Psyc311 – Development Psychology Research Methods

Developmental Periods Prenatal (conception to birth) Infancy (birth to 18-24 mos) Early Childhood (2-5 years) Middle Childhood (6-11 years) Adolescence (10-12 to 18-21 years) Early Adulthood (20s to 30s) Middle Adulthood (40s to 50s) Late Adulthood (60-70s to death)

Developmental Periods Prenatal (conception to birth) Infancy (birth to 18-24 mos) Early Childhood (2-5 years) Middle Childhood (6-11 years) Adolescence (10-12 to 18-21 yrs) Early Adulthood (20s to 30s) Middle Adulthood (40s to 50s) Late Adulthood (60-70s to death) Age Group 1 Age Group 2 Age Group 3

Week Tues Thurs Topic/Reading 1/11 Intro to Devel; Syllabus Ch 1. Research Methodology Section 1: Introduction 1/18 Grp Research Proposal Q/ Psyc Info: Look up articles Ch 4-6 Section 3: Infancy 1/25 Grp Article Summary -- Intro; Methods Section 2/1 Ch 4-6; Grp Proposal Discussion Ch 4-6; Taking Sides 2/8 Ch 7-8 Ch 7-8; Grp Prop 1st Draft Section 4: Early Childhood 2/15 Ch 7-8; Taking Sides 2/22 Exam 1 Ch 11-12; Obs Journal 1 Section 6: Adolescence 3/1 Ch 11-12 3/8 No Class: Spring Brk   3/15 Ch 11-12; Grp Prop 2nd Draft Ch 11-12; Taking Sides 3/22 Grp Prop Peer Review; Obs Journal 2 Grp Prop Peer Review; Ch 13-14 Section 8: Early Adulthood 3/29 Ch 13-14 4/5 Exam 2 Ch 17-19 Section 9: Late Adulthood 4/12 Ch 17-19; Grp Prop Final Draft 4/19 Grp Presentations 4/26 READING DAY; Volunteer Project Due Obs Journal 3 or Exam 3 and Final exam: 10:50 class - 5/1, 8-11am 1:40 class - 5/4, 12-3pm

top choices for topics social/moral development self/personality/identity development developmental disorders (e.g., ADHD, autism) romantic relationships (dating, marriage) emotional development health issues/problems parenting/family relationships friends/peer relationships puberty/sexual development death/dying pretend play/imagination gender development effects of aging -- physical, cognitive, social

Characteristics of Development Lifelong Multidimensional Biological, cognitive, socio-emotional Multidirectional Expansion/contraction Plastic Gene/environment interaction Multidisciplinary Contextual Age-graded influence History-graded influence Non-normative (individual)

Developmental Science Five steps Ask a (developmental) research question.

Developmental Science Five steps Ask a (developmental) research question. Develop a hypothesis.

Developmental Science Five steps Ask a (developmental) research question. Develop a hypothesis. Construct a methodology to test your hypothesis.

Developmental Science Five steps Ask a (developmental) research question. Develop a hypothesis. Construct a methodology to test your hypothesis. Draw a conclusion.

Developmental Science Five steps Ask a (developmental) research question. Develop a hypothesis. Construct a methodology to test your hypothesis. Draw a conclusion. Share your findings.

NO!! Research questions Does god exist? Is this a good research question? NO!!

Research questions Good research questions must involve something that can be empirically defined and measured.

Operational definition the description of the variable of interest in measurable terms. So, how might we operationally define: Aggression Happiness Measurement Device used to detect the events/phenomena to which the operational definition refers. With this in mind, let’s generate some research questions of our own.

Which is the best research q? A) Alcoholic parents tend to neglect their children more than non-alcoholic parents. B) What factors influence high school dating? C) Does the frequency and graphic quality of violence in video games influence levels of anti-social thinking in adolescent males? D) How much longer until class is over? E) None of these are good.

Developing hypotheses Developing a hypothesis: What do you think you’ll find? Why? That is, what is your (theoretical/conceptual/empirical) justification for you hypothesis?

