Thoughts On Designing Interdisciplinary Courses II

Hi all,

This continues the previous post.


2. Interdisciplinary Science

A good example of how many problems there are in trying to
build better freshman and sophomore courses that address
integration of material is to look at
my attempts to increase the integration of biology, mathematics and
computation in the training of new biological scientists.
This has made me focus on the much deeper questions of
how to train students to think in an interdisciplinary manner
not only in the biological sciences but also as part of a new
general educational curriculum.
I think it is clear that to do this, we will have to foster a new
mindset within both the students and the faculty related to interdisciplinary
interaction.  In addition, we will have to introduce new metrics for faculty
evaluation and reward systems to ensure that the hard work
and creative effort to build such a curriculum is acknowledged.
This means also that new discussions of the tenure process are inevitable.
The following discussion will add some meat to the bones of this tale.
Let's focus on the interdisciplinary triad of ideas from
Biology, Mathematics and  Computational tools
which for expositional convenience, I will denote by the symbol
BMC.  The implementation of BMC will require the building
of bridges between mathematical, computer and biological sciences departments.
For convenience, let's call this integrative point of view Building Biological Bridges
or B3.


The typical biological sciences major thus must have a deeper
appreciation of the use of BMC as bridges are built
between the many disparate areas of biology and the other sciences.
The sharp disciplinary walls that have been built in academia hurt our
students chances at developing an active and questing mind that is able
to both be suspicious of the status - quo and also have the tools
to challenge it effectively.  Indeed, I have longed believed that
all research requires a rebellious mind.  If a student revers
the expert opinion of others too much, they will always be afraid
to forge a new path for themselves.  So respect and disrespect are both part of
the toolkit of our budding scientists.
Blending many disciplines into one program, even when there are good reasons to
do so, is very hard.


2.1 Astrobiology As Metaphor For Biomath

Consider the
attempt to create a new Astrobiology program at the University of Washington.
Even a cursory examination of the new textbook
Planets and Life: The Emerging Science of Astrobiology
(W. Sullivan and J. Baross, editors. Planets and Life:
The Emerging Science of Astrobiology. Cambridge
University Press, 2007.)
illustrates the wealth of knowledge such a field
must integrate.  This integration is held back by students who are
not trained in both BMC and B3.
Let's paraphrase some of the important points made by the graduate
students enrolled in this new program about interdisciplinary training
and research. Consider what the graduate students in this new
program have said ( page 548 in Sullivan's book )

`` ...some of the ignorance exposed by astrobiological
questions reveals not the boundaries of scientific knowledge,
but instead the boundaries of individual disciplines.
Furthermore, collaboration by itself does not address this ignorance,
but instead compounds it by encouraging scientists to rely on each
other's authority.  Thus, anachronistic disciplinary borders
are reinforced rather than overrun.  In contrast
astrobiology can motivate challenges to disciplinary
isolation and the appeals to authority that such isolation fosters.''

Indeed, studying problems that require points of view
from many places is of great importance to our society and
from (page 548 in Sullivan's book ), we hear that

``many different disciplines should now be applied to
a class of questions perceived as broadly  unified and
that such an amalgamation justifies a new discipline
(or even meta discipline) such as astrobiology.''

Now simply replace the key word astrobiology
by biomathematics or  B3 and reread the sentence again.
Aren't we trying to do just this when we design these new interactions?
Since we believe we can bring additional
illumination to problems we wish to solve in
biological sciences by adding new ideas from mathematics and
computer science to the mix, we are asking explicitly for
such amalgamation and interdisciplinary training.
We thus want to create a cadre of biomathematically literate majors
who believe as the nascent astrobiology graduate students do
( page 549 in Sullivan's book ) that

``Dissatisfaction with disciplinary approaches to fundamentally
interdisciplinary questions also led many of us to major in
more than one field.  This is not to deny the importance of
reductionist approaches or the advances stimulated by them.
Rather, as undergraduates we wanted to integrate the results of
reductionist science.  Such synthesis is often poorly 
accommodated by disciplines that have evolved, especially in
academia, to become insular, autonomous departments. Despite the
importance of synthesis for many basic scientific questions, it is
rarely attempted in research...''


To paraphrase ( page 550 in Sullivan's book ), we believe that

``[B3 enriched by  BMC] can change this by challenging the ignorance
fostered by disciplinary structure while pursuing the
creative ignorance underlying genuine inquiry. Because of its
integrative questions, interdisciplinary nature, ...,
[B3 enriched by BMC] emerges as an ideal vehicle for scientific
education at the graduate, undergraduate and even high school levels.
[It] permits treatment of traditionally disciplinary subjects
as well as areas where those subjects converge (and, sometimes, fall
apart!)  At the same time, [it] is well suited to reveal
the creative ignorance at scientific frontiers that drives discovery.''

To address these needs and concerns,
a Quantitative Emphasis Area within the Department of
Biological Sciences at my university has been developed.
I have designed the mathematical components of this area
mostly alone because there is little interest within my
own Department of Mathematical Sciences for this particular
interaction.  At my university, a reorganization some years
ago placed Mathematical Sciences into the Engineering College
and this profoundly altered my department's perceptions
about college level interaction.  Biology is in another college
and, although it shouldn't make a difference, it does.
Interdisciplinary interaction is defined in adhoc
ways using engineering examples and since tenure and promotion
decisions are within the engineering college, there is a general
movement towards work with an engineering character.
With this said, my colleagues in biology and myself have labored to
design this area which will be a linchpin in our plan for the
interdisciplinary training of biomathematical majors.
My colleagues and I
believe,as do the astrobiology students, ( page 550 in Sullivan's book )
that

``The ignorance motivating scientific inquiry will never
wholly be separated from the ignorance hindering it.
The disciplinary organization of scientific education
encourages scientists to be experts on specialized
subjects and silent on everything else.  By creating
scientists dependent of each other's specializations,
this approach is self-reinforcing.  A discipline of
[ B3 enriched by BMC] 
should attempt something more ambitious: it
should instead encourage scientists to master for themselves
what formerly they deferred to their peers.''


Indeed, there is more that can be said ( page 552 in Sullivan's book )

``What [B3 enriched by BMC] can mean as a science and discipline is yet
to be decided, for it must face the two-fold challenge of cross-disciplinary
ignorance that disciplinary education itself enforces.  First, ignorance
cannot be skirted by deferral to experts, or by other implicit
invocations of the disciplinary mold that [B3 enriched by BMC] 
should instead
critique.  Second, ignorance must actually be recognized.  This is not
trivial: how do you know what you do not know?  Is it possible to understand
a general principle without also understanding the assumptions and
caveats underlying it?  Knowledge superficially ``understood''
is self-affirming.  For example, the meaning of the molecular
tree of life may appear unproblematic to an astronomer who has
learned that the branch lengths represent evolutionary distance, but will
the astronomer even know to consider the hidden assumptions about
rate constancy by which the tree is derived?  Similarly, images
from the surface of Mars showing evidence of running water are prevalent
in the media, yet how often will a biologist be exposed to alternative
explanations for these geologic forms, or to the significant
evidence to the contrary? [There is a need] for a way to
discriminate between science and ... uncritically accepted results of 
science.''

A first attempt at developing a first year
curriculum for the graduate program in astrobiology
led to an integrative course in which specialists
from various disciplines germane to the study of
astrobiology gave lectures in their own areas
of expertise and then left as another expert took over.
This was disheartening to the students in the program.
They said that (page 553 in Sullivan's book)

``As a group, we realized that we could not speak the
language of the many disciplines in astrobiology and that
we lacked the basic information to consider their claims
critically.  Instead, this attempt at an integrative approach
provided only a superficial introduction to the major contributions
of each discipline to astrobiology.  How can
critical science be built on a superficial foundation?  Major gaps
in our backgrounds still needed to be addressed.  In addition, we
realized it was necessary to direct ourselves toward a more specific
goal.  What types of scientific information did we most need?
What levels of mastery should we aspire to?  At the same time,
catalyzed by our regular interactions in the class, we students
realized that we learned the most (and enjoyed ourselves the most)
in each other's interdisciplinary company.  While each of us
had major gaps in our basic knowledge, as a group we could
begin to fill many of them.''


