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Integrative Analysis of Instruction
Using the Framework of ISM
This page has not been revised
since May 2001, but
the version on another website has been revised since then,
and it's part of a new website that has many more pages,
so I strongly recommend that you read
THE
REVISED VERSION.
This page describes the analysis of a fascinating classroom where "inquiry" learning occurs. Sometime in the future, I'll connect this with the Activity and Inquiry page, which (when it is written) will discuss the distinctive benefits of two types of learning (direct and inquiry) and the advantages of an eclectic approach that includes a variety of instructional techniques.
My PhD dissertation included two major
objectives:
1. Construct an integrative model
of "scientific method."
2. Use this model to analyze the
instruction -- including both the planned activities and the ways these
activities are put into action by teacher and students in the classroom
-- that occurs in an innovative, inquiry-oriented science course.
The first objective, a model of Integrated Scientific Method, is described in the main body of this website, beginning with the Goals page and Science page. In the near future the second objective, the ISM-based analysis of an innovative classroom, will be available only in the form of RTF files (Rich Text Format) that can be opened from within almost all word processors. Files containing the analysis (as described below) can be downloaded to your hard disk: Chapters 3 and 4 and the Appendix.
This web-page outlines the parts of
my dissertation containing the instructional analysis.
First, however, there will be a brief
description (from Chapter 1) of a fascinating science course and (from the
introduction to Chapter 3) my reasons for selecting this classroom for analysis:
In a conventional course, students typically
learn science as a body of knowledge
but not as a process of thinking, and rarely
do they have the opportunity to see how research science becomes textbook
science. A notable exception is a popular, innovative genetics course
taught at Monona Grove High School by Sue Johnson, who in 1990 was named
"Wisconsin Biology Teacher of the Year" by the National Association
of Biology Teachers, due in large part to her creative work in developing
and teaching this course. In her classroom, students experience a
wide range of problem-solving activities as they build and test scientific
theories and, when necessary, revise these theories. After students
have solved several problems that "follow the rules" of a basic
Mendelian theory of inheritance, they begin to encounter data (generated
by computer) that cannot be explained using their initial theory.
To solve this new type of problem the students, working in small "research
groups", must recognize the anomalies and revise their existing theory
in an effort to develop new theories that can be judged, on the basis of
the students' own evaluation criteria, to be capable of satisfactorily explaining
the anomalous data.
As these students generate and evaluate
theories, they are gaining first-hand experience
in the role of research scientists. They also gain second-hand
experience in the form of science history, by hearing or reading
stories about the adventures of research scientists zealously pursuing their
goal of advancing the frontiers of knowledge. A balanced combination
that skillfully blends both types of student experience can be used to more
effectively simulate the total experience of a scientist actively involved
in research. According to educators who have studied this classroom,
students often achieve a higher motivation level, improved problem-solving
skills, and an appreciation for science as an intellectual activity.
3.11: Selection of a Course
for Analysis
Why has this particular course been
selected for analysis? First, the course already has been studied
by a number of researchers, so in my analysis I can use the data they have
gathered and the reports they have written, and I can build on the insights
they have gained. Second, and more important, this course -- to a
greater degree than in most courses -- gives students an opportunity to
experience a wide range of the "methods of science."
Why might a wider range of experience
be educationally useful? To encourage a wider scope for education,
Perkins & Simmons (1988) describe a model of learning with four frames
of knowledge (italicized below), and recommend that instruction should include
all four frames. But most science classrooms focus on only two of
the frames -- content (theory-learning)
and, to a lesser extent, conventional problem solving
(theory-using) -- so most students learn little about knowledge and
skills in the epistemic and inquiry
frames, about modes of thinking that involve theory-evaluating and
theory-revising. The inquiry frame is the most frequently neglected,
partly because it is "the most ambitious and perhaps hardest to cultivate
through education." (Perkins & Simmons, 1988, p. 313)
But scientific inquiry is the main focus
of Sue Johnson's genetics course. Giving students an opportunity for
an exciting "science in action" experience is one of the main
course objectives, as described by the course developers: "A
good knowledge of science involves experiencing first-hand the production
and application of scientific knowledge. ... [In the MG classroom]
students work in research groups to tackle problems, build models to explain
phenomena, and defend and critique those models. ... The methods they
use are those of the research scientist." (Johnson & Stewart,
1990; pp. 298, 306)
Based on a preliminary review of the
literature describing it, this course seemed to give students significant
opportunities for in-depth experience in many of the methods of science.
Based on this expectation, I selected the MG course -- which encompasses
a wide range of scientific methods, with relatively few "blank spots"
where essential activities of science are missing -- because I thought it
would provide a good context for exploring and testing the analytical utility
of ISM. Compared with conventional instruction, there would be a wider-than-usual
range of instructional activities to be creatively analyzed within the framework
of ISM, so there would be more possibilities for the stimulation of productive
ideas about ISM and its potential applications for education.
