1. Psyc311 – Development Psychology
Research Methods

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

3. Developmental Periods
Prenatal (conception to birth)
Infancy (birth to mos)
Early Childhood (2-5 years)
Middle Childhood (6-11 years)
Adolescence (10-12 to 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

4. 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: :50 class - 5/1, 8-11am :40 class - 5/4, 12-3pm

5. 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

6. 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)

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

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

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

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

12. 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.

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

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

15. 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.

16. 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.

17. 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?

18. 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

19. 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

20. 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

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

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

23. 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)

24. 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…

25. 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

26. 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

27. 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

28. describing data
Central tendency
mode—most frequent 28

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

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

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

32. 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

33. describing data
Variability
range
7 – 1 = 6 33

34. 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+

35. 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.

36. 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).

37. 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.

38. 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

39. third variable problem: Classic example
+

40.  + 

41. 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

42. Violent TV
Non-violent TV

43. 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.

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

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

46. 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?

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

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

49. 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