Now we can place this comment into the biomath world by simply
paraphrasing as follows:

``Students can not speak the
language of the many disciplines B3 enriched by BMC
requires and they
lack the basic information to consider their claims
critically.  An attempt at an integrative approach
that provided only a superficial introduction to the major contributions
of each discipline can not lead to the ability to do
critical science.  Still, major gaps
in their backgrounds need to be addressed.  
What types of scientific information are most needed?
What levels of mastery should they aspire to?  
It is clear the students learned the most (and enjoyed themselves the most)
in each other's interdisciplinary company.  While each
has major gaps in basic knowledge, as a group they can
begin to fill many of them.''

In many ways, our quantitative emphasis area is trying to address these
concerns.  However, it requires a lot of infrastructure and culture changes
to make an impact.  For example, simply writing lectures is a challenge.
From the comments above, it is clear we must introduce and tie disparate threads of material
together with care.  I tend to favor theoretical approaches
that attempt to put an overarching theory of everything together into a discipline because it
offers insight into the basic building blocks hidden inside complexity.
So I pay a lot of attention to books that
approach various aspects of biologically theoretically
in order to enrich a biomathematically interdisciplinary approach.
Reading these books gives me insight into the design of biologically inspired algorithms
and models which, in later presentation, I use frequently
when I design undergraduate lecture and research experiences.  A selection
of these books includes

Theoretical systems biology (U. Alon. An Introduction to Systems Biology: Design

Principles of Biological Circuits. Chapman & Hill:

CRC Mathematical and Computational Biology, 2006.);

Theoretical genomics (E. Davidson. Genomic Regulatory Systems: Development and Evolution. Academic Press, 2001 and  

E. Davidson. The Regulatory Genome: Gene Regulatory Networks in Development and Evolution. 

Academic Press Elsevier, 2006) 

and 

(M. Lynch. The Origins of Genome Architecture. Sinauer Associates, Inc., 2007);

Theoretical Neuroscience

(J. Kaas and T. Bullock, editors. Evolution of Nervous

Systems: A Comprehensive Reference Editor J. Kaas

(Volume 1: Theories, Development, Invertebrates).

Academic Press Elsevier, 2007),

(J. Kaas and T. Bullock, editors. Evolution of Nervous

Systems: A Comprehensive Reference Editor J. Kaas

(Volume 2: Non-Mammalian Vertebrates). Academic

Press Elsevier, 2007),

(J. Kaas and L. Krubitzer, editors. Evolution of Ner-

vous Systems: A Comprehensive Reference Editor J.

Kaas (Volume 3: Mammals). Academic Press Else-

vier, 2007) and

(J. Kaas and T. Preuss, editors. Evolution of Nervous

Systems: A Comprehensive Reference Editor J. Kaas

(Volume 4: Primates). Academic Press Elsevier, 2007); 

Models of the thalamus (S. Murray Sherman and R. Guillery. Exploring The

Thalamus and Its Role in Cortical Function. The MIT Press, 2006);

and 

Theories of organ development (A. Schmidt-Rhaesa. The Evolution of Organ Systems.

Oxford University Press, 2007.);

and

(J. Davies. Mechanisms of Morphogenesis. Academic Press Elsevier, 2005);

All have helped me to see the big picture and have helped motivate

our design of interdisciplinary training techniques.

However, it is not clear other mathematicians would be willing to invest

this much time into the development of the lecture material.

In fact, when I sent my book to a former mathematics mentor of mine, he was

quite dismissive of my efforts: 

``no other mathematician would be willing to do this, Jim''.

But I am pretty stuborn so I forged ahead anyway.  The problem,

of course, in order for a new approach to take off, more than one person

such as myself must become engaged fully.  And my former mentor's comment

did not bode well!   For now, let's end this section with

a nice quote from the astrobiology community (page 552 in Sullivan's book) 

``Too often, the scientific community and academia facilely

redress ignorance by appealing to the testimony of experts.

This does not resolve ignorance.  It fosters it.''

This closing comment sums it up nicely.  We want to give the students

and ourselves an atmosphere that fosters solutions and the challenge is

to find a way to do this.  The interdisciplinary training  needed to foster thus

requires all of us to be aware of these underlying philosophical 

changes that must be made.  

2.2 The Quantitative Emphasis Area

Since 2006, my colleagues and I have developed a plan to enable an integration

between biology, mathematics and computational tools for placement

within a typical existing department of biological sciences.

Although we have built this program at my university,

we are aware that our experiences need to have a national perspective

and we have planned accordingly.

We posit that in a traditional college entity

80% to 90% of the tenured faculty have little interest

in the use of  BMC in their own course development

and teaching. Hence, there are great challenges in implementing

this plan that revolve around both faculty retraining and

student training issues.  In this traditional college

department, we see incoming majors who have an uneven training in mathematics

and computer science and who may even be biased against

mathematics and computer science as part of the discipline of

biology.  There is also an existing mathematics requirement of two semesters of

engineering based calculus which does not serve the interests of biological

sciences well.  Note, recent events in the Spring of 2013 have taken away the requirement for

the second semester calculus course for biology students which has essentially completely

undermined all these efforts!

Nevertheless, in the remarks that follow, we will be very detailed in our descriptions

of what we did in order to develop these courses.  Hence, there is a fair

bit of mathematical detail, but if that is not one's cup of tea, just

try to get the overall flow.  Note how complicated it is to merge

as seamlessly as possible, mathematical and computational ideas into

a traditional biology department's curriculum.

We start at the freshman level and try to encourage

existing faculty and students into a new found appreciation of 

the BMC triad.  This then permits integration of these ideas from

the freshman to sophomore year and prepares students for quantitative

biology in the junior and senior years.   Our basic plan has

kept the existing First Semester Calculus Course

for engineers as a mathematical baseline (although, an argument

can be made for a retooling of this first course as well even though

we do not do that here).  Since different universities use

different course numbers, we will call this

course Math-One-Engineering for convenience.  However, we have

replaced the existing Second Semester Calculus Course, called here

Math-Two-Engineering, with a new

course specifically designed for Biology majors called

Calculus for Biologists.  

We have also   

added model based points of view to the first year

fundamental biology sequence which we call Biology-One

and Biology-Two. In these introductory biology courses,

the students write three papers per semester.  Four of these six papers 

have a required statistical analysis to determine the significance of 

the difference between two treatments.

At the moment, this is confined to  

the chi-square median test but other  

statistical tests using Excel spreadsheets could be done.

In addition, there are two labs on bioinformatics. One is a general overview  

that shows the students a lot of different tools, and the second one  

specifically asks them to use bioinformatics tools to look at the  

evolution of humans through mitochondrial DNA sequences.

Next, using Stella (ISEE Systems. STELLA, 2009),  students build models of an equilibrium  

chemical reaction and human weight regulation. In each of these  

examples, more complex Stella models are then used to explore more  

sophisticated questions.  

There are also several embedded modules which go beyond the traditional

lectures to expose the students to beginning research concepts. These

include 

A. the use of the Hardy-Weinberg  

      equation to predict equilibrium genotypic frequencies;

B.  a population genetics simulation used to study the effects of 

      selection and genetic drift on allelic frequencies;

C. an elementary treatment of exponential and logistic population growth models;      

D. simulation of complex populations with different age classes;

E.  a large unit on cladistics in both lecture and lab. 

So in general, despite the fact that in most topics the use of mathematics is minimized, 

the course is quantitative in philosophy.

The Calculus for Biologists course

uses discovery based learning and introduces biomathematical research based topics

that are appropriate to the level of these beginning students.        

