at all, it should be as a last resort.” But surely this is not the last word. Stay tuned for more findings and debate. ... View more

The Lancet reports that 15.3 percent of all humans are daily smokers. Yet smoking varies enormously, from: 25 percent among men to 5 percent among women, and from 43 percent among Greenlanders to 1 percent among Sudanese. Even the gender difference varies dramatically, from: nonexistent among Icelanders, where 14.4 percent of women and 14.5 percent of men smoke, to huge among Armenians, where nearly half (43.5 percent) of men and virtually no women (1.5 percent) are smokers. A question: What else do we know about all humanity (apart from our shared physiology)? Here is my short list. Do you know of more? If so I’d love to hear from you.  Human life expectancy: 71 years but with huge variation—from 39 years in Sierra Leone to 84 years in Japan. Humans overweight: 37 percent of men and 38 percent of women but with huge variation—from 3 percent in Timor-Leste to 85 percent in Tonga. Human religiosity: 68 percent say “Religion is important in my daily life” but with huge variation—from 16 percent in Estonia to 100 percent in Niger. Humans employed full time by an employer: 26 percent  but with huge variation—from 19 percent of women to 33 percent of men, and with child-free women varying from 11 percent employed in North Africa to 67 percent in Russia. The bottom line: We humans are kin. But how we differ!   Caiaimage/Robert Daly / OJO+/Getty Images ... View more

After covering experiments or as a research methods boost when covering attractiveness, pose this hypothesis to your students: Tattoos on men influence how others perceive the men’s health and attractiveness. Ask students to design an experiment to test this hypothesis, identifying the independent variable (including experimental and control conditions) and the dependent variables. In the design of the experiment, how would students eliminate any potential confounding variables? Circulate among groups as students work through the design. As discussion dies down, ask volunteers to share their experimental designs. Now share with students the experiment conducted by Andrzej Galbarczyk and Anna Ziomkiewicz (2017) using over 2,500 Polish participants recruited through Facebook; all participants self-identified as heterosexual. Researchers used nine non-tattooed male models, photographed from the waist up and without shirts for the control condition. “A professional photographer digitally modified the pictures by adding a black arm tattoo with an abstract, neutral design” for the experimental condition. This means that the only difference in the conditions was the tattoo. Participants were randomly assigned to see one photo for each model pair, and in the nine photos seen, each participant saw at least one tattooed model and one non-tattooed model. The dependent variables were ratings of attractiveness, health, dominance, aggression, fitness as a partner, and fitness as a father. Data were analyzed separately for male and female research participants. Before revealing the results, ask students to predict how the participants responded. Using clickers or a show of hands, ask students: Who did women rate as healthier? Tattooed men Non-tattooed men No difference [Women rated the tattooed men as healthier] Who did men rate as healthier? Tattooed men Non-tattooed men No difference [Men didn’t see a health difference between tattooed and non-tattooed men.] Who did women rate as more attractive? Tattooed men Non-tattooed men No difference [Women didn’t see a difference in attractiveness between tattooed and non-tattooed men.] Who did men rate as more attractive? Tattooed men Non-tattooed men No difference [Men rated the tattooed men as more attractive.] Who did men and women rate as more masculine, dominant, and aggressive? Tattooed men Non-tattooed men No difference [Tattooed men.] Who did women rate “as worse potential partners and parents”? Tattooed men Non-tattooed men No difference [Tattooed men.] Who did men rate “as worse potential partners and parents”? Tattooed men Non-tattooed men No difference [No difference.] Ask students to volunteer guesses as to why women would see tattooed men as healthier than non-tattooed men. And why men would see tattooed men as more attractive than non-tattooed men. The article’s authors offer a number of possible explanations, all worthy of further research.    REFERENCE Galbarczyk, A., & Ziomkiewicz, A. (2017). Tattooed men: Healthy bad boys and good-looking competitors. Personality and Individual Differences, 106, 122-125. doi:10.1016/j.paid.2016.10.051 ... View more

