PSYC 190 lecture 9

Achievement Gap & Learning

International Comparisons: U.S. Student Performance

🇺🇸 U.S. vs. Other Countries

• Concerns exist that U.S. students lag behind internationally in math, science, and reading.

• Conflicting reports are due to different studies with varying methods and countries sampled.

🧪 Key Studies

1. TIMSS (Trends in International Mathematics and Science Study)

   • Conducted by U.S. Department of Education (since 1995).

   • Tests formal math & science in grades 4 and 8.

   • U.S. ranks top 10 internationally.

2. NAEP (National Assessment of Educational Progress)

   • U.S.-only data (grades 4, 8, 12).

   • Shows improvement since 1970s in math & reading.

   • Does not compare to international peers.

3. PISA (Program for International Student Assessment)

   • Tests 15-year-olds in math, reading, and science.

   • U.S. ranks 35th in math, below average in all categories.

⚖ Explaining Differences in Rankings

• TIMSS focuses on formal math (algebra, geometry).

• PISA emphasizes applied problem-solving.

• Countries like Finland & New Zealand excel at applied math → perform better on PISA.

• Removing wealthier European countries from PISA → U.S. ranking becomes similar to TIMSS.

👩‍🏫 Teacher Training & Curriculum Gaps

• Key problems in U.S. education:

  • Weak focus on geometry/measurement.

  • Low teacher math training.

    • Only 28% of 4th-grade math teachers trained in math (vs. 51% in top countries).

    • In 8th grade: 48% in U.S. vs. 65% in high-performing countries.

• Teacher quality and certification are strongest predictors of student success (even after accounting for poverty or language).

📈 Achievement Gap Within the U.S.

• “Average” student hides real variation.

• Achievement gap = difference between:

  • Affluent White students vs. poor, Black, or Hispanic students.

  • Asian-Americans and recent African immigrants often outperform all groups.

👩🏿‍🏫 Data from NAEP ("The Nation’s Report Card")

• Scores available since 1970s by:

  • Gender, ethnicity, parental education, etc.

Example Trends:

1. White Students (1978–2012):

   • High percentage scored ≥250 (almost none below).

   • Improvements seen over time in all score tiers.

2. Black Students:

   • 1978: 29% scored below 250.

   • Over time: fewer in lowest tier, more in middle, but few in top tier.

3. Hispanic Students:

   • Similar to Black students but with ~10% more in the middle tier.

4. Reading scores reflect similar disparities.

🧬 Nature vs. Nurture & Achievement Gap

• Ongoing debate:

  • Some claim genetic causes for group differences (discredited).

  • Others argue cultural bias in IQ/achievement tests.

🧪 Adoption Studies as Evidence

• Dennis (1973): Lebanese orphanage → adopted kids scored ~100 IQ vs. 65 in non-adopted.

• U.S. (1976): Black infants adopted by White families → scored above average.

• Timing matters: Early adoption (<12 months) → better outcomes.

🔬 Limitations of Early Studies

• Small sample sizes.

• Compared adopted kids to institutionalized peers.

✅ More Recent Study

• 62 adoption studies (17,000+ children):

  • Adopted kids outperformed non-adopted peers in IQ & academics.

  • Environmental change (home/school quality) is key factor.

  • Gaps disappear if adopted before 12 months.

🧠 Genetics vs. Environment

• Genetics play a role in individual differences (twin studies).

• But group achievement gaps are mostly environmental (poverty, school quality).

• Confounding factor: Wealthy, educated parents → better schools, not just better parenting.

✅ Key Takeaways

• U.S. children lag behind globally, especially in applied math.

• Differences between tests (TIMSS vs. PISA) explain conflicting rankings.

• Teacher training and curriculum gaps hurt U.S. performance.

• Achievement gap reflects deep social/economic inequalities.

• Early intervention and stable environments can drastically improve outcomes.

• Genetics matters for individuals, but not the achievement gap across racial/economic groups.

Gender & Academic Achievement

1. Biological vs. Cultural Debate

• There are early differences in learning between boys and girls (e.g., girls learn words earlier).

• Boys and girls have biological differences, but the question is whether these cause differences in academic achievement.

2. Larry Summers Controversy

• Summers (former Harvard president) suggested three reasons for fewer women in elite Math/Science positions:

  1. Women less attracted to high-powered jobs (family focus).

  2. Fewer women are exceptionally gifted in relevant areas.

  3. Socialization and discrimination.

• Used SAT score variance to argue boys are more likely to be outliers (very high scores).

• Criticized for insufficient evidence and misusing SAT data.

3. U.S. and International Test Data (TIMSS)

• Grade 4: Boys slightly outperform girls in Math/Science in the U.S.

• Grade 8: No significant difference; girls often outperform boys globally.

• Math performance varies by country:

  • Boys outperform in 12 countries (often less wealthy).

  • Girls outperform in 16 countries (many in Middle East/Asia).

  • 23 countries show no difference.

• Reading: Girls outperform boys in almost all countries.

4. Key Implications

• No consistent biological advantage for boys.