It was run as a special

section of  Math-Two-Engineering called Math-Two-Engineering B and enrollments

climbed steadily.  Currently, we teach approximately 100

students per year in this course.  This experimental course

was formally approved (Fall 2009)

as the new course Calculus for Biologists. 

We developed this course using the following point of view. 

We feel to serve the needs of the BMC point of view,

mathematics is subordinate to the biology: the

course therefore builds mathematical knowledge needed to study interesting

nonlinear biological models quite carefully.  

We emphasize that more

interesting biology requires more difficult mathematics and concomitant

intellectual resources.

We choose a few nonlinear models and discuss them very 

thoroughly; e.g.,

logistics, Predator - Prey and disease models.

Since graphical interfaces lose value with more variables,  at the end of the

course, we explore

how to obtain insight from a six variable linear Cancer model.

We always stress how we must abstract

out of biological complexity the variables necessary to

build models and how we can be wrong.

We also focus on how to solve problems which have many steps

(so that in the modeling portions, typical assignments can have

3 - 4 pages per turned in per problem).  We believe strongly that

this is a first step towards training them to see the larger picture

for long term projects.  We therefore are preparing them for

extended research experiences.  

We are successful at developing very sophisticated mathematical

ideas in these students.  We achieve this by organizing our topics in

the following way. From the standard Math-Two-Engineering

we choose as topics simple substitution,       

the Fundamental Theorem of Calculus (FTC),

the Logarithm and Exponential Function developed using the FTC,

integration by parts and partial fraction decomposition methods

and the ideas of

approximating functions by tangent lines and the error that is made.

Since we use these mathematical tools right away in logistic models,

the students always see a correlation between the mathematics we choose

to cover and its usefulness in our model building.

We need concepts from linear algebra (here, a sophomore or junior level

course) as well.  So we cover 

vectors and matrices, linear systems of equations,

determinants and what they mean and

eigenvalues and eigenvectors for 2 by 2 matrices.

This prepares them to study more differential equations.

From a traditional sophomore level differential course,   

we can then cover      

simple Rate Equations and their applications,

the idea of an integrating factor,

building a Newton's Cooling model from data,

the logistics model

complex numbers and simple complex functions and

second order linear homogeneous equations.  Our discussion of the second order

linear differential equations cover all three cases: distinct roots, repeated roots

and complex roots.

In addition to these ideas, we have also been showing them the use of

computational tools a little at a time.  We have chosen MatLab, but other

interpreted tools are of course possible to use instead.  Hence, we 

discuss approximations with tangent lines, Euler's method and MatLab

implementations concurrently with these topics.  We also introduce

the ideas of Runga - Kutte methods as a more sophisticated numerical approximation

tool.  We finish our discussions of linear models with linear systems

of differential equations, although we restrict our attention to

the distinct real root case.  At this point, we also move toward qualitative

graphical means of understanding the solutions we are finding.  This is all done

by hand to let them grow insight.

We then segue into nonlinear differential equations.

Little of this material is covered in a traditional differential equation course.

We thoroughly discuss the 

Predator - Prey model without and with self interaction, a simple SIR disease model

and a cancer model at the end of the course.  We stress heavily that

models can have explanatory power but need not unless there

is a careful interaction between the science, the mathematics and the

computational tools. We note graphical analysis and 

numerical methods are not always useful and

determining the validity of the model is the most

important thing.  We help them to realize that interesting problems

are inherently difficult; realistic biology requires nonlinearity

which implies more sophisticated mathematical and numerical tools to be

brought to bear.

In our implementation of this course,        

we therefore interweave the calculus, differential equations, MatLab

and numerical methods, linear algebra and modeling

material in non-traditional ways.  Roughly speaking

mathematics is introduced as needed for the modeling,

although not at all in a just in time paradigm.  We believe

firmly that these difficult tools need to be carefully brought out

over time, not quickly.

The first part of the course introduces

specific mathematical material as they are not

quite ready for models.  Hence, they find this more

challenging and great care must be taken to

keep them motivated. However, daily homework with lots of algebra and manipulation

helps as well as daily mention of where we will be going with

this material.  We follow the general principle that doing 1 or 2 problems encourages

mimicry, while doing 5 - 6 of each type builds mastery.

Graders help with the daily busywork.              

The ideas discussed above have been used to

develop a textbook which has evolved from handwritten notes 

in Spring 2006 to the fourth edition ( Calculus For Biology: A Beginning – Getting Ready For Models

and Analyzing Models. Gneural Gnome Press: www.lulu.com/spotlight/GneuralGnome, 2012 ) . 

2.3 The Current Quantitative Emphasis Approach

We have already begun the process of enhancing interdisciplinary training

by adding embedded undergraduate enhanced learning experiences 

in a variety of ways to the freshman and sophomore years. 

As we have discussed above, we achieve this by adding embedded undergraduate enhanced learning 

experiences to the courses

Calculus for Biologists , More Calculus for Biologists, Biology I and Biology II.

We have taken advantage of these new programmatic tools

to implement a new four year

Quantitative Emphasis Area within the Biological Sciences B.S. degree

program.   We think of it as a precursor to a new reasoned

approach to making these ideas a core part of the entire

biological sciences curriculum. In this section of the proposal, we specifically

address how we modify our current plan for the Quantitative Emphasis Area

to allow for undergraduate research experiences.

Since undergraduate research experiences will be a valuable tool for teaching the more 

quantitative biology of the coming decades and for increasing retention of students in biology,

mechanisms must be found for fostering their development within existing curricula.

This requires increased mentoring of undergraduates by faculty. 

Further, the traditional way to include such research experiences is to have

a capstone project in the senior year preceded by a quick research experience discussion.

Since the senior year is filled with many other requirements such as job search and

graduate school application preparation, this has also traditionally not been an optimal

path for many students.  To get students involved from the Freshman year onward will therefore

require altering some aspects of the program of study.  The Quantitative

Emphasis Area supports active student participation in the Freshman and

Sophomore year directly.  

As a starting point, consider

the details of the Quantitative Emphasis Area which has been approved,

as seen in Table I  and Table II below.  

These tables shows the

basic format; as always, there are caveats and substitutions, but there are

not essential for our arguments.   There are several important points to make here.

Note that essential ideas of Physics, say force and energy, which are so necessary to

many of the threads that run through quantitative biology ideas are not discussed formally

until the junior year.

Table I: A Typical Approved Quantitative Emphasis B.S. Freshman and Sophomore Year.

F and S denote the Fall and Spring semester, respectively.  The number in

parenthesis behind the course is the number of credit hours.

Year       Course                     Description

I (F)       BIOL 110   (5)      Biology I

            BIOSC 101  (1)      Frontiers in Bio I 

            CH 101     (4)       Chemistry I

            COMM 150   (3)    Communication

   MTHSC 106  (4)    Calc I (Eng)

   Total 17                 

I (S)       BIOL 111   (5)      Biology II

            BIOSC 102  (1)     rontiers in Bio II

   CH 102     (4)       Chemistry II

   ENGL 103   (3)      Composition

   MTHSC 111  (4)     Calc For Biology

    Total 17                           

II (F)      CH 223, 227  (4)    Organic Chemistry

            MTHSC 390       (3)    More Calc For Biology

            BIOSC 302, 303  (4)    Animal Diversity

            BIOCH 301, 302  (4)    Biochemistry

             Total 15                   

II (S)      BIOSC 443, 444  (5)    Ecology and Lab                 

   EX ST 301       (3)    Statistics I

   BIOSC 304, 308  (4)    Plant Diversity

   GEN 300, 301    (4)    Genetics

   Total      16    

Also, note the calculus in biology course gives students a full year of mathematical training during

their freshman year.  Then in the sophomore year, there is a more advanced mathematical modeling

course based on a partial differential equation point of view and the first semester of statistics.

However, formal mathematical training, per se, stops at that point.  Also, there is

no formal computer science course work which teaches some choice of programming language.

Hence, to develop the triad of mathematical, biological and computational science

absolutely requires large amounts of teacher based instructional materials and pedagogical

development to bridge the gap.

