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

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Presentation on theme: "Psyc311 – Development Psychology Chapter 01 Introduction to Developmental Science Theory & Research Methods."— Presentation transcript:

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

2 Conducting Research

3 the “five step” process Developmental Theory 1.Ask a (developmental) research question. 2.Develop a hypothesis. 3.Construct a methodology to test your hypothesis. 4.Draw a conclusion. 5.Share your findings.

4 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.

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

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

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

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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 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.

23 third variable problem ++

24  + 

25 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

26 experimental design Violent TV Non-violent TV ?

27 experimental design In the case of a 3 rd 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 3 rd variable) used when z is not important for the study

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

30 additional material

31 31 describing variables Central tendency mode—most frequent

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

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

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

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

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) –Examples?

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40 other considerations Internal 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…

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43 other considerations Biases in observation – 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 –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


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