Dani Ben-Zvi dbenzvi@univ.haifa.ac.il The University of Haifa, Israel

1. Helping Students Develop Statistical Reasoning:Implementing a Statistical Reasoning Learning Environment (SRLE) Dani Ben-Zvidbenzvi@univ.haifa.ac.ilThe University of Haifa, Israel EncontroInteramericano de EducaçãoEstatística

2. The Challenge of Learning and Teaching Statistics • Current research studies suggest very different ways of teaching than traditional lectures (Garfield and Ben-Zvi, 2007) • Leaving familiar teaching methods to try active learning techniques is challenging

3. Statistical Reasoning Learning Environment SRLE • A model for an interactive, introductory statistics course that is designed to develop students’ statistical reasoning • This model is built on the socio-constructivist theory of learning

4. Building on socio-constructivist principles of learning • New knowledge and understandings are based on the existing knowledge and beliefs we already have and are grounded in our experiences (e.g., Cobb, 1994; Piaget, 1978) • People learn by constructing knowledge (rather than by receiving knowledge) while interacting with adults or peers (Vygotsky, 1978) • We learn by doing

5. Implication of current theories of learning • Good instructional practice consists of designing student-centered learning environments that stimulate students to construct knowledge and understanding • Activities that provide students many opportunities to think, reason, and reflect on their learning, as well as discussing and reflecting with their peers • The teacher is cast as an instructional coach, a co-learner, an enculturator, or a facilitator, rather than as a conduit of knowledge in a teacher-centered classroom

6. Why change? • A student-centered approach is more effective in helping students build a deep understanding of statistics and to be able to transfer what they have learned in subsequent classes or in the real world • Students in the “teaching is telling” approach rarely have a chance to develop a deep understanding of what they have “learned,” and quickly forget it after they complete a course

7. Principles of a Statistical Reasoning Learning Environment (SRLE) • Focus on central statistical ideas • Use real and motivating data sets • Design classroom activities to support development of students’ reasoning • Use of appropriate technological tools • Promote classroom discourse • Use alternative methods of assessment (Cobb and McClain, 2004)

8. 1. Focus on central statistical ideas

9. 2. Use Real and Motivating Data • Data should be the focus for statistical learning (Franklin and Garfield, 2006) • Throughout a course, students need to consider methods of data collection and production and how these methods affect the quality of the data and the types of analyses that are appropriate • Interesting data sets motivate students to engage in activities, especially ones that ask them to make conjectures and think about a data set before analyzing it

10. 3. Classroom activities • Use of carefully designed, research-based activities that promote student learning through collaboration, interaction, discussion, data, and interesting problems (Bransford, Brown, & Cocking, 2000) • Activities that promote active learning

11. Types of classroom activities

12. The data investigation cycle (PCAIC)

13. 4. Appropriate technological tools

14. 5. Promote classroom discourse Engage students in sustained exchanges that focus on significant statistical ideas: • Learn to question each other • Explain their reasoning and justifytheir answers and arguments • Express their views, even if they are tentative. Create a safe classroom climate. What would happen if? What do you think and why?

15. 6. Alternative assessment Teachers: • Become knowledgeable about alternative methods of assessment • Learn about student projects as a form of authentic assessment Types of assessments: • Statistical literacy (e.g., critique a graph in a newspaper) • Statistical reasoning (e.g., write a meaningful short essay) • Feedback to each other or the instructor ARTIST Website https://app.gen.umn.edu/artist

18. Moving to a SRLE Moving to SRLE approach is faced with many challenges: students, colleagues, and institution, instructors. (Garfield and Ben-Zvi, 2008) Some teachers: • View statistics as mathematics • Teach statistics in terms of computations and formulas • lack experience in analyzing and exploring real and messy data • Believe there is a single correct answers to most statistics problems • Are not comfortable with open-ended discussions • Are not comfortable with the inquiry-based pedagogical methods • Do not understand the important big ideas of statistics and data analysis.

19. Moving to a SRLE • The first step: Align current course and materials with the components of a SRLE and pick a starting point • Sample activities in the AIMS Website (http://www.tc.umn.edu/~aims) • Careful and steady change over a period of time may lead to a successful implementation of a SRLE in a statistics course, rather than trying a radical, all at once change

20. Summary: Key elements SRLE

21. Additional Reading

22. Read more about theses ides: • Garfield J., & Ben-Zvi, D. (2009). Helping students develop statistical reasoning: Implementing a Statistical Reasoning Learning Environment. Teaching Statistics, 31(3), 72-77. • Ben-Zvi, D., & Garfield, J. (Editors) (2004). The challenge of developing statistical literacy, reasoning, and thinking. Dordrecht, the Netherlands: Kluwer Academic Publishers. • Garfield, J., & Ben-Zvi, D. (2007). How students learn statistics revisited: A current review of research on teaching and learning statistics. International Statistical Review, 75(3), 372–396.

23. Obrigado! For further questions: Dani Ben-Zvidbenzvi@univ.haifa.ac.ilThe University of Haifa, Israel

24. The Connections learning environment Hands-on small-groups activities Presentation preparation Final project presentation Scaffolding instructional activities Investigationsusing Excel Minds-on: whole-class discussions