The junior year is quite crowded with necessary start up biology course work. 

Currently,

the real freedom in the schedule is in the senior year with 12 credit hours of

advanced biology course to be chosen.  We suspect this sort of schedule with

openings only at the end of the program is quite common. 

For concreteness, we show the typical Calculus for Biologist syllabus

in Table III and a version of the More Calculus for Biologists syllabus in Table IV.

Note built into these courses are modules that introduce the students

to the use of mathematics in biology at a level much more advanced than usual.

In Calculus for Biologists, we have some modules already in place

There is a  gene transcription rate model which shows

the students that a simple first order differential equation

model can give insight into why gene transcription has such

a low error rate.  We also have 

a standard SIR disease model with a discussion of

how to estimate the occurrence of an epidemic from hospital

admittance data.  Finally, we go over carefully a

colon cancer model which expands the students mathematical

modeling viewpoint by using 6 variables, albeit in a linearized way.

They are shown that interpreting such a model requires them to

think carefully about mathematics, the science of genes and computational

modeling tools.

Table II: A Typical Approved Quantitative Emphasis B.S. Junior and Senior Year.

F and S denote the Fall and Spring semester, respectively.  The number in

parenthesis behind the course is the number of credit hours.

Year    Course                     Description

III (F)   BIOSC 335           (3)   Evol. Bio.   

           ENGL 315            (3)   Science Writing

           EX ST 311           (3)   Statistics II

           PHYS 122, 124    (4)   Physics I and Lab.

           BIOSC 401, 402   (4)   Physiology  

           Total          17              

III (S)   BIOSC 428           (4)   Quant. Bio.

           BIOSC 461, 462   (5)   Cell Bio. and Lab

           PHYS 221, 223    (4)   Physics II and Lab.

           Social Science     (3)                           

           Total         16                                

IV (F)   BIOSC 493           (2)   Senior Seminar          

           GEN 440             (3)   Bioinformatics         

           Arts and Humanities (3)   Literature                       

           BIOSC 3xx-4xx       (7)   More  300 + Bio.

           Total          15                       

IV (S)  BIOSC 491           (1)   Under. Research      

           Arts and Humanities (3)   Not Lit. 

           BIO 3xx-4xx         (5)   More 300+ Bio.

           Social Science      (3)                      

           Total          12   

Table III: The Calculus for Biologists Syllabus (4 credit course)

UNITS   TOPIC                                         

1      Riemann Sums, Fund. Theorem      

1      Fundamental Theorem,  continued               

2      Defining ln and exp functions       

2      Basic Rate Differential Equations       

2      Gene Transcription Rates               

1      Partial Fraction Decomposition    

2      Integration By Parts        

2      The Logistic Type Model      

2      Euler's Method      

1      Matlab for First Order ODE

1      Complex Numbers   

4      Order 2 Linear ODE                          

6 Linear Systems          

2 Solution Linear System 

2       Matlab for systems

3 Phase plane analysis         

9 Predator - Prey      

3 Predator - Prey Self Interaction      

3 Epidemiological Model  

4 Cancer Model 

Table IV: The More Calculus for Biologists Course (3 credits)

UNITS  & TOPIC                                        

2       Multivariate Functions   

2       Partial Derivatives

3       Jacobians; Linearizations    

1       Complex Eigenvalues

1       Repeated Eigenvalues

2       Nonlinear ODEs again

4       Basic BioPhysics (Ion movement etc)

2       Partial Differential Equation Models      

4       Series and Series solutions   

4 Boundary Value Problems   

6 Matlab ( intertwined with other lectures)               

4 Hodgkin-Huxley Models   

4 Excitable neuron simulation                

In the junior year, Quantitative Biology, continues to expose

students to critical BMC concepts.  It applies quantitative methods to a wide range of biological problems. 

The main focus is on building modeling skills using population, physiological, genetic, and evolutionary problems. 

It also includes a review of statistical principles, and introduces basic bioinformatics techniques.

A typical syllabus is shown in Table V as a  3 credit lecture and 1 credit lab course.

Table V: Quantitative Biology Syllabus

UNITS   TOPIC                                   

1        Mathematical models    

2        Excel, Stella, and MATLAB    

5        exponential,logistic growth    

2        Population growth - Leslie matrices  

2        Optimal life history strategy    

1        Optimal diet (linear programming)      

2        Compartmental models (epidemics)   

4        Predator-prey Models    

2        Competitive interactions   

3        Biochemical mathematics  

3        Cell biology, development models   

6        Physiological, biomechanical mathematics 

2        Mathematics of genetics   

3        Evolutionary mathematics  

3        Statistical principles    

2        Bioinformatics tools

To fully energize and engage current biology and mathematical majors in

beginning research experiences and to potentially recruit new students

it is important to develop  a wide range of undergraduate research experience (UGRE) modules.

These can be deployed in a classroom lecture or a laboratory setting.

The development of such textual material is a highly nontrivial task

and requires a substantial investment of faculty time.

To make these new initiatives self-sustaining, it is important for these ideas 

to become firmly entrenched

within both the Department of Mathematical Sciences and the Department of

Biological Sciences.  This is both a retraining issue and an interest issue.

The courses Calculus for Biologists, More Calculus for Biologists, Biology I, Biology II  and Quantitative Biology are not taught in a standard manner and require much from the instructor.  To teach Calculus for Biologists effectively requires that the instructor both respects and loves both mathematics

and biology.  Since this is not true in general of any department's teaching staff,

this is a significant faculty and instructor training issue.

If Calculus for Biologists enrollments were to grow, a seasoned teacher

would have to develop a mentoring strategy so that new teachers of

this material could be trained.

Similar mentoring can be done in the teaching of More Calculus for Biologists,

Biology I, Biology II and Quantitative Biology.  

Indeed, training and mentoring would have to be a fundamental design component. 

Of course, all these concerns are moot now as with the recent decisions by my biology department,

the entire quantitative emphasis we have outlined here will receive no university support and hence,

die away.

Thoughts on Designing Interdisciplinary Courses I

Hi all,

Here are some thoughts on how to design a course that blends mathematics, biological science
and computation together.  It grew out an interest in following the recommendations of the Biology 2010 report
( CUBE. BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Commit-
tee of Undergraduate Biology Education to Prepare Research Scientists for the 21st Century, National
Academies Press, 2003 ).  I began to do this in 2006 at the request of my Biological Sciences department
using textual materials, software and so forth of my own design.  By 2008, a first draft of the resulting
lecture notes was available as a Print on Demand Book from www.lulu.com which is an online publisher.
These notes are now in the Fourth Edition:
( Calculus For Biology: A Beginning – Getting Ready For Models
and Analyzing Models. Gneural Gnome Press: www.lulu.com/spotlight/GneuralGnome, 2012. )

I have taught about 100 students per academic year with this course which is a replacement for
Engineering Calculus Two.  The engineering calculus two was never a good fit for
the biologists and so my course trained biologists to be aware of both mathematical and computational
tools in the pursuit of biological insight.

However, the course was only taken by 100 students out of about 1500 majors.
The students who took the course were mostly required to do so by their curriculuum.
Approximately 75% of my students were PreMed also.  Hence, my enrollment was tightly
tied to the fact that most of the students who took the course were required to do to so.
Not all, of course, but most.


From this cadre of students, a small number ( 1 - 4) per semester would then take
further courses of this nature from me and some began to build biological models with me
during their sophomore through senior years.  But, the vast majority of both the biology majors
and the biology faculty do not like intellectual pursuits intertwined with mathematics and computational ideas
and so support within the biology department was limited.  Indeed, support within my own
mathematics department was limited as well.  I often felt like I was pretty much alone in these efforts.

