Intervention methodology and the quest for the autonomous learner in mathematics

1. Intervention methodology and the quest for the autonomous learner in mathematics Tania Nethercote

2. Thinking • Learning is a natural process. It happens without schools and teachers. If we want to change what people learn we have to intervenein the natural process of learning. • What student know and what teachers know influence what schooling is. For schooling to change we have to change what students and teachers know. • What teachers and students know will change. How do we promote learning that is appropriate and timely? • Who better to be in control of what needs to be learned than the learner. How do they learn to exploit all resources to secure their future?

3. Research Question If autonomous learning is a desired outcome for students, how do we intervene? With students? With teachers?

4. Context • ASMS - specialist science and mathematics-based school • Years 10 and 11 study an interdisciplinary curriculum • Curriculum design – constant state of flux – personalised learning opportunities for students. • Students need to demonstrate interest in pursuing a mathematics or science based career. • Teachers - innovation and research professional learning requirement - expected to provide professional learning opportunities. • Physical environment is open plan. • Metacognition is a whole school focus.

5. Typical Method: Case Study of Action Research Unique - Unique + Student reflective comments Student Autonomy (STUDENT ARTEFACTS) • Teachers collect student comments that reflect “typical” and “unique positive” and “unique negative perspectives (see diagram). • Two collection points, approximately six months apart. Leadership and Management Strategies (TEACHER SURVEY) • Teacher survey • Reflect on professional learning community • Which factor • is most important ? • is least important ? • is best supported? • needs the most improvement? • Reflect on thinking skills used • Which thinking skills • is most important ? • is least important ? • is best supported? • needs the most support?

6. Results: Student Autonomy

7. Results: Student Autonomy

8. Results: Student Autonomy

9. Results: Student Autonomy TABLE: Example demonstrating movement towards Expert Self-Regulation (Zimmerman. 2002)

10. Results: Leadership and Management PROFESSIONAL LEARNING COMMUNITY mostimportant COLLABORATION! leastimportant (little consensus - ⅓ Shared Norms) best supported COLLABORATION! needs most improvement (eclectic responses - some Shared Norms featured) THINKING SKILLS FOR INNOVATION most important (diversity of opinion -Collaborative Inquiry, Paying Attention featured) least important IMAGING! best supported COLLABORATIVE INQUIRY! needs most support (diverse comments - Paying Attention featured)

11. Results: Leadership and Management • Innovation in mathematics education requires teachers to work collaboratively • Collaboration is supported by de-privatization of practise, time to meet and talk and teacher empowerment. • Neither collaboration nor innovation is easy • Risks are easier to take as part of a group • Working collaboratively places different often contrasting and conflicting stressors on different individuals • Leaders address needs of individual teachers • Meetings structure allow sand encourages learning, sharing, conversation, writing and debate. • Observations, beliefs and ideas need to be heard and valued. • Shared norms and values are an asymptotic aspiration • Norms and values in a constant and irregular state of flux • School vision and teacher well-being is a juggle • Need to help individuals find their own autonomy within team planning • Different preferences about thinking for innovation used metacogntively • Least important might thinking skills - possible potential for growth ?( links between imaging and the development of conceptual knowledge)

12. Conclusions • Students can learn to be more self-directed. • Self-direction is learnt different ways and at different rates for different students. • Scaffolding thinking and metacognition supports self-directedness. • Goals for self-regulation need to be explicit • Collaboration is essential for innovation • Improvement needs to be ongoing • Norms and values are in a constant state of flux • Future needs are far too eclectic to trust a single prescribed methodology • Metacognition allows teachers (and students) to become more strategic and flexible • Teachers and students need metacognitive knowledge to co-create learning environments • Further investigation • What is the relationship between self-directedness and self-differentiation? • What are appropriate professional learning opportunities for teachers? .

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