Notes on Scientific Method, Theory, and Research Designs in Psychology

Weeks of Welcome and campus connections

  • VCU is in Weeks of Welcome; many events across campus beyond orientation

  • Theme this year: “Friday time, enter the brand universe”

  • To find events, visit the campus site and search for Weeks of Welcome

  • Purpose: provide opportunities for connection and community during the start of fall semester

Administrative announcements and course logistics

  • First due date mentioned: syllabus quiz due tonight (no flexible date); you can take it as many times as needed for a perfect score

  • Connect (Labs and SmartBook) updates:

    • SmartBook assignments for Chapter 1 and 2 available

    • Lab Number 1 opened as of yesterday; Lab Number 2 opens over the weekend or Monday (flexible schedule)

    • For Lab 1 and Lab 2, there is a Best Buy window: Lab-related content is available with a Best Buy

    • Lab quizzes: first two quizzes allow up to three attempts to maximize score

  • Instructor expects questions about SmartBook and Lab; plan to address questions as they come

SmartBook vs Lab: what counts for credit

  • SmartBook

    • Completion-based grade: you earn full credit just for completing SmartBook, regardless of number of correct/incorrect answers

    • If you score low (e.g., 65%), review the questions you struggled with; you can retake SmartBook multiple times

    • Strategy: use SmartBook to identify weak topics before Exam 1; revisit content you found difficult

    • You can indicate your confidence level for each question before seeing correctness; Connect can generate a report showing accuracy and confidence

    • High confidence with many wrong answers may indicate a need to seek office hours or review; low confidence with many correct answers may indicate trust in your understanding

  • Lab (Canvas structure)

    • Lab module contains three clickable parts per week: Lab Number 1, ABA, and Lab Number 1 Quiz (and similarly for Lab 2)

    • Important flow: complete the “above” activities (videos, readings, games, articles) before attempting the lab quiz

    • Quiz questions map to activities and ADA-style application tasks; the quiz may not be directly tied to the lecture material but to lab activities

    • Recommended order: complete lab activities (psychological research-related tasks, videos, readings, games) → complete ADA/activities → take the quiz; you can choose to try the quiz earlier, but a thorough lab engagement is advised

  • Packback

    • Sign up by next Tuesday; first practice round will help acclimate to the platform (will not count toward grade)

  • SONA (psychology participation system)

    • You should expect an email from the SONA coordinator by around the Tuesday after Labor Day with steps to get started

  • Under 18 considerations

    • If you are under 18 (as of the start), by around October 15 you may still be under 18; contact instructor and Waverly for access to alternative assignments if needed

  • Religious observances

    • If you have religious observances affecting attendance or exam timing, notify instructor by tomorrow; accommodations can be made to avoid choosing between spiritual practice and exam taking since attendance isn’t tracked in-class here

Extra credit opportunity and psychology jeopardy segment

  • An informational extra credit activity was introduced: identify four psychologists whose names were shown in a jeopardy setup

  • Four scholars discussed (and their contributions):
    1) Robert L. Williams II – prominent member of the National Association of Black Psychologists; discussed his challenge to conventional views on how Black children learn; introduced the concept related to Ebonics/AAVE and its connection to West African dialects.
    2) Dr. Erica Anderson – psychologist who specializes in gender dysphoria in transgender youth and how to support transitioning among teens; noted as a trans individual herself.
    3) Caroline Agne / Caroline Lewis Atney – one of the first Native American psychologists to earn a PhD; pivotal in family psychology as a subdiscipline; personal tie: speaker received the Caroline Atney award from the American Psychological Association for couples and family psychology diversity.
    4) Darryl Wing Sue (also listed as Darryl Wayne Sue) – cofounder of the Asian American Psychological Association; pioneer in multicultural psychology and research on microaggressions

  • Takeaway: There are many well-known figures and equally important, lesser-known contributors in psychology; students are encouraged to identify researchers they connect with and explore their work

  • Educational aim: understanding that fields have unsung heroes beyond the most cited names; broaden exposure and avoid a purely textbook view

Transition to today’s content: theory, designs, and ethics in psychological research

  • The class will continue Monroe Park study discussion, focusing on:

    • The importance of theory

    • Three basic research designs and associated methods

    • A brief discussion on ethics in psychological research

  • Review of the scientific mindset used in coursework: move from intuition to scientific attitudes and the scientific method

  • Monro Park study evolution: a team-designed project on time of day and crowd density in Monroe Park; broad topic: time of day and park usage

  • Approach to applying the scientific method to study design:

    • Observations: e.g., variability in park occupancy across times of day

    • Interesting question: why do occupancy patterns differ by time of day and day of the week?