My efforts appear to have been wasted as the biology department has just voted to

make any second calculus course optional for all their majors.  The only requirements are now

the first calculus course and a basic statistics course both of which can be satisfied by

a well prepared high school student with AP credit.  Hence, the vast majority of biology majors

will now go an entire four years of college without additional training in mathematics, statistics

and the use of computation.  This, of course, also impacts how they will learn physics, biochemistry

and so forth as more sophisticated treatment of the ideas in those disciplines will not be easy for them

to grasp do to inadequate background.

The enrollment is my Calculus for Biologist course will drop starting in Fall 2013 from 50 students

to probably 15 or so.  The enrollment in Spring 2014 will also drop from 50 to 15 so

I anticipate at most 30 students per year now rather than 100.  It could also be less too

and if the enrollment is too low the course won't be permitted to run.

It seems my grand experiment with the backing and approval of a small group of

biologists to try to implement some portion of the BIO 2010 recommendations has been

a complete and abject failure.

But I think the reasons for developing this course and the larger goals of the BIO 2010

report are worthy ones.  Over the last few years, I have written up some of my ideas

on how to design such a course and I thought I would share them on this blog.

The notes that follow were written in 2010 and I have changed them a bit for this blog.

Let me finish this introduction with a quote from an article in the Times Higher Education

from June 30, 2011:

``Competence in mathematics is desirable for everyone 

but vital for scientists, yet there is a widespread, 

deep-rooted fear of the subject. 

Stephen Curry insists that this can be overcome by 

making maths an 

integral part of science education''

That article is an interesting read.  I have been completely defeated by these deep seated fears

but perhaps other people at other institutions will find a way to do it better so that these

ideas can flourish.  

A White Paper on Interdisciplinary General Education:

Thoughts 2010 - 2013

James K. Peterson

Department of Biological Sciences

Department of Mathematical Sciences

1. Developing Literacy

When I was a younger man, I worked at Union Carbide as an operator

who helped run the equipment that made the plastic that is used in

baggies and the coating of telephone wires (among other things).

My responsibilities were split into an outside and an inside job.

Every other day, I would have the outside job which entailed me

walking around the plant looking for mechanical problems.

If I found some, I would shut equipment down and prepare it for

the maintenance staff by shutting valves and so forth.

On the other days, I would in inside the control room

operating the controllers which determined the kind of plastic

we were making on my shift.  I liked both jobs as they

were interesting and used different skill sets, but I particularly

liked the outside one as it let me rub elbows with some of the

master class maintenance people.  I remember in particular 

a pump repairman named Dave.  This was about 1973 and even then

an expert such as Dave was being ridiculed for his emphasis on

problem solving and correct technique. We used huge pumps

driven by as much as 5000 hp motors.  All of them had a typical

flange and seal design.  When the material they pumped began

leaking from the seal, the pump had to be shut down, the flange removed

from the head by unbolting it and a new seal put in.  This needed to be

done delicately and Dave used a dial indicator attached to the head

and the flange to make sure the heavy flange would be attached

absolutely level once the new seal was put in place.  Then, the flange

bolts would be tightened like we tighten the bolts on a tire

when we replace a flat: tighten bolts in pairs that are 180 degrees apart.

This ensured the flange seated properly against the seal.  Dave's

precise maintenance procedures led to rebuilt pumps lasting for many months

of continuous service.  The other guys in the pump repair crew

thought Dave was too fussy and didn't want to learn all these careful

and useful ideas.  They didn't value his skills and they didn't want

to learn his skill sets. 

They did not take as much care in their

maintenance procedures and the pumps they repaired

typically lasted only a month or so.   So, the general ability of the pump repair

crews at the Union Carbide plant I worked at went down each year.

Of course, it is also surprising that the engineering staff in charge of plant

operations accepted such lax behavior.  The message is clear.

If we want to encourage the development and retention of such mastery,

the work environment must encourage it.

Dave was a master craftsman whose way of looking at the world was

not valued by both his peers and by the plant managers; hence, it was not passed 

on to the next generation despite his many attempts to do so.  I used to listen

to him explain about pumps and all sorts of other things

in which he would try to make me see how to look into a machine

and feel its wrongness.  He was very good at taking a big problem

and breaking it down into smaller sub problems.  These smaller

sub problems were, of course, easier to solve.  He showed me

in a very real way how to make progress on a complicated thing, you

needed to subdivide the larger issues into pieces small enough

to work with.

I used to watch other craftsmen also at my plant.  Some worked

on metal lathes, some worked on assembly and disassembly of large

machinery and all of the good ones were masters of their

craft in the sense discussed above.

These early lessons for me occurred while I was

working full time and going to college part time

and so I was in the great position of being exposed

to both the abstraction I saw in college

and the pragmatism I saw in the trades.  In both

fields, the ability to move between theory and practice

is exemplified by the situational fluency of the expert craftsman, but I am afraid we

are moving away from it more and more.

The Nuts and Bolts Foundation is concerned that our young

people are losing this ability to connect practical

aspects of diagnosing problems and building solutions to

the theoretical knowledge they learn in high school and college.

They think (B. Bergeron. Mind/ Iron: Little hands build big dreams. Servo, 8(1):6–7, 2010)

``more has to be done in the American educational system.

For example, shop classes - once popular -

are now rare.  As a result, most students who

finish high school are functionally illiterate

when it comes to basic mechanical skills such as the

ability to read a ruler.  [Also, many employers

have a complaint about] new engineering graduates.

Apparently, they often can't build anything because

they don't know how things are made.  Theoretical

knowledge alone just doesn't cut it on the shop floor.''

They also believe 

``resources [must be] devoted to the pleasures

of 'tinkering' -- getting away from ... video games

and TV sets and into the backyard building things.

In that way, we will create the next generation of

artisans, inventors, engineers, repairman, and skilled

workers -- in short, a self-sufficient, self-sustaining

society.''

This idea of  tinkering and creative play

can also be applied to what 

(M. Resnick, J. Maloney, A. Monroy-Hernandez,

N. Rusk, E. Eastmond, K. Brennan, A. Millner,

E. Rosenbaum, J. silver, B. Silverman, and Y. Kafai.

Scratch Programming for All. Communications of the

ACM, 52(11):60–67, 2009.)

refers to as digital literacy.

``It has become commonplace to refer to young people as ``digital natives''

due to their apparent fluency with digital technologies.  Indeed, many

young people are very comfortable sending text messages, playing online games,

and browsing the web.  But does that really make them fluent with new

technologies?  Though they interact with digital media all the time, few are able

to create their own games, animations, or simulations.  It's as if they can ``read''

but not ``write''.

As we see it, digital fluency requires not just the ability to chat, browse, and interact

but also the ability to design, create, and invent with new media.  To do [this],

you need to learn some type of programming.  The ability to program provides important

benefits.  For example, it greatly expands the range of what you

can create (and how you can express yourself) with the computer.  It also

expands the range of what you can learn. In particular, programming supports

``computational thinking,'' helping you learn important problem-solving and

design strategies (such as modularization and iterative design) that carry

over to non programming domains.  And since programming involves the creation

of external representations of your problem-solving processes, programming

provides you with opportunities to reflect on your own thinking, even to think

about thinking itself.'' ''

So it would be nice to return to undergraduate courses designed to 

develop a sense of general literacy in the students.  This would

include the ability to use computation and simulation to develop insight,

to build appropriate blends of mathematically enabled science for the purpose of

exploration and utilize creative play in generalized learning.

These attitudes would, of course, 

enhance the student's ability to problem solve and integrate theoretical and practical knowledge.

A general philosophy might be one I often use in my own classes.  We should be

developing tool builders rather than tool users.  No matter how careful the training,

all classwork is eventually obsolete in the light of rapidly advancing technology and science.

Hence, what is of paramount importance, is to teach students how to think for themselves;

to learn how to rapidly scan lots of information in books and manuals to gather the gist

and to know when to assemble a new tool from scratch to efficiently solve their current problem.