After introducing correlations, I share a number of examples with students. Here are couple new ones that going into my pool. Young adults (age 19-32) who spend their time on a lot (7 to 11) of different social media platforms are more likely (than those who spend their time on 0 to 2 different social media platforms) to report symptoms of depression. That same relationship exists between the number of different social media platforms and anxiety (Primack, et.al., 2017). Ask students if these represent a positive, negative, or zero correlation (clicker question, show of hands, shout out). (Both correlations are positive.) If students say negative, they may be caught in the trap of thinking that this is a “bad thing,” so it’s negative. Remind students that that is not what positive and negative mean in this context. It can help students in identifying correlations to first note what the two variables are (“number of social media platforms used” and “depression”; “number of social media platforms used” and “anxiety”) and then sort out whether those variables are moving in the same direction (positive) or opposite directions (negative). Next, to help students see that correlations don’t mean causation, ask students to consider the causes, why anxiety and depression may be related to the number of social media platforms used. In think-pair-share, give students a couple minutes to jot down their thoughts, then give students a couple minutes to share their ideas with one or two classroom neighbors, then ask for volunteers to share their thoughts. Students may surmise that jumping from one social media platform to another may cause depression or anxiety. The authors note three possibilities here: “participation in many different social media platforms may lead to multitasking between platforms, which is known to be related to poor cognitive and mental health outcomes;” since each platform has its own rules and customs “as the number of platforms used increases, individuals may experience difficulty navigating these multiple different worlds successfully, leading to potentially negative mood and emotions;” and the more social media platforms you are on you run an “increased risk of damaging gaffes.” Students may also surmise that those who are depressed or anxious may choose to jump from one social media platform to another. The authors suggest “[t]his may be because these individuals tend to search multiple avenues for a setting that feels most comfortable and in which they feel most accepted.”  A third possibility is that something else, a third variable, could be affecting both social media use and depression/anxiety, perhaps loneliness. Those who are more isolated may be more likely to seek out community in social media and being more isolated may contribute to depression/anxiety. Remind students that the value in correlations comes from revealing a relationship between two variables. Students identified a number of possible reasons as to why there is a relationship between those variables. The next step is to do more research on which of those possibilities are right -- and it may be one, some, or all of them.  Side note. Even though their research is clearly correlational, the article's authors are comfortable suggesting that it’s the social media use that’s causing or at least contributing to depression/anxiety. They write “it may not be too soon to suggest that individuals with depressive and/or anxiety symptoms, and who use a high number of different social media platforms may wish to decrease the number of platforms used.” Ask students if this is a fair statement for the authors to make.    Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among U.S. young adults. Computers in Human Behavior, 69, 1-9. doi:10.1016/j.chb.2016.11.013 ... View more

A political science grad student, Kevin Munger (2016a, b), decided to conduct an experiment on Twitter. His goal was to reduce the amount of hate speech posted to that media platform. To that end, he searched Twitter for a particular racial slur and sent every writer of such a tweet the same message: “@[subject]   Hey man, just remember that there are real people who are hurt when you harass them with that kind of language.” But that’s not all. Munger reasoned that the impact of the message on future use of racial slurs likely depends on the communicator of that message, such as the perceived race and status of the person who is sending the reminder of the impact of language. Munger created four Twitter accounts: “High Follower/White; Low Follower/White; High Follower/Black; and Low Follower/Black.” The high followers had over 500 followers whereas the low followers had two followers. The White accounts displayed a White avatar and had a more stereotypically White-sounding name, Greg. The Black accounts displayed a Black avatar and had a more stereotypically Black-sounding name, Rasheed. Following Munger’s be-nice tweet, Munger tracked daily use of the racial slur over the next two months. The results. When Munger’s twitter account was High Follower/White, the number of racial slurs dropped .3 per day, the highest of any group. High status ingroup members do have power to influence. With about an equal, but smaller, decrease in daily use of racial slurs where the High Follower/Black and Low Follower/White avatars, although these differences disappeared within a few weeks (Munger, 2016b). Ingroup membership and high status both have an immediate, but not lasting impact, all on their own. What about Low Follower/Black? No Impact. In Intro Psych, you can give your students a little practice with experimental design by using this article at the beginning of the course when you cover research methods or as a research methods refresher later in the course when you cover social psychology. Ask students to identify the independent variables and dependent variable. The response to Munger’s missive wasn’t uniform; reponses differered by the anonymity of the Twitter user who received Munger’s message. Munger looked at the profiles of the Twitter users in his experiment. Of those users who were not anonymous, Munger reports that the High Follower/White Twitter account had no impact on the ensuing use of racial slurs. But the Low Follower/Black Twitter account “actually caused an increase (emphasis in original) in the use of racist slurs.” These were largely directed at Munger’s Twitter account that sent the be-nice message. Shout out to Danae Hudson (Missouri State University) for finding this article and suggesting this activity!   References Munger, K. (2016a, November 17). This researcher programmed bots to fight racism on Twitter. It worked. Retrieved from https://www.washingtonpost.com/news/monkey-cage/wp/2016/11/17/this-researcher-programmed-bots-to-fight-racism-on-twitter-it-worked Munger, K. (2016b). Tweetment effects on the tweeted: Experimentally reducing racist harassment. Political Behavior. doi:10.1007/s11109-016-9373-5 ... View more

