Scientific Reasoning Research Institute - Product

For TinkerPlots Software and Materials

Jang Kreetong — Sat, 27 Oct 2007 15:36:40 +0000

go to www.tinkerplots.com

Click here for downloads, support, activities.

TinkerPlots has a new publisher.

TinkerPlots was developed at the University of Massachusetts as part of the NSF-funded TinkerPlots project.

Energy in the Human Body

lstephens — Mon, 15 Feb 2016 16:16:41 +0000

A Middle School Life Science Curriculum

Group Page:

CLSG

by:

Mary Anne Rea-Ramirez, Maria Nunez-Oviedo, John Clement

Energy in the Human Body is an exciting curriculum for grades 6-8 based on learning theory. It actively engages students and teachers in the construction of new knowledge through multiple strategies. With it, teachers take on the role of facilitator and co-constructor with your students.

Because we believe youth need and want to take responsibility for their own bodies and their health, we feel it is important to find better ways to help them construct mental models of their bodies that they can use to reason about their world. That is the purpose of this curriculum. In addition, new teaching strategies for helping students in the difficult process of constructing mental models of complex topics have been developed. We hope you will find it useful both in teaching this curriculum and in other areas as well.

Go to the Curriculum: http://www.cesd.umass.edu/energyinthehumanbody/

The Energy in the Human Body curriculum is the result of eight years of research on student learning and teaching strategies that assist students in constructing complex mental models of how their bodies work. It has been developed by a team of researchers and expert teachers in an attempt to find strategies that help students learn important concepts in life science. Students learn about how their own bodies use the energy they get from food. They learn why we breathe in oxygen, and breathe out carbon dioxide. Most importantly, they learn why their bodies are designed the way they are and apply this knowledge to common everyday occurrences. Instead of simply memorizing vocabulary, students learn concepts that will be important in their study of Biology later in their academic career. Students will have a chance to relate structure to function, to understand how the way a part of the body is structured relates to the way it works.

Supported by grants from the National Science Foundation [ESI-9911401 and REC-0231808] John Clement, PI. Copyright 2004 Mary Anne Rea-Ramirez. All rights reserved.
Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Strategies For Using Interactive Simulations In Science Class

lstephens — Sat, 30 Jan 2016 00:47:24 +0000

a website for educators

Group Page:

CLSG

Contact(s):

Clement, John

Funding:

NSF Grants DRL-1222709 and DRL-0723709

http://www.umass.edu/teachingstrategies/

This manual is the product of a long-term project designed to investigate the different teaching strategies that science teachers use with simulations in the classroom. The site contains a collection of approximately 40 strategies for using simulations in science classes.

The manual is set up in two sections shown in the lists below. The first section is composed of nine core strategies and contains some video examples. We chose to highlight these strategies because they show different ways simulations can be used to enhance science lessons and support student learning. Many of these strategies have not been written about before.

Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mental Simulation

Jang Kreetong — Tue, 14 Feb 2012 20:24:03 +0000

Group Page:

CLSG

Contact(s):

Clement, John

by:

John Clement

This monograph presents a theory of creativity and imagery-based conceptual learning in science that was developed on the basis of think-aloud protocols from experts and students.

How do scientists use analogies and other processes to break away from old theories and generate new ones? This book documents such methods through the analysis of video tapes of scientifically trained experts thinking aloud while working on unfamiliar problems. Some aspects of creative scientific thinking are difficult to explain, such as the power of analogies, the use of physical intuition, and the enigmatic ability to learn from thought experiments. The book examines the hypothesis that these processes are based on imagistic mental simulation as an underlying mechanism. This allows the analysis of insight ("Aha!") episodes of creative theory formation. Advanced processes examined include specialized conserving transformations, Gedanken experiments, and adjusted levels of divergence in thinking. Student interviews are used to show that students have natural abilities for many of these basic reasoning and model construction processes and that this has important implications for expanding instructional theories of conceptual change and inquiry.

