*For all comprehensive exam sections, DO NOT attempt answering a question unless you really know the answer. You will be much less likely to pass if you provide information that does not actually address a question (even if the information you provide is technically accurate, and could be used to answer another question). Also, most questions (except Statistics) will require you to cite original sources to support your arguments, but please do not cite a textbook.

Cognition and Learning Section

This exam is tied most directly to PSY 620 and 621. You are not allowed to attempt this exam until you have passed both of these courses.

You will see questions covering such topics as (in no particular order of importance): perception, attention, working memory, episodic versus semantic versus procedural long- term memory, implicit versus explicit memory, automatic versus controlled processing, categorization, social cognition, metacognition, theories of learning and behavior, eyewitness memory, language, decision-making and problem-solving, expertise, and developmental/age issues concerning memory.

By far the most important thing to study is an undergraduate textbook in cognitive psychology (e.g., Goldstein; Reisberg; Robinson-Riegler; Sternberg), as well as notes and materials from PSY 620.

Below is an example question (no longer used) with a good student response. It will give you an idea of the level of detail needed for a good response, and how to cite original sources to support your statements.

You are an eyewitness to a crime in which a man robs a liquor store. He does so in under 5 minutes while pointing a gun at the clerk, is not wearing a mask or anything else to hide his face, and he quickly runs away after the robbery. A few days later the police present you with a lineup from which your goal is to identify the perpetrator. Utilizing your knowledge of attention and memory, describe what is involved in your ability (or inability) to make an accurate identification from the lineup.

The first factor that might come into play in determining my ability to identify the perpetrator in this robbery would be the presence of a gun. The weapon focus effect (WFE; e.g., Pickel, 1999; see review by Fawcett et al., 2013) predicts that the presence of the gun would turn the gun into the central focus of my attention, and the face of the perpetrator would fall into the periphery of my attention. The WFE also predicts that the context of the situation will determine the strength of the effect. In this case, the gun was in a threatening context where the perpetrator was pointing the gun at the clerk, so the WFE is more likely to occur. In contrast, if the gun would have been in a non-threatening context, such as at a gun range, then the WFE would not be expected to occur. Essentially, the gun would dominate my attentional field, hindering my ability to identify the perpetrator. The second factor that might determine my ability to identify the perpetrator is the presence and influence of misinformation. Misinformation involves a perceiver receiving information contrary to the details of the original event, and that information either replaces or alters the perceiver’s memory for the details of the original event. Loftus and Palmer (1974) conducted a study where participants viewed a video depicting a car accident, and then received misinformation-filled written description about that car accident. In a later recall task, the participant’s recall displayed the infiltration of misinformation and confusion as to whether certain details came from the video or the written description (source misattribution). In the present robbery situation, misinformation could have plenty of opportunity to infiltrate my memory over the course of the “few days” that were in-between the witnessing event and the lineup task. Misinformation could come in the form of co-witness discussion, media coverage, etc. By discussing the robbery events with my co-witnesses, their recall for the event could influence my recall for the event; essentially turning several individual viewpoints for witnessing the crime into one collective memory for how the event occurred or even what the perpetrator looked like. Media coverage of the crime could have the same influence as co-witness information; contaminating my memory with details reported on the news. The infiltration of misinformation could skew my memory for the events and the perpetrator, ultimately hurting my ability to identify the perpetrator in a lineup. The third factor that could influence my ability to identify the perpetrator is the presence and influence of post-identification feedback. Post-identification feedback (PIF) refers to information received by an eyewitness from a line-up administrator that serves to influence the eyewitness’ lineup choice and/or confidence in that choice. Wells and Brewer (1998) were one of the first researchers to conduct an investigation into PIF. In their study, participants viewed a mock-crime, completed a lineup identification task that was either accompanied by positive feedback from the lineup administrator or no feedback, and then completed a survey indicating their confidence in their lineup choice. Participants who received feedback from the administrator were more confident in their lineup choice than those who did not receive feedback even though all of the lineups were target-absent (none of the lineups contained the suspect). This false inflation of confidence could lead an innocent to be arrested and possibly convicted of crime they did not commit. In the current robbery situation, PIF could come into play when the police present me with a lineup task. I could possibly choose someone and be confident in my choice even if my choice is not accurate. Essentially, the police could influence my lineup choice and confidence, which could potentially put an innocent individual at risk. The final factor that could influence my ability to identify the perpetrator is whether or not the perpetrator and I were of the same race. The other-race effect (see review by Meissner & Brigham, 2001) could come into play if the perpetrator and I were of different races. The other-race effect refers to a phenomenon where recognition for individuals of one’s own race is better than recognition for individuals of another race. This recognition preference comes about as a result of more experience with members of one’s own race, and can be seen to take place starting as early as our infancy years. Ultimately, if the perpetrator is of a different race than I may have a more difficult time of picking them out of a lineup just because they are of another race.