Authors of Discovering the Scientist Within: Research Methods in Psychology ,  Gary Lewandowski, Natalie Ciarocco and David Strohmetz are all active researchers and committed teachers at Monmouth University. They’re excited to engage in a conversation about the Research Methods course, why it is so important, and talk about how they solve challenges in their own classrooms. Check out their Facebook live video from 11/4! Please feel free to leave any questions below or directly on the Facebook video and the authors will respond! ... View more

Originally posted on October 18, 2016.  For both graduate students and instructors alike, there are many reasons to teach a research methods course. From demand for professors to the ability to harbor student skills, these pragmatic approaches to teaching an engaging course are beneficial for students and instructors. Read more about my approach to teaching research methods on TeachPsych: http://teachpsych.org/page-1784686/4311450 ... View more

When covering research methods or as a research methods boost in health psych in Intro, ask your students, “Do fitness trackers, like Fitbit, work? If you were a psychological scientist trying to answer this question, how would you do it?” Give students a couple minutes to think about this on their own. Next, ask students to work in pairs or small groups to design an experiment that would help answer this question. As you circulate among the groups, make sure the groups are answering the question “Do fitness trackers work… at doing what?” As discussion is winding down, bring the class back together and ask for groups willing to volunteer their experimental designs. There should be some sort of random assignment to wearing a fitness tracker or not. Ask students why? [Because if you compared existing users with existing non-users, the users may already be more motivated to engage in physical activity.] Ask students to identify the independent variable [fitness tracker usage] and the experimental condition [fitness tracker] and control condition [no fitness tracker]. How long did students think participants should use/not use a fitness tracker to ensure a fair test? Why that amount of time? Ask students to identify the dependent variable(s) [perhaps weight loss]. With class discussion on the design wrapping up, share with students the results of such a study (Jakicic, et.al., 2016). Participants (470 of them) were six months into a 2-year weight-loss study when they were randomly assigned to either wear a fitness tracker that included a website for monitoring diet or self-monitor exercise and diet via a website (74.5% completed the study; every six months, participants were given $100). Note that this study did not have a no-treatment control group. Ask students to predict the results by a show of hands or via an audience response system. A. Fitness-tracker users lost the most weight B. Self-monitors lost the most weight C. Fitness-tracker users and self-monitors lost about the same amount of weight. Ready for the results? Those assigned to wear fitness trackers lost 3.5 kg (7.7 lbs). Those assigned to self-monitor lost 5.9 kg (13 lbs). There were no differences in the groups at the 6-month mark, the point in the study where they were randomly assigned to wear the fitness tracker or self-monitor. But at the next three check-ins (12 months, 18 months, and 24 months), the self-monitoring group had always lost more weight. Did your students guess right? Were they surprised by the results? Some explanations for these results are offered in this NPR story. But before you share these with students, ask students to generate some hypotheses as to why the self-monitoring group lost more weight than the fitness-trackers. If time allows, give students a couple minutes to think on their own before sharing in pairs or small groups.  Ask student volunteers to report out their hypotheses. Write the hypotheses where students can see them. If you’d like to send students off with a take-home assignment, assign students to design an experiment (but not conduct it!) that would test one of the student-generated hypotheses. Students should identify their independent and dependent variables and anything else they would do that would eliminate confounding variables. You can either let students choose the hypothesis, or assign hypotheses by last name, e.g., “If you’re last name begins with A through F, you have hypothesis 1.” Students can submit as a written assignment, or if you have time at the beginning of the next class, give students an opportunity to share their designs with each other, and then take a few minutes to ask volunteers to share their designs.   Reference Jakicic, J. M., Davis, K. K., Rogers, R. J., King, W. C., Marcus, M. D., Helsel, D., . . . Belle, S. H. (2016, September 20). Effect of wearable technology combined with a lifestyle intervention on long-term weight loss: The IDEA randomized clinical trial. Retrieved from http://jama.jamanetwork.com/article.aspx?articleid=2553448 ... View more