Table of Contents:

http://people.umass.edu/clement/pdf/ClementCreativeTOC.pdf

Annotated Table of Contents:

http://people.umass.edu/clement/pdf/ClementCreativeAnnotatedTOCf.doc

Model Based Learning and Instruction in Science

Jang Kreetong — Tue, 14 Feb 2012 20:15:50 +0000

Group Page:

CLSG

This book is a collection of chapters by our research team describing new, model-based teaching methods for science instruction. It presents research on their characteristics and effectiveness, exploring them in a very diverse group of settings: middle school biology, high school physics, and college chemistry classrooms. Mental models in these areas such as understanding the structure of the lungs or cells, molecular structures and reaction mechanisms in chemistry, or causes of current flow in electricity are notoriously difficult for many students to learn. Yet these lie at the core of conceptual understanding in these areas. Six different levels of organization for teaching strategies are described, from those operating over months (design of the sequence of units in a curriculum) to those operating over minutes (teaching tactics for guiding discussion minute by minute).

DataScope

konold — Thu, 14 Jan 2010 22:26:23 +0000

Group Page:

SERG

Funding:

US National Science Foundation Grant MDR-8954626

Starting date:

1990

by:

Clifford Konold and Craig D. Miller

DataScope® was a Macintosh Classic data-analysis program from the 1990s with accompanying data sets and instructional activities for grades 9-13. The design of DataScope was heavily influenced by our belief that the best way to motivate students to learn and use statistical techniques is through exploring issues of concern to them. It was designed to be computationally powerful yet simple to use. Displays included histograms, box plots, scatterplots, one and two-way tables of frequencies, and tables of descriptive statistics. The software was intended for use in introductory courses stressing exploratory data analysis of fairly large data sets. It encouraged students to make initial judgments of relationship by visually comparing plots. A generalized "grouping" capability permitted the formation of plots (and tables) grouped on different levels of a chosen variable. Additional features included point ID on scatterplots and box plots, and random resampling for testing hypotheses about differences between two medians, frequencies in a 2 X 2 table, and correlation coefficients.

We used DataScope to support student projects in which they formulated their own questions, collected and analyze their data, and wrote a brief report. We also made use of several large data sets, including results of a student survey, almanac-type information on 104 countries, and Olympic gold-record times/distances from a selection of track-and-field events. These data sets were incorporated into the instructional units we designed for use with the software.

The following articles and reviews provide additional information about instructional use of DataScope. See also the Chance Plus Project.

Articles

Konold, C. (1995). Datenanalyse mit einfachen, didaktisch gestalteten Softwarewerkzeugen für Schülerinnen und Schüler. Computer und Unterricht, 17, 42-49. (English version: "Designing data analysis tools for students.")

Konold, C. (1995). Issues in assessing conceptual understanding in probability and statistics. Journal of Statistics Education, 3(1). http://www.amstat.org/publications/jse/v3n1/konold.html

Konold, C. (1994). Understanding probability and statistical inference through resampling. In L. Brunelli & G. Cicchitelli (Eds.), Proceedings of the First Scientific Meeting of the International Association for Statistical Education (pp. 199-211). Perugia, Italy: Università di Perugia.

Reviews

Ernie, K. (1996). Technology reviews: DataScope and Prob Sim. Mathematics Teacher, 89, 359-360.
Garfield, J. (1995). Software review: DataScope and Prob Sim.The Statistics Teacher Network, Winter , p. 7.

Key Works in Radical Constructivism

root — Sat, 16 Feb 2008 18:17:51 +0000

A collection of essays by Ernst von Glasersfeld

by:

Ernst von Glasersfeld (edited by Marie Larochelle)

Key Works on Radical Constructivism brings together a number of essays by Ernst von Glasersfeld that illustrate the application of a radical constructivist way of thinking in the areas of education, language, theory of knowledge, and the analysis of a few concepts that are indispensable in almost everything we think and do. Ernst von Glasersfeld's work opens a window on how we know what we know. The present work grew out of a desire to make more accessible this line of thought, to highlight its originality and consistency, and to illustrate its fecundity in the domains of cognition and learning. The first three parts of this book contain texts by Glasersfeld that outline the constructivist approach and explicate the frequently drastic reconceptualizations he has suggested. Both the last part and the postscript consist of commentaries by Edith Ackermann, Jacques Désautels, Gérard Fourez, Leslie P. Steffe and Kenneth Tobin, scholars in the fields that Glasersfeld has been concerned with. They examine a number of critical aspects pertaining to (radical) constructivism's current and future development, often tracing out paths that warrant further exploration and reflection, in particular concerning the sociopolitical dimension of knowledge.

