1. Psyc311 – Development Psychology
Chapter 01
Introduction to Developmental Science
Theory & Research Methods

2. Conducting Research

3. the “five step” process
Developmental Theory
Ask a (developmental) research question.
Develop a hypothesis.
Construct a methodology to test your hypothesis.
Draw a conclusion.
Share your findings.

4. !! NO !! research questions Does god exist?
Is this a good research question?
!! NO !!
Good research questions must involve something that can be empirically defined and measured.

5. i<clicker Which of these is the best research question?
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) B & C are equally good.

6. definition and measurement
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, take a moment to generate a research question of your own.

7. types of measurement Subjective measures
Introspective reports
Survey/Questionnaire
Objective measures
Standardized testing
Naturalistic observation
Physiological measures
fMRI, galvanic skin response
Levels of hormones, neurotransmitters
Are physiological measures subjective or objective measures?
A) subjective
B) objective
C) both

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

9. 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

10. non-experimental designs
Systematic Observation
Naturalistic
Structured
Self-report Survey
Clinical
Qualitative
Case study – in-depth study of individual
Ethnography – in-depth study of culture
What are the (dis)advantages of a naturalistic vs. structured observation?
Why choose a survey over an observation?
Ask Yourself! What design is best for study non-normative development?

11. tracking development 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

12. cross-sequential
Time 1 Time 2
2nd
4th
6th
4th
6th
8th

13. cross-sequential Time 1 Time 2 2nd 4th 6th 4th 6th 8th Ask Yourself!
How do cross-sequential designs reveal any cohort effects?
2nd
4th
6th
4th
6th
8th

14. 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

15. 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

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

17. i<clicker Which makes for a good sample?
A) when it is chosen to match the demographics of the population as closely as possible
B) when it is randomly selected from the population
C) both.

18. 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+

19. relationships between variables
As a person gets angrier, they also get more violent.
A) Positive
B) Negative
Positive. As anger increases, violence increases.
As a person gets older, they start to remember fewer vocabulary words.
A) Positive
B) Negative
Negative. As age increases, vocabulary memory decreases.
As calorie consumption drops, people have less energy.
A) Positive
B) Negative
Positive. As calorie consumption decreases, energy levels decrease (movement is happening in the same direction).

20. relationships between variables
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.

21. Ask Yourself!
A researcher compares older adults with chronic heart disease to those with no major health problems and finds that the first group scores lower on mental tests. Can the researcher conclude that heart disease causes a decline in intellectual functioning in late adulthood?
A) yes
B) no

22. correlation vs. causation
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. 22

23. third variable problem
+

24. third variable problem
 + 

25. experimental design
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 25

26. experimental design
Violent TV ?
Non-violent TV

27. experimental design
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.

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

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

30. additional material

31. describing variables
Central tendency
mode—most frequent 31

32. describing variables Central tendency mode—most frequent mean—average
Μ = 3.27 32

33. describing variables Central tendency mode—most frequent mean—average
median—middle 33

34. describing variables Central tendency mode—most frequent mean—average
median—middle
Each of these tells us something different about our data. 34

35. describing variables
Variability
range
7 – 1 = 6 35

36. 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

37. Income is one thing that is not normally distributed. A) True B) False
Can you think of others?

38. 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)

39. i<clicker
If I asked college students and mature adults to rate on a scale how much fun they have ever day and I found college students rated their level of fun much higher, could I then draw the conclusion that college students are happier than mature adults?
A) yes
B) no
Why?
Issue of invalid definition.
If I was interested in studying freshman college students’ general anxiety levels and so I polled all of my Intro students using a standard anxiety scale at the beginning of class right before they took an exam, could I draw conclusions about general levels of anxiety from those measurements?
A) yes
B) no
Why?
Issue of invalid detection.

40. other considerations Internal validity External validity
Study was designed so that you were able to draw accurate inferences about causal relation between independent and dependent variables.
External validity
Study was 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?

41. design considerations
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…

42. i<clicker
You want a measurement that is sensitive enough to detect changes in your variable when changes actually occur…
This is an issue of:
A) power
B) reliability
You also want a measurement that is stable enough that it won’t detect changes in your variable when changes haven’t actually occurred.
This is an issue of:
A) power
B) reliability

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

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

45. 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