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Education for Innovation: the Role of Arts and STEM Education OECD/France Workshop – Paris, 23-24 May 2011. Effective Teaching for Improving Students ’ Motivation, Curiosity , and Self-Confidence in Science. Evidence from PISA 2006. Francesco Avvisati

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effective teaching for improving students motivation curiosity and self confidence in science

Education for Innovation: the Role of Arts and STEM EducationOECD/France Workshop – Paris, 23-24 May 2011

Effective Teaching for ImprovingStudents’ Motivation, Curiosity, and Self-Confidence in Science

Evidence from PISA 2006

Francesco Avvisati

OECD Centre for EducationalResearch and Innovation (CERI)

outline
Outline
  • PISA measures of behavioural skills
  • The paradox of international comparisons of interest, curiosity, and self-confidence
    • between and within-country evidence
  • Teaching activities’ effectiveness on students’ learning
    • within-country evidence
pisa measures of behavioural skills
PISA measures of behavioural skills
  • PISA Test
    • interest in science topics (“embedded”)
  • PISA Context Questionnaire
    • Enjoyment of science
    • Science self-concept
    • Science self-efficacy
the test score interest paradox robustness
The Test-Score/Interest Paradox Robustness
  • Interest is less sensitive to cultural biases
  • Adding confounders:
the test score interest paradox conclusion
The Test-Score/Interest Paradox Conclusion
  • Some school cultures (teaching cultures?) have diverging effects on interest and scores
    • High stake testing? (extrinsic motivation)
    • Low academic standards?
    • Teaching to the test, lack of cognitive activation?

Japan, Germany, Korea, France –

United States, Chile, Israel, Portugal

effective teaching motivation
Effective Teaching: Motivation
  • What teaching activities are associated with better test-scores?(subject-based competences)
  • What type of teaching develops motivation, curiosity and self-confidence the most? (behavioural competences)
effective teaching data
Effective Teaching: Data

student reports on 4 clusters of activities

  • Interaction
  • Collaboration and participatory exchanges
  • Hands-on
    • Guided activities around lab experiments
  • Application
  • Drawing connections between school science and the outside world
  • Investigation
    • Autonomous student inquiries
effective teaching data1
Effective Teaching: Data
  • example: focus on models & applications
effective teaching methods
Effective Teaching: Methods

Problems with interpreting correlations causally:

  • Pupils differ ex-ante (correlation might be spurious)
    • Control for observable individual and peer characteristics; control for reading scores.
    • Explore robustness across countries
  • Measurement error and reverse causality in reports of teaching activities
    • “back-up” reports with peer reports (instrumental variables estimation)
effective teaching interpretation
Effective Teaching: Interpretation
  • How big are effect sizes?
  • example: focus on models & applications

How to interpret a unit increase? (+1 standard deviation)

based on: “in all lessons” = every single lsn, “in most lsns” = every 2 lsns, “in some lsns” = every 5 lsns, “never or hardly ever” = every 10 lsns.

conclusion
Conclusion
  • International comparisons do not need to limit themselves to “cognitive” test scores;
  • Patterns diverge between subject-based skills and science-related attitudes;
  • Inquiry based activities: effectiveness hinges critically on guidance;
  • Application activities foster positive attitudes to learning and self.