    • Hypotheses: multiple, sometimes non-competing; e.g., weather, class schedules, and day of week may influence park occupancy

    • Background research and terms: review prior work and define terms clearly

    • Operational definitions: define how observations will be measured (e.g., physical counting, in-person observation vs. camera surveillance); consider methodologies such as interviews or questionnaires

    • Testable predictions: derive concrete expectations (e.g., sunnier days → more park visitors; weekends vs weekdays; fewer classes/work shifts → more park activity)

    • Experimentation: collect data to test predictions; various data collection methods discussed (observation, interviews, questionnaires, secondary data)

    • Refinement: as data come in, refine or expand hypotheses to account for new insights (e.g., different reasons for students vs. non-students in the park)

    • General theory: ultimate aim is a theory about behavior in Monroe Park that could be generalized across similar settings if replicable

  • Replication and cross-cultural considerations

    • Replication strengthens theory; replication across different parks/settings improves generalizability

    • Cross-cultural applicability: some theories generalize globally (e.g., universal facial expressions of emotion), while others are culturally specific (e.g., certain parenting styles and dress norms)

    • Critical stance: be skeptical about universality; consider population and setting when applying theories

  • Key concepts connected to the Monroe Park discussion

    • Theory: a broad explanation and prediction about observations; guides the formation of hypotheses and research directions

    • Hypotheses: educated guesses derived from theory; testable predictions that can be supported or refuted by data

    • Operational definition: precise, replicable definition of a concept used to measure it in a study

    • Replication: repeating studies to verify findings; strengthens or revises theories

    • Replication and diversity of settings/groups: measurement and theory should be tested across different groups and environments

    • Reliability of research: theories should be able to withstand replication and produce consistent predictions

    • The role of humility: be willing to revise beliefs if data contradicts predictions

    • Ethical implications: understanding that historical and cultural contexts matter; ethical conduct in research is foundational and will be addressed

Theory in psychological science

  • Definition: a broad explanation and prediction about observations

  • Purpose: to organize complex ideas and provide a framework for understanding behavior

  • Relationship to hypotheses: theories generate testable hypotheses and clear predictions

  • Replication and cross-context validity: replication strengthens theories; cross-cultural replication assesses generalizability

  • What makes a good theory:

    • Simplifies and organizes complex ideas

    • Leads to clear, testable hypotheses and predictions

    • Guides and motivates empirical research

    • Should be able to be replicated and tested across settings

  • Skepticism and cross-cultural applicability:

    • Some theories generalize across cultures and contexts (e.g., certain emotions and some universal processes)

    • Others are culture-specific (e.g., dress and some parenting styles); always consider population and setting when evaluating theories

  • Questions about replication in psychology:

    • Are all theories tested across different settings and groups? Answers vary: some show cross-cultural applicability, others do not; critical examination is encouraged

Descriptive, correlational, and experimental designs: overview and distinctions

  • Important distinction: research design vs. research methods

    • Design: the overall structure and goal of the study (descriptive, correlational, experimental)

    • Methods: specific strategies used to collect data (observational, archival, surveys, interviews, etc.)

  • Three primary research designs:

    • Descriptive (to describe behavior/mental processes; provide a picture of what is happening)

    • Correlational (to examine relationships between variables; assess whether they are associated)

    • Experimental (to establish causality by manipulating an independent variable and observing effects on dependent variables)

Descriptive research designs (systematic description of behavior)

  • Core goal: describe behavior or mental processes; not to explain why

  • Key features: thorough, objective, and systematic observation

  • Common descriptive strategies:

    • Archival research: use existing records or databases (e.g., census data, college records) to infer patterns

    • Naturalistic observation: record behavior in a natural environment without manipulation; describe but not explain

    • Example given: analyzing Facebook posts for positive language, noting when positive posts peak (late Saturday night) and dip (Tuesday afternoons)

    • Case study: in-depth study of a single case or small group; provides deep insights but limited generalizability

    • Example: Piaget’s child development observations based on his own children; replication later extended findings

    • Ethnography: researcher immerses in a culture/group to understand attitudes and values through in-depth observation; highly contextual

    • Surveys and interviews: gather data from many people; can be broad but depth varies (surveys often broad, interviews deeper)

  • Data collection methods within descriptive designs:

    • Observational studies (systematic observation)

    • Interviews and questionnaires (surveys)

    • Random sampling: to improve generalizability; gold standard for generalizing to a population

    • Wording effects: survey/question wording can bias results; operational definitions help ensure that questions map onto the behavior or construct of interest

  • Key terms and notes:

    • Archival data advantages: inexpensive

    • Archival data disadvantages: limited by what exists; potential bias in what was recorded (not all aspects of behavior are captured)

    • Naturalistic observation advantages: high ecological validity; behavior observed in real contexts

    • Naturalistic observation disadvantages: limited control over extraneous factors; cannot establish causality

    • Case study advantages: depth and rich qualitative insights

    • Case study disadvantages: limited generalizability; potential for biased interpretation

    • Ethnography advantages: deep understanding of a group’s culture

    • Ethnography disadvantages: researcher bias and misinterpretation if not culturally immersed or aware

    • Random sampling in surveys: improves representativeness and generalizability

Correlational designs (assessing relationships between variables)

