Adapting and Implementing Innovative Material in Statistics (AIMS)
This NSF-funded project developed lesson plans and activities based on innovative materials that have been produced in the past few years for introductory statistics courses. These lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons, which build on implications from educational research, involve students in small and large group discussion, computer explorations, and hands-on activities.
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AIMS & GAISE
The AIMS materials have been aligned with the 2005 Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. Each of the six recommendations from this report is listed below along with an indication of how the AIMS materials have been aligned with it.
- Emphasize statistical literacy and develop statistical thinking: The AIMS materials help build students’ statistical literacy by having them read their text and complete study questions, and respond to literacy oriented assessment items.
- Use real data: The AIMS materials use data gathered from students (student survey data, body data) and analyze other real data sets of interest (e.g., college admissions data)
- Stress conceptual understanding rather than mere knowledge of procedures: The AIMS materials focus on the nine big ideas (data, model, distribution, center, variability, comparing groups, samples, inference, and covariation), and develop them throughout the course. Students first encounter these ideas informally, and then as they revisit them, the materials aid in moving them to more formal understanding and reasoning.
- Foster active learning in the classroom: The AIMS lesson plans suggest how teachers may guide students through activities where they are actively engaged in making and testing conjectures, working in small groups, explaining their reasoning, and learning together. The materials also incorporate versions of many innovative student activities.
- Use technology for developing conceptual understanding and analyzing data: The AIMS materials use Fathom™ for data analysis and exploration, Tinkerplots™ to help students understand and reason about graphs, Sampling SIM to simulate data to make informal inferences, and several applets to illustrate abstract concepts.
- Use assessments to improve and evaluate student learning: Three free resources can be used to assess students' statistical reasoning: The ARTIST website, the ARTIST Item Database, and the ARTIST Topic Tests and CAOS tests. These are all located at the ARTIST website.
AIMS Principal Investigators
- Joan Garfield (University of Minnesota)
- Robert delMas (University of Minnesota)
- Andrew Zieffler (University of Minnesota)
AIMS Contributing Author
- Dani Ben-Zvi (University of Haifa)
- Michelle Everson (University of Minnesota)
- Jared Dixon (University of Minnesota, Graduate Research Assistant)
- Beng Chang (University of Minnesota, Graduate Research Assistant)
- Robert Gould (University of California, Los Angeles)
AIMS Advisory Board
- Beth Chance (California Polytechnic State University)
- George Cobb (Mount Holyoke College)
- Bill Finzer (KCP Technologies)
- Cliff Konold (University of Massachusetts Amherst)
- Robin Lock (St. Lawrence University)
- Dennis Pearl (The Ohio State University)
- Allan Rossman (California Polytechnic State University)
- Richard Scheaffer (University of Florida)
References, Papers, and Presentations
delMas, R., Garfield, J., & Zieffler, A. (2008). Adapting and Implementing Innovative Materials in Statistics Courses (AIMS). Poster presented at the Joint Mathematics Meetings, San Diego, CA.
delMas, R., Garfield, J., & Zieffler, A. (2008). Innovative, research-based activities for a first course in statistics. Presentation at the Joint Mathematics Meetings, San Diego, CA.
Everson, M., Zieffler, A., & Garfield, J. (2008). Implementing new reform guidelines in teaching introductory college statistics courses. Teaching Statistics, 30(3), 66–70.
Garfield, J. & Ben-Zvi, D. (2008). Developing students' statistical reasoning: Connecting research and teaching practice. New York: Springer.
Garfield, J., delMas, R., & Zieffler, A. (2007). Studying the role of simulation in developing students' statistical reasoning. Proceedings of the 56th Session of the International Statistical Institute (ISI), Lisbon, Portugal.
Garfield, J., delMas, R., & Zieffler, A. (2007). Select AIMS materials. Presentation at Stat Chat. Macalester College, St. Paul, MN.
Zieffler, A., Garfield, J., & delMas, R. (2007). Studying the role of simulation in developing students' statistical reasoning. Presentation at the 56th Session of the International Statistical Institute (ISI), Lisbon, Portugal.
Zieffler, A., Garfield, J., delMas, R., & Gould, R. (2007). Studying the development of college students' informal reasoning about statistical inference. In J. Ainley and D. Pratt (Eds.) Proceedings of the 5th Statistical Reasoning, Thinking and Literacy (SRTL) Research Forum, Coventry, England.