Exam Prep: Logistics, Study Tips, and Research Methods
Exam One Logistics
Weighting: This exam is weighted slightly lighter than subsequent exams, providing room for students to adjust studying if needed for future exams.
Cumulative Elements: Exams may have some cumulative elements. While primarily focusing on recent material, earlier concepts might reappear, especially foundational ones due to the building nature of the course material.
Content Coverage: The exam will cover material from both assigned readings and class lectures.
Focus: Instructor emphasizes that topics covered in both lecture and reading are most likely to appear on the exam.
Format: In-class, paper-based exam.
Time: Conducted within the regular class block.
Closed Book: No notes or electronic devices are permitted during the exam.
Accommodations: Students with approved accommodations through Accessible Education Services (AES) should have already arranged these. The instructor will have been in touch regarding special arrangements.
Late Arrival: Students arriving late will be allowed to take the exam but will lose the equivalent amount of time from their allocated duration.
Materials to Bring: Students should bring something to write with, preferably a pencil, for filling out bubble sheets (allows for erasing and changing answers).
Test Booklet Usage: Students are permitted to write notes, circle questions, or make any marks on the test booklet itself before transferring answers to the bubble sheet.
Question Format: All questions will be multiple-choice or similar formats (e.g., matching, true/false), requiring a bubble letter answer. There will be no written response questions (long or short answer).
Number of Questions: Approximately to questions.
Time per Question: This allocates about minutes per question, which is generally considered ample time.
Question Philosophy: Questions are designed to be straightforward, challenging students to learn and apply concepts, sometimes integrating multiple concepts (e.g., research methods applied to specific people's work).
Best Answer Selection: Always select the best available answer, even if there seems to be slight ambiguity. The goal is one correct answer.
No Questions During Exam: To maintain fairness across different testing environments (e.g., accommodated testing locations), the instructor will not answer questions during the exam.
If a fundamental error is suspected (e.g., no correct answer, multiple correct answers), students should answer to the best of their ability and raise the issue after the exam (that day, office hours, or email).
Mistakes on the instructor's part (e.g., two correct answers) will be adjusted (e.g., accepting either answer, dropping the question).
For logistical issues (e.g., unprinted booklet parts), notify the instructor immediately.
Makeup Exam: A makeup exam will be available within the week following the original exam date for illness, emergency, or unavoidable conflicts. Students are encouraged to reach out if they anticipate missing the exam.
Study Guide: A study guide for Exam One has been posted on Canvas, located in the course resources module. It lists potential questions and topics to direct students' attention to key areas, although it's not exhaustive with detailed answers.
Effective Study Strategies
Beyond Rereading: Simply rereading notes or textbook material is not the most effective study method, though not harmful.
Familiarity vs. Free Recall: Rereading primarily triggers familiarity-based memory (recognizing something seen before) rather than free recall memory (retrieving information from one's own memory), which is crucial for tests and real-life application.
False Confidence: Familiarity can create a false sense of confidence; seeing something repeatedly makes it feel known, but actual recall ability might be limited.
Example (State Capitals):
Familiarity Task: A person studying state capitals will perform much better at identifying those capitals from a list of items.
Free Recall Task: The same person would find it much harder to write down all state capitals from memory on a blank sheet of paper.
Even multiple-choice tests often require more than mere familiarity; they challenge the ability to retrieve information.
Active Recall Approaches (Stronger Study Methods):
Self-Testing with Study Guide Questions: Students can look at a study guide question and try to produce their own answer (thinking, speaking aloud, or writing it down).
Writing it Down: Writing answers allows for checking against notes/textbook to confirm accuracy and identify areas needing more review.
Flashcards: Looking at one side and actively recalling the information on the other side before checking for confirmation.
Exam Accommodations Reminders
Students with exam accommodations should set up their appointments with the testing center immediately, as the recommended sign-up period is at least days prior to the exam.
If unable to sign up, contact the testing center first, then email the instructor.
It's also advisable to sign up for future exams if possible.
Importance of Understanding Research Methods
For Researchers: Directly vital for conducting research projects.
For Consumers of Research: Valuable for various applications:
Clinicians: Understanding populations, evaluating the latest treatments, and determining their applicability to specific clients.
Public Policy/General Population: Forming informed opinions on community, family, and personal decisions.
Critical Evaluation: Understanding research methods helps to:
Assess trustworthiness of research.
Evaluate methodology (e.g., sample size).
Determine if conclusions align with the research conducted.
Judge the applicability of findings to one's specific context (e.g., client population).
Questions Answered by Research in Psychopathology
Problem Identification: Which problems cause distress and impair functioning? (Shapes individual outcomes).
Causation: Why do people behave in unusual ways? (Causes of disorder).
Treatment Efficacy: How do we help people behave in more adaptive ways? (What works in treatment).