Key works on radical constructivism is intended as a reference book for researchers, educators, and students of education---and for anyone interested in grasping, or deepening their grasp of, radical constructivism's tenets, ambitions and concerns. Readers will discover in this collection of firsthand contributions the contours of a bold, contemporary debate about a most compelling current of thought.

Ernst von Glasersfeld was brought up with more than one language from the very beginning. This taught him early on that the realities people think and talk about are noticeably different. He was much influenced by Silvio Ceccato, the founder of the Operational School in Italy, and then by Jean Piaget's Genetic epistemology, to which, he believes, he was able to add some details. He worked as a language analyst at the Center for Cybernetics in Milan, directed a language research project for the Us Air Force from 1962 to 1970, and then taught as professor of cognitive psychology at the University of Georgia, USA. In 1987 he retired at the age of 75 and became Research Associate at the Scientific Reasoning Research Institute of the University of Massachusetts. Throughout, his main interest was how we come to know what we know and how thought and language are linked. He has published several books in English, German, and Italian.

Marie Larochelle is Full Professor at the Faculty of Education of Université Laval, Québec City. For many years, she has actively researched socioepistemological problems related to the teaching/learning of scientific knowledge. Her publications have been primarily in the fields of science education and constructivism. Her current research interests focus on how students and future science teachers figure or represent the conflicts, controversies, negotiations and socioethical issues that shape the practice of the technosciences.

ISBN: 978-90-8790-085-4 paperbound
ISBN: 978-90-8790-086-1 hardbound
[The book is available from Amazon.](http://www.amazon.com/exec/obidos/tg/detail/-/9087900856/ Amazon.com)

Springbok

root — Fri, 11 Jan 2008 23:23:38 +0000

A simple but rich mechanical system for teaching about the physics of jumping

Group Page:

PERG

Contact(s):

Leonard, William J.

(This is a companion website to the article Springbok: The physics of jumping, published in The Physics Teacher.)

Springbok is our name for a simple mechanical system for teaching about the physics of jumping. A springbok consists of a large mass and a small mass connected by a spring; when compressed and then released, it jumps up into the air. (The name "springbok" comes from a South African gazelle noted for its grace and its delightful habit of springing suddenly into the air.)

A springbok is easy to make and engaging to study. It provides a rich context for exploring a wide range of physics concepts and principles, and it possesses a number of features that give it broad instructional value. There is much a student can learn about the physics of jumping from a purely conceptual analysis of this toy.

However, the simplicity of the spring-loaded design also allows for a straightforward quantitative analysis of jumping. A springbok is ideal for hands-on projects and science competitions. With an appropriate focus, a springbok can be used in a variety of instructional settings, from high school physical science to graduate mechanics.

An article providing both a conceptual and quantitative analysis of the springbok (the mechanical system, not the gazelle) can be found in the published paper Springbok: The physics of jumping.

ProbSim

konold — Sat, 24 Nov 2007 21:53:04 +0000

Software and activities for teaching probability via simulations

Prob Sim was a Macintosh (Classic) program from the 1990s with accompanying instructional activities designed for teaching probability via simulations in grades 6-13. To model a probabilistic situation, you:

construct a "Mixer" containing the elementary events of interest;
sample from the Mixer after specifying replacement options, sample size, and number of repetitions; and
search for or count specified events of interest in that and subsequent samples.

The program made the last step especially easy. Once analyzes had been conducted on one sample, you could press a button to see the results of the same analyses performed on a new random sample.

Prob Sim was especially useful for mathematics teachers striving to teach students probability in line with recommendations offered by the National Council of Teachers of Mathematics in their Principles and Standards for School Mathematics.

Also included with the software was a User's Guide and Instructional Activities.

System Requirements

Prob Sim was written in 1992, so you can run in on:

any Macintosh computer with 1MB of RAM or more, with
MacOS 6.0.5 - 9.2.2, or MacOS X with the Classic environment installed, and a
68000 or PowerPC processor (not an Intel processor)

We have tested it on recent versions of Macintosh's operating system (including OS X 10.4) and it appears to work well. But we cannot guarantee that it will continue to do so, and we are not planning any future updates.

Download

Prob Sim Software License

You are free to load Prob Sim onto as many machines as you like and use it freely. However, you cannot resell it or incorporate any parts of it, including the documentation or activities, into another product or publication without written permission.