Before describing the analysis (in
Chapter 3) I'll quickly outline the first two chapters:
Chapter 1 is an overview of the
dissertation, describing Objective 1 (developing
a model of Integrated Scientific Method) and Objective
2 (applying this model for the analysis of instruction). At
the beginning of Chapter 2, Section 2.00 explains the relationships
between Objectives 1 and 2.
The remainder of Chapter 2, which is
devoted to Objective 1 (developing ISM), has been summarized in this website:
Sections 2.01-2.07 (an overview of ISM) were revised to form the
SCIENCE-page; 2.11-2.73 describe ISM
in much greater detail, in more depth than on the large ISM-page,
and include some sections (such as certain aspects of "Thought Styles"
in 2.72) that are not in the ISM-page. The goals for ISM (and a discussion
of the extent to which I think these goals have been accomplished) are described
in 2.08-2.09 and 2.81-2.92, in more detail than on the GOALS-page, including subsections (such as 2.08-I, "Can
ISM cope with differences in terminology?") that
aren't on the GOALS-page.
Chapter 3 contains the educational
analysis. In the Table of Contents below, the sections are colorized
to show the main function of each section: to describe the
classroom and instruction, the methods used
for the analysis, and descriptions (based on my analysis) of the instruction and the structure
of instruction, and suggestions for improvement.
If you want to learn about the classroom and/or analysis, you can read the
appropriately colored sections in the word processing files.
In addition, Chapter 4 contains
some sections related to the analysis, and there is some interesting analytical
material in the appendix: examinations of Potential Problem-Solving Actions
(in B1) and Potential Problem-Solving Actions (in B2). { I also
describe the availability, within this website, of the first two parts of
the appendix, which are about "the nature of science" rather than
instructional analysis. }
CHAPTER 3: An Integrative Analysis of a Problem-Solving Classroom
3.11: Selection of a Course for Analysis
3.12: A Classroom
Context for Problem Solving
A. Effect-to-Cause
Problems
B. The
Classroom
3.2: Methods for the Analysis
3.21: Activities and Experiences in a Functional Analysis
3.22: An Overview of the Analysis
3.23: Major Instructional Activities
3.24: Creating
a Classroom Atmosphere
A. Students
as Scientists
B. Stories
about Science
C. Metacognitive
Reflection
D. Social-Intellectual
Interactions
3.25: Genetics
Problems in the Classroom
A. Genetics
Construction Kit (GCK)
B. A
Structured Representation of Mendel's Model
C. GCK
Problems that require Model Revising
3.26: Science Experiences
3.27: Three Stages of Analysis
3.28: Sources
of Information for the Analysis
A. Methods
for the Central Activity
B. Methods
for Other Activities
3.3: The First Phase of Analysis - Student Experiences in Each Activity
3.31: Activity
Group #1 - Black Box Model Revising
A: Developing
(building and revising) Models
B: A
Student Conference
C: Revising
Models
3.32: Activity-Group
#2 - Genetics Phenomena
A: The
Cookie Analogy
B: Human
Variations and Human Pedigrees
3.33: Activity
Group #3 - Initial Models
A: Developing
a Mendelian Model
B: Developing
a Model of Meiosis
C: GCK
Problems without Model Revising
3.34: Activity
Group #4 - Genetics Model Revising
A: GCK
Problems that require Model Revising
B: Student
Conferences
3.35: Activity
Group #5 - Manuscript Preparation
A: Manuscript
Writing and Manuscript Revising
3.4: The Second Phase of Analysis -- The Structure of Instruction
3.41: An Introduction to the Second Phase of Analysis
3.42. Preparation by Learning Procedures
3.43: Preparation
by Learning Concepts
A. Providing
Conceptual Knowledge for Model Revising
B. Simplifying
the Process of Analysis-and-Revision
C. Limiting
What Students Know About Genetics
3.44: Posing
Problems
A. Posing
is done by the Teacher
B. Posing
is done by Students
C. Do
Students Pose Problems?
