Developmental Psychology Unit 1 Quiz

The three major themes of this course are: development is lifelong, meaning it doesn't stop at childhood; development is multidimensional, involving physical, cognitive, and social changes; and development is plastic, meaning it's malleable throughout life.

Theories provide a framework for understanding complex phenomena, helping us organize and interpret data. They also guide research and predict future trends in development.

A falsifiable theory is one that can be proven wrong through empirical evidence. It's open to testing and revision, which is essential for a theory to be considered scientific.

The theory of evolution by natural selection, proposed by Charles Darwin, is a classic example of a falsifiable theory. Its predictions can be tested through fossil records, genetic analysis, and observation of present-day species.

Developmental theories must address three key issues: nature vs nurture, the relative influence of genetics and environment; continuity vs discontinuity, whether development is gradual or marked by distinct stages; and universal vs context-specific, whether developmental patterns are universal or influenced by culture.

The possible answers to the three developmental issues are: for nature vs nurture, it could be either nature-driven, nurture-driven, or an interaction of both; for continuity vs discontinuity, it could be continuous, discontinuous, or a combination; and for universal vs context-specific, it could be universal, culture-specific, or a mix.

Behaviorism argues that environmental factors solely drive developmental change. This perspective emphasizes learning through conditioning and reinforcement.

The key feature of experimental research that allows for causal conclusions is manipulation of variables. This means researchers directly control and vary the independent variable to observe its effects on the dependent variable.

An operational definition clarifies the exact methods used to measure a variable in a study. It provides specific guidelines for how the variable is observed, recorded, and quantified.

Confounding variables are outside factors that can influence the relationship between the variables being studied. They are often found in correlational studies, where researchers don't directly control the variables.

While correlational research can't establish causation, it can reveal important associations between variables. This allows researchers to identify potential factors influencing development and to generate hypotheses for future experimental studies.

A positive correlation indicates that two variables move in the same direction. For example, as height increases, weight tends to increase. A negative correlation indicates that two variables move in opposite directions. For example, as time spent studying increases, test anxiety tends to decrease.

The strongest correlation coefficient is -0.8. It indicates a very strong negative association between the variables. The weakest correlation coefficient is 0.2, indicating a very weak positive association between the variables.

An r value of .99 indicates a very strong positive correlation between the variables. However, correlation does not imply causation. There may be other factors influencing the variables, or the relationship might be reversed.

A cohort is a group of individuals who share a common characteristic, such as age or year of birth. In developmental research, cohorts are often used to study age-related changes.

A cross-sectional design compares groups of individuals at different ages at a single point in time. For example, a study might compare 10-year-olds, 20-year-olds, and 30-year-olds on a cognitive task.

A longitudinal design follows the same group of individuals over an extended period. For example, a study might track a group of children from age 5 to age 25.

Strengths of cross-sectional designs: relatively quick and efficient; allows for large sample sizes. Weaknesses of cross-sectional designs: susceptible to cohort effects (differences between generations); doesn't provide information about individual change.

Strengths of longitudinal designs: provide information about individual development over time; can track changes in specific variables. Weaknesses of longitudinal designs: time-consuming and expensive; potential for attrition (participants dropping out); may not be generalizable to other cohorts.

A sequential design combines elements of both cross-sectional and longitudinal designs. It tracks multiple cohorts over time, allowing researchers to assess both age-related changes and cohort effects.

Sequential designs are useful because they can reveal both the effects of aging and the influence of cohort differences. This allows researchers to gain a more nuanced understanding of developmental trends.

The diagonals in a sequential design can reveal the specific influences of cohort differences. By comparing individuals of the same age from different cohorts, researchers can identify specific factors that impact development in each generation.

The diagonals in a sequential design can help identify age-related changes, or how development changes over time for an individual. By comparing individuals of different ages from the same cohort, researchers can see how development progresses for a specific group.

Behavioral genetics aims to understand the relative contributions of genes and environment in shaping our behavior and development, including personality traits, intelligence, and susceptibility to certain disorders.

Twin studies compare the similarities and differences between identical (monozygotic) and fraternal (dizygotic) twins. This helps researchers estimate the heritability of traits, or the proportion of variation due to genetic factors.

Adoption studies compare the similarities and differences between adopted children and their biological and adoptive parents. This helps distinguish the effects of genes and environment in shaping development.

The assumption in twin studies is that identical twins share 100% of their genes, while fraternal twins share 50%. However, this assumption is not entirely true, as identical twins may experience slight differences in their environments in utero, resulting in variations in their DNA.

Adoption studies compare adopted children to both their biological and adoptive parents. This aims to isolate the influence of genes (from biological parents) from the effects of the environment (from adoptive parents).

Our environments can influence the expression of our genes, but it does not mean that our genes change during our lifetime. The DNA sequence remains constant, but environmental factors can switch genes on or off, impacting their activity.

The epigenome is a layer of chemical markers that sits on top of our DNA. It regulates gene expression, determining which genes are turned on or off at different times and in different cells. It plays a crucial role in adapting to environmental changes and maintaining health.

The epigenome can change throughout our lifespan in response to environmental factors, such as nutrition, stress, and experiences. These changes can be inherited by our offspring, suggesting a potential mechanism for intergenerational transmission of traits.

The epigenome adds a new layer of complexity to the nature vs nurture debate. It suggests that both genes and environment play an essential role in shaping development, and that their influence is not always static but can change dynamically throughout our lifespan.

Research from Sweden suggests that individuals who experienced famine during pregnancy had children with an altered epigenome, increasing their risk of developing health problems later in life. This suggests that environmental factors during pregnancy can influence the epigenome and potentially be passed down to future generations.