• Cultural factors (e.g., expectations, education systems) likely play a much larger role.

• Example: Asian students show no gender difference in math majors; cultural context matters.

5. Giftedness & Achievement

• Girls get better grades than boys in high school.

• In gifted student studies: boys do better on SAT, but girls get better grades in the same classes.

• SAT is not a reliable predictor of real academic performance or future success.

Learning Styles

1. Common Belief

• Many believe they have a preferred learning style (visual, auditory, verbal, etc.).

2. Scientific Review

• A recent review breaks the learning styles question into two parts:

  1. Do people have preferences? → Yes, people report preferences for how they like to receive information.

  2. Do these preferences affect learning outcomes? → To be continued in the next section (not included in your excerpt).

1. Learning Styles: Do They Improve Learning?

• People do have learning preferences (e.g., visual or verbal), and these preferences are stable over time. People also tend to choose information presented in their preferred style.

• The key question is whether learning improves when instruction matches a person’s preferred style.

• Most existing studies fail to test this question rigorously (i.e., using random assignment to matching/mismatching conditions).

• Of the thousands of studies on learning styles, only one found weak evidence supporting matched styles, and three strong studies found no such benefit.

• Conclusion: There's no strong scientific support that teaching to someone's preferred learning style improves learning outcomes.

• Implication: Teachers and learners should use evidence-based strategies that benefit most learners, rather than tailoring instruction to individual preferences.

2. Effective Study Techniques

The Problem

• Most students aren’t taught how to study effectively.

• Even those taught study skills often don’t use techniques that work.

Recognition vs. Recall

• We often confuse recognition ("I’ve seen this before") with recall ("I can retrieve it from memory").

• Reading notes may feel effective due to familiarity, but recall-based studying is much more beneficial.

Key Principles of Effective Studying

A. Retrieval Practice

• Definition: Actively trying to recall information from memory (e.g., flashcards).

• Why it works: Strengthens memory more than passive review, even if you get the answer wrong first.

• Example: Flashcards work if you try to recall before flipping.

B. Spaced Repetition (Spacing Effect)

• Definition: Spreading study sessions over time instead of cramming.

• Why it works: Helps long-term retention, even if you forget a little between sessions.

• Best timing: Review when you’re about to forget (not immediately).

C. Combining Retrieval + Spacing

• Best results come from combining both strategies:

  • Practice recalling material.

  • Space the sessions out (don’t study all at once).

• Example Study: Students who used both retrieval and spaced learning remembered the most.

3. Cramming: When It Works, When It Doesn't

• Cramming can work if the test is immediately after.

• However, information is usually quickly forgotten, so it’s bad for finals or long-term knowledge.

• If the goal is long-term retention (e.g., final exam or real-life use), cramming is ineffective.

4. Practical Scheduling Recommendations

Study Session Scheduling

• Don't study all at once. Space out your time.

  • E.g., for a test in two weeks:

    • 3 hours today

    • 2 hours in one week

    • 1 hour a day before the test

Within-Session Scheduling

• Even spacing topics within a single session (or mixing topics, called interleaving) improves retention.

• Brief pauses or topic shifts increase the effectiveness of your studying.

Tools That Help

• Use spaced repetition software or even a planner/calendar to schedule reviews.

• Any spacing is better than no spacing, so don’t stress about perfection.

Bottom Line

• Forget learning styles — they’re not supported by science.

• Focus instead on:

  • Retrieval practice

  • Spaced repetition

  • Interleaving topics

• These evidence-based strategies will help you learn better and remember longer.

1. “Nation’s Report Card Finds Falling Test Scores, Even Pre-COVID” (Washington Post, Oct. 2021)

This article reports troubling declines in reading and math scores for 13-year-olds in the U.S. based on the National Assessment of Educational Progress (NAEP). The drop, recorded before the COVID-19 pandemic, was the first in 50 years and disproportionately affected low-performing students, suggesting a widening achievement gap. Black and Hispanic students saw notable declines, while White students’ scores remained flat. The article also highlights reduced student engagement with reading and a decrease in advanced math coursework, such as algebra, in middle school. While long-term trends show improvement since the 1970s, the recent declines underscore systemic issues in education and raise concerns about post-pandemic recovery.

2. “Adoption Is a Successful Natural Intervention Enhancing Adopted Children’s IQ and School Performance” (Van IJzendoorn & Juffer, 2005)

This meta-analysis of 62 studies involving over 17,000 adopted children shows that adoption can significantly boost children's IQ and academic outcomes, especially when compared to peers left in institutional care or birth families. Adopted children score higher on IQ tests and perform better in school than those who remained behind. When compared to their current (nonadopted) peers, adoptees have similar IQs but often lag slightly in school performance and language. Notably, adopted children are referred to special education services at twice the rate of their peers. Factors such as age at adoption and prior adversity (e.g., neglect, malnutrition) influence outcomes, with earlier adoptions leading to better school performance. Despite these challenges, the study concludes that adoption represents a powerful intervention that fosters resilience and cognitive recovery.