3.45: Adjusting
the Level of Difficulty
A. Why
Adjustments are Important
B. When
to adjust? Before or During Problem Solving
C. The
Teacher as a Source of Procedural Knowledge
D. The
Teacher as a Source of Conceptual Knowledge
E. The
Teacher as an Adjuster of Problem Difficulty
F. The
Teacher as a Source of Emotional Support
3.46: Helping
Students Learn from Their Experience
A. The
Teacher as a Facilitator of Learning
B. Learning
by Metacognitive Reflection
C. Learning
from Other Students
3.47: Stories
about Science and Scientists
A. Stories
about Science: Strategies for Problem Solving
B. Stories
about Science: Having Fun as a Scientist
3.48: Functional
Relationships in the Instruction
A. Functional
Relationships Within Activities
B. Functional
Relationships Between Activities
3.5: Suggestions for Improving the Course
3.51: Suggestions by Others
3.52: My Suggestions
for Improvement
A. Supplementing
Incomplete or Inauthentic Science Experiences
B. Using
ISM in Discussions of Problem-Solving Strategies
C. Using
Prediction Overviews
3.6: Evaluating the ISM-Based Analysis
3.61: Understanding the Structure of Instruction
3.62: Testing
and Improving the Analytical Utility of ISM
A. Testing
ISM as a Tool for Instructional Analysis?
B. An
Improved Understanding of ISM-Based Analysis?
C. An
Improvement in ISM as a Tool for Analysis?
D. Using
ISM as part of an Eclectic Analytical Framework?
CHAPTER 4:
Potential Educational Applications
for a Model of "Integrated Scientific Method"
4.1: Using ISM for Instructional Design
4.11: Aesop's Activities
4.12: Analysis and Design
4.2: Using ISM in the Classroom
4.21: Learning from Experience
4.22: Coping with Complexity
4.23: Should Scientific Method be X-Rated?
4.3: Using ISM for Teacher Education
4.4: General Thinking Skills and a "Wide Spiral" Curriculum
4.41: A Model for an "Integrated Design Method"
4.42: A Wide Spiral Curriculum
4.43: In Praise of Variety in Education
4.5: An Overview of "ISM in Education"
Appendix
A1: A Brief History of ISM-Diagrams
(an expanded version of this is now available on the History
of ISM page)
A2: Controversies about Scientific Method
(a revised/condensed version of A21-A24 is available on the X-Rated page)
In addition, there is a new Tools for Analysis
page, containing Section A25:
A25: Tools for Analysis: Idealization and Range Diagrams
A. Analysis
by Idealization
B. Analysis
using Range Diagrams
And, related to the genetics classroom and its ISM-based analysis, B1 and B2:
B1: Prediction Overviews and Potential Problem-Solving Actions
B10: A New
Type of Representation: Prediction Overviews
A. A
System of Symbols
B. A
Prediction Overview for a Model of Dominance
C. Utility
- Scientific, Instructional, and Analytical
B11: A Model
for Round 1 -- Codominance
A. Anomaly
Recognition
B. A
General Problem-Solving Strategy
C. Anomaly
Resolution
D. Model
Revising
B12: A Model
for Round 2 -- Multiple Alleles
A. Anomaly
Recognition
B. Anomaly
Resolution
C. Model
Revising
D. Other
Sub-Patterns for the Pattern of Multiple Alleles
B13: A Model
for Round 3 -- X-linkage
A. Anomaly
Recognition
B. Anomaly
Resolution
C. Model
Revising
B14: A Model for Round 4 -- Autosomal linkage
B15: A Prediction Overview for "3 Alleles per Individual"
B16: A Comparison of Three Symbol-Systems
B2: Actual Problem-Solving Actions
B20: Four Sources of Empirical Data for the Analysis
B21: An Overview of the Analysis
B22: An
ISM-based Analysis of Problem-Solving Actions
A. An
Overview of the Problem-Solving Process
B. Anomaly
Recognition
C. Serendipity,
Surprise, Alertness, Statistics
D. Connecting
Anomaly Recognition with Anomaly Resolution
E. Anomaly
Resolution by a process of Invention-and-Evaluation
F. Memory
for Models
G. Conceptual
Constraints on Thinking
H. Three
Alleles Per Individual?
I. Protected
Components
J. Conceptual
Information from the Teacher
K. An
Example of Conceptual Assistance
L. Combining
Ideas in New Combinations
M. Key Factors
in Successful Model Revising
N. Using
Time: Observation and Interpretation
O. Theory
Evaluation: Balancing Empirical and Conceptual Factors
P. Denial
of Anomaly
Q. Evaluation
based on Thought Styles and Complexity
R. Combining
Perseverance and Flexibility
S. Observables
and Unobservables, Logic and Patience
T. Retroductive
Inference of Models and System-Theories
U. Descriptive
Theories and Explanatory Theories
V. Testing
Models: Experimenting and Evaluating
W. Goal-Oriented
Experimental Design
X. Trial-and-Error
with Fluent Speed
Y. A
Story of Goal -Oriented Wandering
Z. Competition
and Cooperation
SHOULD SCIENTIFIC METHOD BE X-RATED ?
ACTIVITY AND INQUIRY
{ this page isn't yet ready for
viewing, so there is no link to it}
http://www.sit.wisc.edu/~crusbult/methods/sue.htm
copyright 2000 by Craig Rusbult
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