Prob Sim is provided "as is" without any implied warranty. Users must assume complete responsibility for any errors or data loss while using the program.

Technical assistance, other than what is in the written documentation, is not available for Prob Sim. You are strictly on your own. (We should add that we have heard of no problems using Prob Sim.)

Download Form

To download this software, please read and complete this form.

If you experience problems with this form, please contact serg@srri.umass.edu.

Credits

Prob Sim was developed by:

Clifford Konold and Craig D. Miller
Scientific Reasoning Research Institute
University of Massachusetts, Amherst, MA, USA

The development of Prob Sim was funded by a grant from the National Science Foundation (grant no. MDR-8954626). The Prob Sim software and related materials are copyrighted 1992-2003 by Clifford Konold.

Preconceptions in Mechanics

root — Sat, 27 Oct 2007 15:49:20 +0000

Lessons dealing with conceptual difficulties

Group Page:

CLSG

by Charles Camp and John Clement. Contributing authors: David Brown, Kimberly Gonzalez, John Kudukey, James Minstrell, Klaus Schultz, Melvin Steinberg, Valerie Veneman, and Aletta Zietsman. College Park, MD: American Association of Physics Teachers. Second Edition 2010.

The nine units in this high school physics curriculum focus on areas where students have exhibited qualitative preconceptions --- ideas that they bring to class with them prior to instruction in physics. Research has shown that certain preconceptions conflict with the physicist's point of view. It has also shown that some of these conflicting preconceptions are quite persistent and seem to resist change in the face of normal instructional techniques. The motivating idea for this book is to provide a set of lessons that are aimed specifically at these particularly troublesome areas and that use special techniques for dealing with them. Ideas in the lessons can be used to supplement any course that includes mechanics. Many preconceptions that pose difficulties are not simply random errors, nor are they due to inattention or failure to remember key ideas. To help a student learn physics in areas where there are persistent preconceptions, these lessons use a number of special strategies. Most lessons are built around a target problem (a problem designed to draw out a conflicting preconception that has been shown to be present in many students). Another strategy is the use of anchoring analogies or examples--situations where many students' intuitions are in agreement with the physicist's view. Such an intuition can be developed as a rival to, and eventually predominate over, a conflicting preconception.

Minds*On Physics

root — Sat, 27 Oct 2007 15:34:42 +0000

A constructivist, active-learning curriculum for high school physics

Contact(s):

Leonard, William J.

MOP is a one-year curriculum for high school physics. It is the result of a materials development project supported by the National Science Foundation, and its design was guided by educational research findings. The curriculum integrates topics traditionally taught at different times of the year, and students are expected to develop conceptual understanding of physics while improving problem-solving proficiency.

GrowAverage

Sun, 14 Jan 1990 23:06:50 +0000

Group Page:

SERG

Funding:

US National Science Foundation Grant MDR-8954626

by:

Clifford Konold (design) and Ian Fraser (programming)

Grow Average© was a Macintosh (Classic) program from the 1990s for demonstrating the Law of Large Numbers and the Central Limits Theorem. The program has two running modes: "grow sample" and "grow average.

The mode "grow average" allows the user to construct sampling distributions (distributions of sample averages) of various sizes. These distributions are saved so that sampling distributions based on different-sized samples can be visually compared. The important insight, of course, is that statistics based on larger samples are less variable than statistics based on smaller samples. This property is referred to as the "Law of Large Numbers."

The mode "grow sample" demonstrates what happens to the mean (or median) of a sample as it grows in size. When a sample is still relatively small, its average can be seen to fluctuate, sometimes wildly, as new observations are added. As the sample gets larger, its average stabilizes near the population average. We designed this mode to help suggest to students a "mechanism" behind the Law of Large Numbers: namely, that whenever the sample average differs from the population average, there are generally a greater number of population elements to sample from that will bring the sample average closer to the population average than there are population elements to sample from that will take the sample average farther from the population average. Furthermore, the farther the sample average is from the population average, the higher in general the probability that the next observation will bring the sample average closer to the population average.

In developing this program, we have attempted to make it useful for a variety of instructional settings and levels. The program can display not only means (and SDs) but medians (and IQRs), sample with or without replacement, has several different levels of sample size and various sampling speeds, and can use any data stored as a text file (with certain limitations).

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