Reading Stats. in Australia

Introduction

  • Significant increase in cultural and academic diversity among commencing tertiary students over the past decade.

    • Total higher education students rose by 43% from 1990 to 2000, reaching nearly 700,000.

    • Overseas students increased fourfold, approaching 100,000, resulting in a ratio of one-in-seven students.

  • The increase in diversity is accompanied by varying academic capabilities.

  • Professional work demands a broad range of linguistic and numerical skills from graduates.

  • Mathematics and statistics educators face challenges in developing curricula that:

    • Address language-related difficulties for language minority students.

    • Cater to the mathematical backgrounds of diverse student cohorts.

    • Enhance learning outcomes for all.

  • The paper reflects on approaches based on research into:

    • Student conceptions of statistics.

    • Language needs of professionals in mathematical sciences.

Importance of Mathematical Education

  • Recognized by governmental and professional bodies as critical for economic and social development.

    • A review highlighting the significance of advanced mathematical services to Australia (1995-2010).

  • Government initiatives targeting declining standards and interest in mathematics.

  • Integration of generic skills into university curricula.

    • Statistical study often misconceived by students as unrelated to their domains.

Research on Student Learning in Statistics

  • Investigated the effects of:

    • Educational approaches

    • Learning environments

    • Materials used

    • Assessment methods

  • Studies on students’ attitudes and conceptions of statistics, focusing particularly on:

    • Probability understanding.

    • Benefits of teaching methodologies on statistical learning.

Theoretical Frameworks

  1. Phenomenographic Approach

    • Study of students’ varying conceptions of statistics found significant differences in understanding and learning approaches.

    • Ranges from limiting to expansive views.

    • Limiting views lead to fragmented learning; expansive views promote integrated understanding.

  2. Professional Entity Model

    • Introduces three levels of understanding professional work, guiding curriculum design.

      • Extrinsic Technical Level: Technical components used in work situations.

      • Extrinsic Meaning Level: Developing meaning from discipline-related objects (e.g., data).

      • Intrinsic Meaning Level: Personal connection to professional identity.

  3. Critical Discourse Analysis (CDA)

    • Examines how social power dynamics are reflected in language.

    • Emphasis on communication skills necessary in modern workplaces.

    • Adaptation to client language needs rather than expecting clients to understand professional jargon.

  4. Equity and Inclusion in Education

    • Commitment to equitable learning environments in education.

    • Principles supporting diversity and inclusion in university settings.

    • UTS's Equity Plan emphasizes fair treatment and respect for all students.

Curriculum Design Strategies

  • Focus on enhancing language, numeracy, and communication skills through diverse student cohorts.

  • Development of flexible curricula using authentic materials relevant to students’ disciplines (e.g., articles from tourism, environmental science, etc.).

    • Integration of language and statistical comprehension:

      • Questions designed addressing both skills, encouraging higher-order analytical thinking.

  • Prior materials developed to advance students’ understanding of statistics and enhance communication skills include:

    • Textbooks

    • Video resources

    • Laboratory materials

Reading Statistics Framework

  • Structure designed for reading and comprehension alongside statistical insights.

  • Introductory and specific questions guide students through:

    • Understanding author backgrounds and purposes.

    • Analyzing research methodologies and statistical techniques utilized in articles.

  • Example questions explore:

    • Identification of research gaps.

    • Evaluation of graphical data representation.

    • Ethical considerations in research design.

Conclusion

  • The paper illustrates a comprehensive approach to curriculum design aimed at diverse students.

    • Links between statistical understanding and effective communication skills emphasized.

    • Adaptability of these frameworks for various academic disciplines.

  • Acknowledgment that phenomenographic research can yield practical applications in education.

  • Future research opportunities highlighted for linking statistical learning and communicative competence.