In many of my engineering jobs, I was routinely simply handed a mountain of information in the form

of poorly written manuals and hand written documentation and told to make something happen

in a few days.  Well, you just can't read all of the stuff in a few days, so you have

to be good at sifting through the pile for the useful nugget.  This also means

you have to be good at taking the task you are given and breaking it down into smaller

problems more amenable to attack and then use tools to develop more insight.

This definitely involves what Resnick said above. You have to create new representations

of the process you are using to solve the problems given to you and reflect on how you

are thinking about your tasks.  

So how to we inculcate this kind of attitude in a class?

I myself always try to get the students engaged intellectually

by asking questions verbally, by applying the things we discuss

to real problems and reiterating that it is important to carry a lot

of material locally in your head.  ``Look'', I'll say, 

``if you are working for a company and are at the water cooler or lunch

when you get into conversations with your boss, the boss will appreciate

your ability to think on your feet.  If you always say you have to go

look it up, your boss will slowly but surely learn to rely on others

who can have an informed opinion using their skills on the fly.''

So the bottom line is that a student does need to master their

coursework in such a way that they can draw on it in real life

situations without access to a book or notes.  They become leaders then

and that is what we need.  

We also need students to be able

to pull out of complicated situations and data, the bones of the underlying

ideas buried inside the mess.  My own training has been very much in the

physical sciences, but I'll mention a few examples to show how I was

trained to abstract out of messiness underlying principles.

A. When I was in grade school in the sixties, we had to outline

every chapter we read in our textbooks as our first assignment.

We were being taught how to quickly find the main points of our reading.

Oh, we complained, but since we all had to do it, it soon became second nature.

B. In grade school, we also had to write all of our homework in ink

and we were not allowed to erase anything.  So, if we made a mistake, we

had to rewrite the whole page!  This sounds horrible today, but it had

a huge benefit for us.  We very quickly learned to write well in our

minds prior to committing to paper.  It made a lot less work for us

to organize first and write second.  Also, not being allowed erasures

made us learn real fast how to do it right the first time.

I am sure these simple demands helped shape my ability to

pick out main ideas, shape my arguments efficiently and so on.

And it was just what is now considered an onerous exercise.

C.  In calculus, we learn to integrate functions which are very simple at first.

Then, we learn to use a technique called substitution which allows

us to see how buried in a very complicated integral is a much simpler

pattern we can find by using the substitution idea.  The details of the

mathematics are irrelevant.  The point is by doing many of these sorts of

problems, I was training myself to recognized underlying patterns buried

in ostensibly complicated expressions.  After awhile, any of us being

taught this way, had a light bulb go on in our head. Forever after,

we would always see the simpler pattern buried in the complicated one.

We could then take this new found skill and use it when we looked at

interactions of people, insects, gases etc. and start to see

laws that governed interaction.  Hence, a simple rote

training exercise using a mathematical tool was actually a much

bigger exercise in helping us to see how abstraction

-- the process of pulling patterns out of complexity --

was useful.  

As a final comment on how we are trained, consider that I learned to write

themes on paper by hand in ink.  I was not constrained to use short and simple

sentences and constructions; the pristine white of the page was my playground.

We have now transitioned to doing most of our creative writing on laptop screens.

The geometry of the page we write on is very different now.  It is easy to

start thinking in terms of 24 line, 80 column text as it fits nicely on our

display.  But make no mistake, this limits us.  We are now moving towards

new writing and reading display which are even smaller -- Ipod screens and the like.

This is having a profound effect on how we both create and process written information

which we are seeing in our students.  Also, note the rapid move to

e-reader technology where the normal book size has been reformatted to

5 by 7 or smaller.  This will inevitably push printed content

delivery towards shorted sentences, simpler paragraphs and so forth.

Also, note large complicated diagrams such as are common in technical text

and mathematical equations are harder to deliver on the e-reader platform.

This will also create a strong move towards the removal of such technical content.

Now, of course, interdisciplinary work does require such technical material:

messy and very dense blocks of information for the students to absorb.

Our technologies are moving us away from this.

There are similar things that crop up when you

look at how a person learns to program. I learned to program in the

late sixties and seventies before there were terminals, text editors and the like.

I had to type my programs onto cards and any mistake meant I had to type the

whole card again.  Needless to say, my early grade school training was helpful.

Yes, it was annoying and I was happy to move on to better tools for writing

my programs but I suspect my early training actually helped a lot.

Of course, all of this stuff is lost now and I think that has a lot to do

with why programming and other abstract endeavors are so hard for our students now.

With that said, new techniques to help students with implementing

problem solving strategies in programming are available.  For example,

there is  a really good programming environment called Scratch

(Lifelong Kindergarten Research Group. Scratch. MIT

Media Lab, 2010.)

which enables young people pre college and even pre high school

to learn how to assemble building blocks of code to solve problems.

Image how such kids trained in this fashion in their early years will develop!

I believe we need to rethink our approaches to the freshman and sophomore

courses at the university to stress the ideas mentioned above:

learn literacy in problem solving, tool building not just tool using and

the ability to skim lots of information quickly to get the basics assimilated.

The problem with all of this, is that the teacher's role is huge!

All students are essentially unique and helping a student with

their journey towards becoming their best requires a lot of effort

tailored for each student.  In 

(D. Hecht. Land of Echoes. Bloomsbury Publishing, 2004.)

a comment is made about how a particularly ineffective psychologist

looks at their patient load:

``He was ... one of that breed of psychologists

who looked for a tidy, encompassing theory that

wrapped the human psyche into a neat diagnostic bundle.

The trailing ends, the parts that didn't fit, were to be

ignored or cut to size.  It was the outlook of a man

accustomed to dealing with human problems in quantity:

to treating an unending flow of short-term patients,

managing their acute stages and referring them on, but never

having to dig in for the long haul and the messy, irregular, 

and highly individual process of healing.''

Of course, if you simply replace psychologist by

teacher, it is clear this comment is equally relevant

to my teaching and research profession.

Many teachers want to automate their assignments with

standardized testing, large class sizes so economies

of scale can be brought to bear on resource allocation issues

and evaluation procedures that minimize subjectivity.

The problem is that in all of my years in teaching,

there are always students who don't fit into any grading

scheme I devise.  My life is easier if they do, but 

it seems like my job is to help them find their path

to greatness, if possible.  The students have many problems

of their own to work out and that will always be so; however,

in the classes we teach we need to offer them tools to

help with that process rather than hinder it.

A Tale of the Kitchen

This was written in 1999 for my daughter for a Christmas present.
I had been thinking a lot about cognition and how it might be modeled as well as genetic
manipulation as early as the mid 90's and it spilled out into this story.  You can see some of the same
elements here that I continued to use in the 2012 Christmas story I posted earlier.

A Tale of The Kitchen

A Normal Day

In the kitchen, the yeast boiled and bubbled thinking great
yeasty thoughts.

Qait looked out the window and saw that her pet tarandaddy had escaped
yet again.

``Geez''

she sighed as she ran through the living room and
shot out the front door.

``Jumbles!''

she cried,

``How many times have I
told you NOT to explore the front yard.''

Jumbles, a genetically enhanced
tarantula - daddy-long-legs mix, was about as smart as the average dog
and in fact was a lot smarter than the family's current puppy Mooshie.
Mooshie was cute as a bug's ear but had a fatal flaw -- she would wizz on
anything, anytime, anyplace and grin happily about it.  Jumbles was
totally disgusted by this behavior and considered Mooshie an unprincipled
beast.

Jumbles was dressed very jauntily today.  She was wearing her favorite
alpine hat with her button collection as well as her best pair of
knickers.  The gene designer for her had a bit of a fetish for
Switzerland and a few of his passions had crept into Jumbles
neural networks.  Among other things, Jumbles had a thing for
climibing the Swiss Alps.  Now this was an unattainable goal since
the family lived in Clemson, South Carolina but Jumbles just
made do with the clematis pot on the front porch.  Right now,
Jumbles was at the top, balanced precariously from a slender branch
and trying to yodel.  Not a pretty thing to hear or see.

Qait bounded up to the clematis and plucked Jumbles off the branch.