Years ago, as a young instructor, I didn’t have the tools to help my struggling students who came to my office for studying advice. I had a clear idea of what “studying” was since I had done it for so long, but I don’t know if it’s that I couldn’t put words to what I did to study or if I assumed that everyone did the same thing when “studying,” and that if that didn’t work, I didn’t know what would. In any case, over time, I got better at my advice – test yourself, space out your studying, for example. One term I had a student who earned a perfect score on an exam. Students in the class knew somebody did, and they asked who it was. I said I couldn’t reveal the person’s name, but that person can if so desired. My perfect-score student immediately said, “I did! And I’m proud of it.” The other students began peppering her with some version of “How did you do it!” She explained that she spent time every day on the class. She read the textbook, took notes, merged her textbook notes with her class notes, thought of examples, tested herself over what she was learning. Students started exclaiming, “Oh! I don’t want to do all of that!” Her response? “Then you don’t get an A.” Learning is hard work. There’s no way around it. For students who are willing and able to put in the hard work, I want them to use effective, research-based study techniques. Unfortunately, students may not know what those research-based study techniques are. Some of the techniques students use may be a complete waste of time. Gurung, Weidert, and Jeske (2010) asked 120 students to complete a questionnaire on 35 different study behaviors. The behaviors that correlated positively with the students’ final exam scores: “attended every class,” “answered every question in the study guide,” “used practice exams to study,” and “was able to explain a problem or phenomenon using the material.” Behaviors that correlated negatively with exam scores: “after class, I looked over my notes to check for and fill in missing information,” “highlighted the most important information in each chapter to review later,” “reviewed the chapter after the lecture on that topic,” “asked… a classmate/friend to explain material I didn’t understand,” and “asked the professor or TAs for additional materials.” Interestingly, when they looked at just the top half of exam performers, only one correlation remained. Those who reported highlighting as a study strategy scored lower than those who did not. Highlighting is easy to do – it’s too easy to do. It doesn’t require deep processing; it’s a very shallow process. But at the end, with words highlighted, it’s easy to fool oneself into thinking studying was accomplished. Highlighting is really just coloring – and there are reasons coloring is relaxing: it takes little to no cognitive effort. Now, how about some advice on how to study? Yana Weinstein (UMass Lowell) and Megan Smith (Rhode Island College) of the LearningScientists.org blog have created a wonderful set of posters (slides and sticker templates) to help students learn how to study better. The strategies: spaced practice, retrieval practice, elaboration, interleaving, concrete examples, and dual coding. Side note: I love the use of the very specific word practice instead of the fuzzier word study. Elliott Hammer (2016) reports that “I’m also trying as of late to drop the word ‘study’ from my vocabulary in favor of ‘practice. It’s difficult to get students to be more active in their approach, and I want them to get beyond simply trying to read and call that studying. I don’t have data showing that the switch is working, but it feels more genuine.” To get your students to dive into these learning strategies, after covering the memory chapter, ask students to explain why each strategy is effective based on the concepts and research covered in their reading. This makes a nice out-of-class assignment, but it would also work well done in class with small groups. Give each small group the set of posters to explain the effectiveness of each. After discussion wanes, ask a group to report out on one of the posters; give other groups an opportunity to add to the conversation. Move onto another group, and ask them to report out on a different poster. Continue until all of the posters have been covered. If you use a classroom response system, ask students if they currently use the study strategy and whether they plan to use it in the future. Or you could do a jigsaw classroom. Divide the class into 6 groups of at least 6 members each (or 12 groups of at least 6 members or some other multiple of 6, depending on your class size) and give each group a different poster. (For smaller classes, use multiples of 3 and give each group 2 posters). After each group identifies why the strategy is effective (using the concepts learned in the memory chapter), break apart the groups so that at least one person from each group now forms a new group. Ask each new group member to share the strategy on their poster and explain why the strategy is effective. Bonus: Use the Gurung, et.al. (2010) study as examples when you cover correlations in the research methods chapter. Or use it here in the memory chapter to reinforce correlations. And then ask students which learning strategy is being used in the practice of learning correlations.   References Gurung, R. A., Weidert, J., & Jeske, A. (2010). Focusing on how students study. Journal of the Scholarship of Teaching and Learning, 10(1), 28-35. Hammer, E. (2016, July 31). I’m a member of STP and this is how I teach. Retrieved from http://teachpsych.org/page-1703896/4186852 ... View more