Untitled

Introduced the idea of reviewing recorded lectures from a past date.
Emphasized that specific critical content will be covered in class instead of in videos.
Mentioned the length and accuracy issues of a recorded lecture from 2020 during COVID.

Reliability is key in measuring intelligence.
- Defined as the consistency of a testing measurement.
- Test-Retest Reliability: The best method involves giving the same test at two different times and correlating the scores.
- Coefficients can vary based on time frames: one month, ten months, or one year reliability coefficient.
Split-Half Reliability: A simpler method to assess reliability by dividing a test into two parts and comparing scores from both halves.
- Example: A 60-question test is split into two 30-question scores that are randomly selected.
- If two different topics were tested (e.g., first 30 vs. last 30), there may not be a correlation, thus indicating unreliable scoring.

Reliability Coefficient: A numerical representation of reliability derived from correlational studies of test scores over time.
Validity: Can be considered in terms of criterion validity, which relates a test's outcome to an external criterion for the same measurement.
- Validity coefficient is derived when comparing scores of one test with another related measure.

When two scores from a split test are correlated, a high correlation indicates strong internal reliability.
Conceptual Understanding: If one half receives high scores and another half receives low scores irregularly, the tested material lacks reliability (e.g., a bathroom scale giving inconsistent weights).

A longstanding issue regarding the influence of genetics versus environmental factors on intelligence.
Early theorists and studies provide varying percentages for the influences:
- Arthur Jensen's theory (1960s): 80% genetics, 20% environment.
- The Bell Curve (1994): 60% genetics, 40% environment.
- Twin studies often suggest a 70% genetic contribution.
Critiques of these percentages emphasize the significance of environmental influences on developing intelligence.

Different definitions of intelligence among ethnic groups with widely varying average scores:
- Observations often show predictable patterns based on socio-economic and environmental influences.
- Importance of understanding that differences are not purely genetic but also strongly influenced by environmental factors like parental education levels.
Head Start Program: A federal initiative aimed at improving educational outcomes for underprivileged youth, countering assertions of genetic inferiority.

Jensen faced backlash in the 1960s for suggesting resource waste in aiding lower socio-economic groups, viewed as racist and controversial.
Research is ongoing, with claims often presented online despite not being widely accepted in current psychology.

Importance when interpreting test scores, especially among different demographic groups.
Potential explanations for differences in scoring:
1. Bias within the test favoring one group over another.
2. A true valid difference in ability across groups.
Historical concerns have led to efforts in removing test biases based on gender and cultural background.

SAT (Scholastic Assessment Test) biased towards English speakers.
- Designed to predict success in American schooling but not necessarily a measure of innate intelligence or ability.
Suggestion that over time, non-native speakers tend to improve in language skills, impacting college success prediction.

Bias is defined as differential predictive validity; evidence for bias is not merely based on mean score differences between groups but on how well the test predicts success for each group.

Previous terms used for low IQ have transitioned due to societal shifts:
- Idiot, Moron, Imbecile: Terms abandoned as they became derogatory.
- Retarded: Officially changed to Intellectual Disability to avoid stigma and ensure respectful language.

Reflects social movements towards respect and decency concerning individuals with cognitive impairments.

Development: The study of growth and change throughout the lifespan, encompassing prenatal to old age.

Traditional focus (Freud era) on child development tends to ignore adult changes post-puberty.
Emphasis has shifted to lifespan development, including significant contribution from theorists like Erikson.

Prenatal conditions can have lasting effects on child development.
Social Attachment: The bond formed between a caregiver and child during early years affects psychological and emotional growth.
Nutrition during pregnancy is highlighted as crucial for fetal development and long-term health outcomes.
The New Science of Fetal Origins discusses how prenatal issues can influence genetics affecting offspring well beyond birth.

The significance of prenatal periods begins discussions that extend to preconception influences on future children.

Original sin: Medieval concept of inheriting sin and the need for correction and salvation through parenting.
Tabula Rasa: Philosophical idea attributed to John Locke, where children are born as blank slates to be formed by their experiences.
Innate Goodness: Jean Jacques Rousseau emphasized that children are born inherently good and should be nurtured.
Noble Savage: Concept suggesting that primitive societies were morally purer, and insights can be gained from traditional child-rearing practices.

Post-WWII changes led to increased female workforce participation, necessitating developments in childcare and early education.
Focus on child development research was fueled by the government’s educational research funding starting in the 1960s.
The intertwining of nature versus nurture continues to shape educational policies and practices today.

The lecture wraps up, emphasizing upcoming topics, discussions on nature vs. nurture, and the various methodologies for studying developmental changes.
Tailored discussion scheduled for the next class regarding research methods and their implications in developmental psychology.