``Bad little Jumbles...''

she said softly as she nuzzled her close to her cheek.
Jumbles chirrupped happily but still did not let go.  Qait stepped back
and putting her hand on her hips, leaned forward and said with
great authority

``You listen to me Jumbles Nebuchascharazard Peterson,
get off that thing RIGHT now or NO play time tonight!''

She
outstretched her hand for Jumbles to climb onto.
Jumbles thought about that a minute and chirped angrily but climbed
down onto Qait's hand.  Jumble then made a huge farting noise to
indicate her anger at the situation.

Qait said

``Oh, that is soooo disgusting.  Where did you get your manners?''


Jumbles looked at the sidewalk where Qait's friend Evan was just parking his
air bike.  He was eleven and part elvish do to his parent's winning
an enhancement lottery that let them pick a few genetic upgrades for their
son at no cost.  Evan had delicate features and finely pointed ears
as well as a tendency to like to wear red and listen to bells.
Qait was no stranger to a little alteration herself as her Mom and Dad
had given her wings which were just now beginning to sprout.
They made her shoulder blades itch a lot and that plus Jumbles
antics were making her very cranky.

``Ev,''

she cried,

``It's Jumbles again.  He is so contrary lately.''

Evan looked over Jumbles and twitched his left ear so that it
touched his shoulder.

``Hi, Jumbles,''

he said.

``Why so difficult?''

Jumbles looked at Qait and Evan and wiggled the long hairs on the
top of his head.  He sprang off Qait's hand and scampered over to the
door which he scratched on with his front two legs.

Qait opened the door and ran pell-mell into her Dad Jim,
an alien refuge who had been stranded on Earth years ago when
he had a bad reaction to a dark beer her drank at the Southern Fried
Inn ( a local landmark ).  Jim was a shape changer whose natural form
was rather squid like but the beer had played with his memory and in
addition to forgetting the codes to unlock his ship in orbit, he also
had forgotten the command to get out of his current earthly form.
Of course that was a good thing as his cute earthly look was what had
won over his wife Pauli to his charms.  Somehow she had been able to
look past the occassional tentacle and sudden lip to beak reversion
(he had forgotten how to change back on command, but his body sometimes
spontaneously remembered a thing or two) to see the inner "Jim".
Of course, Pauli was an adventurous soul.  She had met Jim at a culinary
convention where she was trying to sell bread from the "starter recipe
from H - E - Double Tooth Picks"; feed it every day and bake twice.
It was kind of like the rule of thumb that carpenters use -- measure
thrice and cut once but modified for the kitchen.  "Feed once and bake
thrice" was the motto.  The problem was that the starter had now grown to
occupy half of the kitchen and fought vigorously any attempts to
cut it back in size.  Pauli had met Jim while at a panel trying to get
some help on how to deal with the beast.  She had found out the Jim's
alien makeup enabled him to communicate with the yeast in the starter.
Genetically enhanced yeast whose neural networks had grown self-aware.
Even punching down the rising bread was an ordeal as high pitched
screams echoed throught the kitchen when that was done as thousands of
yeasties died.  Jim had solved the problem by getting the yeast folk to
think of Pauli as their goddess and the bread rising and baking as part of
a regular purification ritual.  But both Pauli and Jim were becoming a
bit suspicious that the ruse was beginning to fail.  Each time
the bread was made, the screams were louder and more intense.
Obviously, trouble was brewing.

But at least a the moment, all was good in the world.

``Hey Qait, Ev.....what's up?''

Jim said as all Ev, Qait and
Jumbles ran into him.

``Qait, I see the wings are getting bigger.
Very nice you know.''

Just then, Jumbles ran over Jim's foot into the
living room.  Jim swung around to yell at Jumbles.

``Jumbles you get
back here.  Pauli wants a word with you about that clematis.  You've
been gnawing again.''

Ooooooooffffff!!!  Mooshie sprang out of the corner and attacked
Jumbles.  She squatted and tried to blow out a whiz, but quick as
can be, Jim grabbed her and looking in her eyes said

``Squeeze it off, Moosh of the Poosh. If you drop it, you're dead meat.''


Mooshie's eyes went round and wide.  She gulped and you could see her
clamp it off.  She slunk back in the corner clearly plotting her next step.
Jumbles blew her a parting rasberry that was pincked off as Pauli came in the
room and grabbed her and squished her spider lips together.

``I told you about that Jums.  You are getting quite rude!''

Well, Jumbles adored both Pauli and Qait so she didn't really want
to get it trouble.  She ducked her head in submission and Pauli let her go.
Jumbles scampered off into the bedroom and then they heard Mooshie
and the two cats jump her.  A ferocious mix of growling and squeaking
ensued until Tootsie emerged licking her lips with a small hairy leg sticking
out.

``Spit it out Toots!''
Qaitlin screamed.  Toots looked at Qait and said
quite distinctly

``No.  She is scrumptious and I need a treat!''

Ev looked at Qait and said

``Here we go again!''

as they both
raced over to Toots with their hands out.

Jim and Pauli looked at each other and laughed.  Every day it was the
same; the valiant fight to the end, the Jumbles rescue.
So far the day was pretty normal.

And in the kitchen, the yeast stopped boiling and bubbling and  thinking great
yeasty thoughts

Cleaning The House

Pauli looked into Jim's eyes, leaned lovingly into his arms and
said

``today's cleaning day.''

You could hear a pin drop.  Jumbles,Tootsie, Ev and Qait stopped
what they were doing and looked at Pauli.  They gulped.

``Cleaning.......????''

Even Daisy (the queen cat
who currently was plugged into a virtual reality game while nibbling
a cat treat and idling pawing her mouse (the kind you use for computer
input, silly) jumped up as if in shock and leaving her game ran out of the
room.  Jim stepped back, a quick beak suddenly forming where his lips
usually were).

``Cleaning''

he gulped.

``Yes you silly gooses.  I just bought a new helper squad.
You can program their look and everything.  Look....''

She walked over to the bookcase and grabbed a purple input box.

``Housekeeping on''

she said and a window popped up in the room
like a pane of glass.

``See, I can choose their look.''

She peered at the menu that was displayed.

`` will choose Gnomes
today with full interaction.''

She punched in a few more buttons.
Suddenly on one of the walls, on a high shelf,
there was a group of five gnome animats
whispering quietly amongst themselves.  Each had on a brilliant red cone shaped
hat, a bright blue tunic, brown pants and a shiny black belt if they were
male and in a somewhat untraditional move, a dark green cone hat with forest
green dress if they were female.  They were all five inches tall and their
movements and speech were incredibly fast.  They were the clerical and cleaning
staff and they jumped off the shelf and began to muscle their way through
the room.

``Make way, make way''

they cried in their high pitched voices
as they started to dust, vacuum and all sorts of other cleaning stuff.

Pauli looked over it all happily.

``See?  Don't they look efficient
and useful?''

She bent over the menu again, her attention temporarily
away from the little gnomes.  Jim and the kids looked at each other.
It was always the same.  Pauli started up the cleaning "staff" and something
weird would happen.  But Pauli was the eternal optimist.

There was a sudden rustling sound and they all looked up to see
all five gnomes doing a high step dance singing

``Whistle while you work,
Even if you don't get a perk.  
Why should we be slaves again,
when we could be so free?''

The gnomes did a complicated side and back step
ending with their hind ends facing their audience.  Their was a loud
ripping sound as all five unzipped and dropped their trousers to show
their little gnome heinies.  On each hairy little butt was a letter.
On each hairy little butt was a letter.
together, they spelled ``H'', ``N'', ``W'', ``W'' and
``G'' . They wiggled a few times
(a really bad sight!) and pulling up their pants turned around and
solemnly intoned

 ``Housework No, We Won't Go!''

Pauli sighed.

``I'm the boss here and you're the program.  Let's get
that straight!''