Testing hypotheses How are you going to test your hypothesis? Non-experimental Design Observation of variables of interest Experimental Design Manipulation of variables of interest

Testing hypotheses Types of measurement Subjective measures Introspective reports Survey/Questionnaire Objective measures Standardized testing Naturalistic observation Physiological Measurements fMRI, galvanic skin response Levels of hormones, neurotransmitters

Research designs Case study Target age group Developmental – several age groups Cross sectional Benefits – cheap way to capture change over time Problems – cohort effect and other group differences Longitudinal Benefits – confidence that change being captured is genuine change Problems – reduction of sample size and learning effect Cross-sequential

Time 1 Time 2 2nd 4th 6th 4th 6th 8th

Time 1 Time 2 2nd 4th 6th 4th 6th 8th

Design considerations Validity Being able to draw accurate inferences (conclusions) about what you are studying from your measurements Invalid in definition Examples? Invalid in detection (measurement)

Type 1 error (false positive) Reliability The tendency for measurement to produce the same results when used in the same way (or under the same conditions). Type 1 error (false positive) You want a measurement that is stable enough that it won’t detect changes in your variable when changes haven’t actually occurred. Power The tendency for measurement to produce different results when used in different ways (or under different conditions). Type 2 error (false negative) You want a measurement that is sensitive enough to detect changes in your variable when changes actually occur…

population and sample You are asking a question about behavior in a given population It is difficult (if not impossible) to ever study an entire population – so what do we study instead? teenagers

population and sample You are asking a question about behavior in a given population It is difficult (if not impossible) to ever study an entire population – so what do we study instead? a sample. teenagers

We choose a representative sample. How do we make sure that we can accurately generalize from a sample to a population? We choose a representative sample. controlled or random sampling

describing data Central tendency mode—most frequent 28

describing data Central tendency mode—most frequent mean—average Μ = 3.27 29

describing data Central tendency mode—most frequent mean—average median—middle 30

describing data Central tendency mode—most frequent mean—average median—middle Each of these tells us something different about our data. 31

normal distribution Many things tend to be normally distributed in a given population. So, we should expect most people to fall somewhere close to the middle, with the extreme cases being less frequent. IQ is normally distributed. mean

describing data Variability range 7 – 1 = 6 33

relationships between variables What is a correlation? Relationship between two variables A is related to B Positive relationship: A+/B+, A-/B- Negative relationship: A+/B-, A-/B+

what kind of correlation? As a person gets angrier, they also get more violent. A) Positive correlation B) Negative correlation Positive. As anger increases, violence increases. As a person gets older, they start to remember fewer vocabulary words. Negative. As age increases, vocabulary memory decreases.

As calorie consumption drops, people have less energy. A) Positive correlation. B) Negative correlation. Positive. As calorie consumption decreases, energy levels decrease (so variable movement is happening in the same direction).

relations between variables: causation Ultimately, we are typically interested in whether or not one variable causes another. T/F: All variables that are causally related are correlated. T/F: All variables that are correlated are causally related.

Two variables are correlated X  Y three possible relationships X causes Y Y causes X Z causes both X and Y with correlation, we cannot know which it is. 38

third variable problem: Classic example +

 + 

experimentation To establish causation, we must conduct an experiment. Experimentation requires manipulation A  B A is the independent variable -- manipulated e.g., amount of television violence watched B is the dependent variable -- measured e.g., amount of aggressive behavior exhibited 41

Violent TV Non-violent TV

experimentation In the case of a 3rd variable, you have two choices: Manipulate and measure x & y, while controlling for z. or Manipulate and measure x, y, & z.

randomization (controls for 3rd variable) used when z is not important for the study

selected groups (measures influence of 3rd variable) Used when z is important for the study Adult supervision No adult supervision

other considerations: drawing conclusions Internal validity Study is designed so that you are able to draw accurate inferences about causal relation between independent and dependent variables. External validity Study designed so that your independent and dependent variables are defined in natural/realistic way. You can have internal validity but not have external validity – why?

other considerations: biases Biases in observation Participant biases Demand characteristics Observer biases Confirmation bias Double-blind experiments

other considerations: ethics Ethical practices Informed consent Debriefing Special considerations for children Are there things we shouldn’t study?

Final steps Drawing conclusions Sharing your findings What kinds of conclusions can you draw? Can you generalize to a population? How broad of a population? Limitations Sharing your findings Conference presentations Publications