Components of a Research Study
Research Question
Definition: What researchers aim to answer.
Scope: Can range from broad (e.g., "What helps people with depression?") to narrow and specific.
Narrow Questions: A specific study addresses a more focused question, detailing:
Specific treatment being investigated.
Specific population/sample.
Specific outcomes measured (e.g., academic performance, social success).
Example: "Do SSRI drugs help adolescents with depression on academic and social outcomes?"
Hypothesis
Definition: An educated guess or prediction about what will be found in a particular study.
Specificity: Directly answers the narrow research question with a predicted outcome.
Example: "The research team predicts that SSRI drugs will help adolescents with depression improve specifically on scores of academic and social outcomes."
Foundation: Based on existing research and theoretical frameworks.
Testability: Must be capable of being supported or refuted by collected data; data must be collectable to address the hypothesis.
Research Design
Definition: The overall plan for how all pieces of a research project (research question, hypothesis, methods) come together.
This includes the plan for testing the hypothesis.
Key Design Considerations:
Sample: Who is participating directly (e.g., in treatment or control group).
Population: The broader group the sample is intended to represent, to whom study conclusions ideally generalize.
Example: A sample of college students from the US aiming to make conclusions about the entire population of college students in the US.
Treatment/Intervention: Details of what is provided or done with participants.
Measurement: What and how variables are measured.
Variables: Identification of independent and dependent variables.
Ethical Limitations: Consideration of what is ethically permissible.
Practical Constraints: Time and financial resources available.
Independent and Dependent Variables
Independent Variable (IV):
Definition: The variable that researchers manipulate or change.
Purpose: To observe what impact this manipulation has on another variable.
Example (Depression Study): Whether people receive SSRI drugs, talk therapy, a combination, or no treatment.
Context: Primarily used in experimental studies where random assignment to conditions occurs.
Dependent Variable (DV):
Definition: The variable that is measured by the researcher, expected to change as a result of the independent variable's manipulation.
Example (Depression Study): Scores on a depression scale, academic performance, or social outcomes.
Predictor and Outcome/Response Variables:
Context: Used in non-experimental research (e.g., correlational studies) where variables are observed for relationships rather than manipulated.
Predictor Variable: A variable thought to shape, influence, or predict an
outcome variable(similar to an IV but not manipulated).Example: Gender in a study looking at how depression rates vary by gender (gender predicts depression rates, but isn't manipulated).
Outcome/Response Variable: The variable that is predicted or influenced (similar to a DV but not directly impacted by manipulation).
Terminology: While independent/dependent variables are common in experimental settings, predictor/outcome or response variables are used for correlational or observational relationships. Statistical literature may use a dozen different terms.
Validity
Internal Validity
Definition: The extent to which observed results in a study were genuinely caused by the treatment or intervention provided, meaning changes in the dependent variable can be confidently attributed to the independent variable.
Question: Did we set up the study correctly to avoid other explanations for the observed changes?
Factors Supporting Strong Internal Validity:
Avoiding Confounds (Confounding Variables): Ensuring that if groups receive different treatments, they are treated identically in all other respects.
Example: If anxiety treatments 'A' and 'B' are given at 10 AM and 2 PM, respectively, time of day becomes a confound. If 2 PM appointments generally lead to more anxiety, this could falsely appear as an effect of treatment 'B'. To avoid this, appointments should be randomly assigned across treatments.
Random Assignment: Participants should have an equal chance of being assigned to any of the different treatment or control groups.
This helps ensure that any observed differences are due to the treatment, not pre-existing differences between groups (e.g., self-selection bias if participants chose their treatment).
Attention to Unintentional Group Differences: While random assignment aims for equivalent groups (especially with large samples), researchers can also check for demographic differences (e.g., gender) between groups.
Quotas: Sometimes random assignment is combined with quotas to ensure proportional representation of certain demographics in each group.
Use of Control Groups: A group that does not receive the experimental treatment, allowing for a direct comparison to determine if the treatment itself caused the observed effects.
Rationale: Helps account for natural improvement over time (e.g., in depression) or the effects of participating in a study.
Ethical Considerations: Denying potentially helpful treatment to a control group raises ethical concerns.
Wait-List Control Group: A solution where the control group eventually receives the same treatment, but after a delay. This still allows for comparison of immediate effects without permanently denying treatment.
Placebo Effects: The expectation of change or optimism can lead to positive outcomes.
Nocebo Effects: The negative expectation or disappointment from not receiving treatment can lead to negative or absent positive effects.
Placebo Control Groups: Both treatment and control groups believe they are receiving treatment (or are unaware). This helps rule out expectation-based improvements and isolate the effect of the active treatment.
Challenges: Difficult in pharmaceutical studies (side effects can be clues) and talk therapy (designing a