Methods of Developmental Psychology I.Introduction A.The scientific method B.Why study research methods II.Dimensions of research method A.The normative-explanatory dimension B.The naturalistic-manipulative dimension 1.Naturalistic observations 2.Controlled/experimental observations C.The atheoretical-theoretical dimension D.The ahistorical-historical dimension III.Designs of developmental research A.Longitudinal designs B.Cross-sectional designs C.Sequential designs D.Comparative designs E.Cross-cultural designs IV.General methodological problems A.Contamination B.Researcher effects C.Reconstruction through retrospection D.Faulty logic E.Inadequate definition of concepts F.Sampling G.Overgeneralization

Why study research methods? Two general reasons Importance of being a wise and critical consumer of research Bridging research and practice

Dimensions of Developmental Research The normative-explanatory dimension Normative research describes some typical behavior Explanatory research provides explanations for developmental differences The naturalistic-manipulative dimensions Naturalistic research observes behavior in its natural setting Controlled or experimental observations put the child in situations that will maximize the occurrence of the behavior of interest The atheoretical-theoretical dimensions Involves the relative emphasis on theory as a basis of research The ahistorical-historical dimensions Ahistorical research studies behavior at one particular point in time Historical research is concerned with the origins and future courses of behavior

The Longitudinal Design Age at time of testing 6 years  8 years  10 years Involves assessing the same group of people over an extended period of time Advantages of the approach Similarities or differences in behavior across development are seen directly Track performance of individuals over time, identify common patterns and individual differences Can examine relations between early and late behaviors Drawbacks of the approach Biased sampling Repeated testing Cohort effects

The Cross-Sectional Design Age group for testing 6 year-olds, 8 year-olds, & 10 year-olds Involves assessing differently aged groups of people at the same time of testing Advantages of the approach Less time-consuming, and less expensive than longitudinal designs Not as concerned with practice effects and selective drop-out Drawbacks of the approach No evidence for change at individual level; change is between groups of people Cohort effects

The Sequential Design Cohort age InformationInformation (in 1995)gainedCS 1 gainedCS 2  6-year-oldsImmediate L 1  Enduring impact  impact on  on children who  6-year-olds  are now 8 yrs old    8-year-oldsImmediate L 2  Enduring impact  impact on  on children who  8-year-olds  are now 10 yrs old    10-year-oldsImmediate L 3  Enduring impact  impact on  on children who  10-year-olds  are now 12 yrs old      1 st cross-sectional2 nd cross-sectionalcomparison tells us at which age training(1) which cohort program has largestbenefited most in immediate impactthe long run; (2) helps to decide which future program might be implemented to maximize long- term impact

The Comparative and Cross- Cultural Research Designs Comparative research Attempt to learn something about human development through comparison to non-human development Permits controlled tests of hypotheses that would be unethical to test with humans Cross-cultural research Compares subjects from different cultural backgrounds Allows investigator to determine whether conclusions drawn about children in one social or cultural context generalize to children in other contexts Cross-cultural differences versus cross-cultural similarities

General Problems with Research and Developmental Research Contamination Data is influenced by factors other than those being studied Researcher effects The researcher unintentionally influences the results of the study Demand characteristics Reconstruction through retrospection Biases introduced through inaccurate memories Faulty logic Problematic reasoning in interpreting data Inadequate definition of concepts Problems in how abstract concepts are defined and operationalized Sampling Errors introduced through the type of subject recruited for the study Overgeneralization The application of findings to situations that are not appropriate or similar enough