  • Core goal: understand whether and how two variables are related; quantify the strength and direction of the relationship

  • Key concepts:

    • Correlation coefficient r: a number that describes the strength and direction of a relationship between two variables

    • r ranges: -1 \, \le\, r \le\, 1

    • Positive correlation: r > 0 (variables move in the same direction)

    • Negative correlation: r < 0 (one variable increases as the other decreases)

    • Strength of the relationship: indicated by the magnitude |r|

    • Strong: |r| \approx 1

    • Moderate: |r| mid-range

    • Weak: |r| small

    • Zero correlation: r = 0 (no linear relationship)

  • Visual representation: scatter plots showing data points; patterns illustrate the sign and strength of the relationship

  • Important limitation: correlation does not imply causation; even a strong correlation does not prove that one variable causes changes in the other

  • Methods commonly used within correlational designs (same data collection tools as descriptive):

    • Surveys and interviews

    • Observations

    • Archival data

  • Additional notes on correlational analysis:

    • A correlation coefficient can be positive or negative regardless of the sign; the key is the direction and magnitude

    • In practice, researchers look at both the sign and the absolute value to assess strength

    • When reporting, always consider potential third variables and lurking factors that could influence observed relationships

Experimental designs (causal testing; not covered in full detail in transcript, but outlined for context)

  • Core goal: establish causality by manipulating an independent variable (IV) and observing its effect on a dependent variable (DV)

  • Key features (typical design elements):

    • Random assignment of participants to conditions

    • Manipulation of the IV to create different experimental conditions

    • Control of extraneous variables (evoking a controlled environment)

    • Measurement of DV(s) across conditions to assess causal impact

  • Why experiments matter: ability to infer causal relationships rather than mere associations

  • Practical considerations: ethical constraints, feasibility, and generalizability across settings and populations

Operational definitions, replication, and ethics in research

  • Operational definition: precisely defining a concept in terms of the specific, observable, and measurable operations used to assess it

    • Example in Monroe Park study: counting people in the park at specific times, noting conditions (sunny vs. cloudy; day of week; class schedules)

  • Replication: repeating a study to see if findings hold under different conditions or with different samples; strengthens theory and generalizability

  • Cross-cultural replication: tests whether findings hold across diverse cultural settings; highlights universal vs. culture-specific processes

  • Ethical considerations (briefly noted for future discussion): historical and contemporary ethics in psychological research, including how to handle sensitive topics like microaggressions and gender identity, and ensuring participant welfare and consent

Quick connections to prior and real-world relevance

  • Linking theory to research design: theory informs hypotheses, which in turn guide data collection and analysis

  • Real-world relevance: understanding park usage patterns can inform urban planning, campus life design, and public space management

  • Critical thinking emphasis: humility and openness to revise hypotheses in light of data; avoidance of overgeneralization

Summary of key takeaways

  • Descriptive, correlational, and experimental are the three primary research designs in psychology, each with distinct goals and methods

  • Descriptive designs describe but do not explain causality; common methods include archival research, naturalistic observation, case studies, ethnography, and surveys/interviews; random sampling increases generalizability; wording effects can bias survey results

  • Correlational designs examine relationships between variables; the correlation coefficient r\in[-1,1] indicates direction and strength; remember that correlation does not imply causation

  • Theoretical work in psychology involves building theories that explain and predict observations; hypotheses are testable implications of theory; replication and cross-cultural testing strengthen theories

  • Operational definitions are essential for clarity and replicability; research methods and designs should be chosen to align with the theory and hypotheses

  • Ethics and cultural context are foundational considerations in psychological research; ongoing discussion about how to apply these in practice

Notable examples and figures mentioned in class

  • Robert L. Williams II: challenged conventional views on Black children’s learning; connection to Ebonics/AAVE and West African dialects

  • Dr. Erica Anderson: gender dysphoria in transgender youth; advocacy and understanding in supportive contexts

  • Caroline Agne / Caroline Lewis Atney: pioneer Native American psychologist; key role in family psychology; recipient of APA award related to diversity

  • Daryl Wing Sue (Darrryl Wayne Sue): cofounder of the Asian American Psychological Association; influential in multicultural psychology and microaggression research

  • Piaget and the point that many influential theories have come from broader study and replication, not just a single study or researcher

Quick reference: a few formulas and definitions used in the lecture

  • Correlation coefficient range and interpretation:

    • r \in [-1, 1]

    • Positive correlation: r > 0; Negative correlation: r < 0

    • Strength by magnitude: stronger when |r| is closer to 1; weaker as |r| approaches 0

  • Descriptive vs. correlational vs. experimental (high level):

    • Descriptive: describe behavior; e.g., counts, observations, archival data

    • Correlational: assess relationships between variables; e.g., r, scatter plots

    • Experimental: manipulate IV, measure DV, infer causality (not detailed in transcript but foundational to the three-design framework)

If you want, I can tailor these notes further to a specific lecture slide set or convert the sections into a study-friendly outline with flashcard prompts for quick review.