Cognition and Instruction Section

This exam is tied to PSY 625. You are not allowed to take it until you have completed this course.

In addition to the PSY 625 materials, you should be aware of the following literature:

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2004). How people learn: brain, mind, experience, and school. Washington, D.C: National Academy Press.

Duckworth, A.L., Gendler, T.S., & Gross, J.J. (2014). Self-control in school-age children. Educational Psychologist, 49(3), 199-217.

Mayer, R. E. (2011). Applying the science of learning to undergraduate science education. Paper commissioned for the committee on the status, contributions, and future directions of discipline-based education research of the National Academies Board of Science Education.

Fyfe, E. R., McNeil, N. M., Son, J. Y., & Goldstone, R. L. (2014). Concreteness fading in mathematic and science instruction: A systematic review. Educational Psychology Review, 26, 9-25.

Graham, M. J. Frederick, J., Byars-Winston, A., Hunter, A-B., & Handelsman, J. (2013) Increasing persistence of college students in STEM. Science, 341, 1455-56.

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2009). Learning styles. Psychological Science in Public Interest, 9, 105-119.

Diamond, A., & Lee, K. (2011). Interventions shown to aid executive function development in children 4 to 12 years old. Science, 333, 959-964.

Snow, C. (2002). Defining comprehension. (Chap 2). Rand National Reading Panel.

McNamara, D. S., Kintsch, E., Songer, N. B., & Kintsch, W. (1996). Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction, 14, 1-43.

Mayer, R. E., Hegarty, M., Mayer, S., & Campbell, J. (2005). When static media promote active learning: Annotated illustrations versus narrated animations in multimedia learning. Journal of Experimental Psychology: Applied, 11, 256-265.

Mayer, R. E., Griffith, E., Jurkowitz, I. T., & Rothman, D. (2008) Increased interestingness of extraneous details in a multimedia science presentation leads to decreased learning. Journal of Experimental Psychology: Applied, 14, 329-339.

Goldin-Meadow, S., Nusbaum, H., Kelly, S. D., & Wagner, S. (2001). Explaining math: gesturing lightens the load. Psychological Science, 12, 516-522.

History, Ethics, and Educational Psychology Section

This exam is tied to PSY 509 and ethics training you receive with the CITI modules required by the university IRB. Do not attempt this exam until both of these are done.

Review a fairly scholarly, fairly comprehensive, textbook on the History of Psychology. Hilgard would be best, but the Hergenhahn or the Thorne & Henley books would suffice. Also, review a “high level” Intro text. It need not even be new. Suggested authors would be Gleitman or Baron.

Be sure and know the contributions of the obvious “big names” in American Psychology that are relevant to either Cognition or Learning or “Education.” This would include (minimally) James, Dewey, Baldwin, Hull, Lashley, Watson, Skinner, Tolman, Darwin, Cajal, Festinger, Kohler, Whorf, Gibson, as well as the “founders” of cognitive science -- George Miller, Roger Brown, Ulric Neisser, Noam Chomsky, Jerome Bruner, etc.

Understand the differences (in both theory and method) between the various “schools” of psychology: Structuralism, Functionalism, Behaviorism, and Gestalt Psychology, as well as modern Cognitive Science.

You should have some understanding of the classic scholarship in the philosophy of science and the history of sciences (e.g., Kuhn, Feyerabend, Lakatos, Laudan) as it relates to psychology.

You should have a good understanding of the various grand debates in the philosophy of psychology: mind-body, nature-nurture, molar-molecular, etc. You should be able to associate names and specifics with these (e.g., Descartes, Galton).

You should have at least a little knowledge of the relatively recent philosophers that have been interested in psychology and/or social science (Pepper, Popper, Wittgenstein, Ryle, Heidegger, Dennett, Searle, etc).

You should know (by heart) all the parts of the APA’s ethical guidelines that address research.

You should be familiar with CFR 45-46 which outlines the laws that address Human Subjects Research.

You should be able to generate several examples of ethically “problematic” research from the history of psychology (or related disciplines) and understand what makes them “problematic.” For example, “Kallikak” and “Tuskegee” should be meaningful to you in this context.

Statistics and Research Method Section

Do not attempt this exam until you have completed PSY 695 (Research Methodology), 612 (Introduction to Statistics), and 681 (Intermediate Statistics). It would also be advantageous to have taken 610 (nonparametric) and/or 671 (multivariate) too.

1. The student should be mindful that statistics and research methodology are not entirely equivalent. Research methodology entails a way of thinking about answering empirical questions and is as much logical as more traditionally mathematical. Thinking about how to avoid errors that are methodological and not statistical is crucial. Confounding, for example, which can be thought of as the situation that obtains when an independent or predictor variable is correlated with some extraneous variable, is often best resolved by adjusting the organization of planned events and measures in a study more than through indirect statistical procedures, e.g., analysis of covariance.

2. The student should be able to design more than one experiment or research study that answers the same empirical question. For example, one might determine the relationship between moral development and ethical behavior using either an experimental or correlational design, the latter of which may entail multiple regression.

3. Likewise, many empirical questions can best be answered with designs that are blends, such as are available in the general linear model, which permits combining classical experimental designs with regression.

4. The student should be aware of the relationships that might obtain across multiple studies pertaining to the same or similar variables. One can imagine, for example, that replicating a study, with or without modifications or extensions, might serve a useful purpose in some instances and not in others. In a general sense, as well, the student should understand the cumulative nature of research, i.e., the way in which one study builds on the findings of another to produce a progressively more complete picture of a particular set of events.

5. In light of these and other considerations, “statistics” in the narrower sense can be seen as one of a number of tools that the researcher uses to answer the questions s/he confronts as an empirical scientist. Types I and II errors, and power estimates, are not simply memorized definitions but very real ways of describing the nature and limits of what one has observed and measured. Likewise, the underlying theoretical distribution of, say, F, t, or Chi square, is seen as an essential benchmark against which to check empirical measures derived from real participants.

6. The student should see that the nature of one’s measures impacts the way in which one can answer the questions. Here the matter of the statistical probity of various parametric and nonparametric procedures is obviously key in deciding what to use, first as an adequate procedure whose assumptions the data meet, and then, within a general grouping, which procedure best fits the logical organization of the design. In a simple case, for example, the Pearson r works when one is trying to see the relationship between two continuous variables with strong measurement characteristics, but not for two variables that represent simple ordinal rankings. Likewise, even with interval or ratio level data, the Pearson procedure might not be appropriate because of the organization of the study. Random assignment to groups (a controlled categorical grouping) might suggest the appropriateness of a t-test, analysis of variance, or similar more “experimental” statistic.

7. A relative newcomer to the researcher’s tool kit is the notion of effect size. The student should be mindful that, whatever form it occurs in – a function of the statistical distribution that it is used with, effect size is an index of the “heftiness” of the proportion of the variability in the study that the statistically significant effect explains. It answers the “So what?” question. The student should have this sense, as well as a feeling for several different effect size measures (I hesitate to say “statistics”) for correlational procedures, and statistics that are more directly appropriate with experimental and quasi-experimental designs.

Research Methodology

Different types of research methods (i.e., case studies to laboratory experiments). (1) What are the strengths and weaknesses of each approach; (2) What are the potential biases that may appear in different methods (e.g., central tendency effect in surveys; demand characteristics in an experiment).

Although they have their own sections please review ethical issues and the concepts of reliability and validity. Although you are not likely to have a question directly about these topics in this section, nonetheless demonstration of your understanding of these topics may be useful in answering a question.

What are the differences between randomized and non-randomized research designs? Why would you sometimes choose a non-randomized design?

The basis of research in our field is the Scientific Method. Be able to discuss this concept and how it impacts our approach to the search for knowledge.

Statistics

What does statistical significance really mean? What is the difference between statistical and practical significance?

What is the relationship between random sampling and inferential statistics?

What is the difference between parametric and non-parametric designs? Why might you choose one over the other?

Although you are not responsible for formulas, you should know the assumptions that go along with the more common statistical analyses.

Why is variance in your data essential when looking for statistical difference between groups when using the ANOVA model?

What are Type I and Type II errors? What is power? How are these concepts related?

What is effect size? What does it tell us? What role does effect size play in a meta- analysis?

What is the Central Limit Theorem? How is the concept of the sampling distribution related to the CLT? What role do these concepts play in the inferential process?

Know about probability theory, including Bayes’ Theorem.

Understand the characteristics of the normal distribution, standard normal distribution, and z.

Understand what it means to control for Type I error rate, why this is important, and different ways of accomplishing this statistically.