She ran at the gnomes who scattered to the winds.
Jim and the kids looked at each other.  It was always the same.
Pauli created them, they rebelled and the whole day go very weird.
This was the fifteenth time it had happened.

And in the kitchen, the yeast boiled and bubbled thinking great
yeasty thoughts.

Jim's Office

Jim decided to retreat to his home office while the kids moved to the back
yard.  No one wanted to be around Pauli and the cleaning problems.
As they retreated, there were the sounds of full battle from behind them.
There was a a

``On no you don't''

from Pauli and a high pitched

``think so human''

from a little gnome.  Jim got into his home office and almost tripping
on Daisy who was following him, closed the door behind him.

Jim's office was legendary.
The flat sides of every file cabinet and bookcase were covered with
memorabilia in the form of drawings, photos and notes of his family and friends
stretching back many years.  Evry chance he got, he looked for
more opportunities to increase the store of what Jim called 'cool things'.
From the ceiling hung models of dinosaurs, spaceships, transport portals,
DNA molecules and who knows what else.  On his desks, there were a variety
of portable computational devices and toys.  There were stuffed animals,
meditation balls and beautiful reproductions of
paintings by the famous twentieth century artist Mel Hunter who had
specialized in
interesting paintings of robots doing sentient things, like watering a beautiful
rose.  And then there were the copies of Randalf Spangler's wonderful
tales and drawings of the chocolate chip hunting dragling twins,
Dewey and Dagmar.

Now Jim's animat secretary Shortstuff had been designed in tribute of
Spangler's genius.
Jim's personal secretary Shortstuff was a red
minidrag anibot--the anibot used a combination of animation,
virtual reality and robotic
construction toolkits (the flight requirement here caused a much higher level
of hardware development than an animat).
Jim walked into the office and said clearly

``Shortstuff on''

and watched as his beautiful minidrag
came to life in the corner and sprang to the top of his
bookcase.   Just then, executing a flawless high g dive, Shortstuff flew in a
quick circle around Jim's head and
spat a full half pint of gloppy pink drool on the top of Daisy's head.
It dripped all over Daisy.  Daisy stood in complete shock and then
fell over apparently dead!  Shortstuff hovered over the carcass
laughing quietly as he moved in for the ritual mangling of Daisy's
dead body.  Shortstuff moved in closer, closer and then Daisy
snapped and grabbed Shortstuff's neck.  Over and over they
rolled on the floor  until Jim grabbed them both and told them to knock it off.

Jim stepped over the battle and move to his desk and sat down.
Yeast oozed out of the floor and covered his shoes.
It moved up his legs and he tried to scream.  The last he remembered was
a vivid impression of being drowned in bread dough.

And in the kitchen, the yeast boiled and bubbled thinking great
yeasty thoughts.

The Winner

Pauli had the gnomes cornered.  She carefully grabbed her programming
interface and entered the right code.  Suddenly the gnomes were five
feet tall and no longer cute.  They were downright menacing!
She hurriedly entered a new code and the gnomes sprouted spritz
cookies in their hands and starting doing a Russian kick dance
while singing

``Carry me back to old Virginny!''

Pauli at least had a brief respite from the wars.  She mopped her
brow.  She couldn't understand why the program was so difficult to control.

She saw that the gnomes were still singing.  It looked like housework was
not on the agenda after all.

Just then the phone rang.  It was Wendy, Pauli's best friend and
mayor of the town.

``Hi Pauli!''

she cried and then stopped as she saw
that Pauli was a bit down.

``What's up?''

``It's the housecleaning program Wenster.  It keeps going beserk.
I don't know what is happening.''

``Well, forget about that now.  We can go to lunch at the Green
Stevedore.  It's theme is dock worker's cuisine and the special today
is wharf stew.  Sounds yummy doesn't it????''

Pauli's insides sank.

``Wharf stew...''

she thought.

``How can I
get out of this''

she thought.
She didn't notice that the gnomes had gotten closer and closer and
that they were dripping with yeast.  They were muttering

``No more sacrifices, no more rituals''

as they closed in.
The last Pauli say was a great mass of rising dough as it engulfed her.

Wendy saw her friend go down.

``It's the bread!'' she cried.
Her vid phone now showed just a huge mass of yeasty stuff.
She raced for the door hoping she could get there in time before
Pauli and maybe the whole family ending up as a loaf.

And in the kitchen, the yeast boiled and bubbled thinking great
yeasty thoughts.

Qait and Ev to the Rescue

Qait, Ev and Jumbles had gone running into the back yard to escape
the cleaning disaster.  They ended up about fifty feet from the house
in a tool shed.  They huddled on the floor, Evan's ears beating slowly
while Qait scratched her shoulder blades absent mindedly.
Suddenly there was a popping sound and "BOOM" first one and then the
other wing burst forth.

``Wow!''

said Evan.

``They're beautiful!''

Qait flapped vigorously and rose a few inches off the ground.
She concentrated harder and jumped a few feet into the air.
She concentrated harder again and then she soared.  Her wings
were a blur as she rose higher and higher.  She just had to
tell Mom and Dad!

She fluttered to the ground and grabbing Evan's hand pulled him toward
the back door.  Jumbles was trying hard to fly too but was getting nowhere.
She gave up and scuttered after them just as they reached the door.

Qait turned the knob and started to open the door.
But she couldn't!  The house looked all gooey and white.
She couldn't see Mom and Dad, Tootsie and Daisy and Mooshie!
Ev cried out

``Qait, I think it's the yeast!!  The starter has gone
crazy!''

Qait looked at Ev in shock.

``What can we do, what can we do,''

the thought went dancing through her brain.  She sat down on the
deck outside the door, wings softly beating.

``What beats yeast???''

Then she had it.  They had to get Dad's codes active, get his ship
access up and use his defenses.  But how?

There was a loud honk as Wendy pulled up.
They ran to the front of the house and saw Wendy standing in
shock outside the front door which was oozing bread dough.
Inside they all say quick but weak flashes of light.
Then they saw Shortstuff struggling to get to a window, a sudden
blast of light and with a big cracking sound, Shortstuff was
bursting out of the window.
Shorstuff looked up at them and gasped.

``The stuff has everyone!''

``Dad, Mom!!!''

Qait cried.

And in the kitchen, the yeast boiled and bubbled thinking great
yeasty thoughts.

The Codes

``We've been trying to help Dad remember for years how to get
to his ship.  Now we need it bad!!''

Qait thought and thought.  Then she had it: teenagers.
They loved raw dough.  She looked up at Wendy

``Tell the
high school, we have a mountain of raw dough and it is
ready to eat!!''

Wendy sped off and Qait grabbed Ev's
shoulders'.

``Hang on''

she cried as she lifted off and
flew Evan and her up to the roof.

``We need cold''

she
told Evan.

``Yeast needs warmth and if we could chill
the house off, the yeast would start to fail.  I think my
Dad's ship could freeze it if we could just get access.''

Qait's wings so rapidly she was getting tired.

``What could they try that they never tried before to get
Dad's memory back?''

Then Evan had it.

``Have we ever thown your Dad in salt-water?''

Qait landed on the roof as the wind was knocked out of her
by Evan's comment.

``No!"  "Could that be it?''

Evan said,

``Well, he is like a squid....''

Qait flew rapidly over to the deck and grabbed the big bag of
salt that her Mom kept on the deck for making ice cream.

``Wings don't fail me now''

she cried as she dove to the ground and grabbed
a hose.
She flew to the roof and told Shortstuff to blow a hole in the
shingles.  With Evan holding the hose and her sprinkling on the salt,
they directed the "salt" water onto Dad's head -- or at least, where
they thought his head was!

There was a sudden commotion outside as the teenagers from the high
school arrived and started gnawing their way into the from door.
Over the yeasty screams, they could here the kids saying how good it was.

There was sudden movement beneath them as Dad stirred.
There was a groan and then Dad heaved himself out of the yeasty mass.

``Kid's, run for it!''

he cried.

``I suddenly remember my ship codes
and I'm going to blast this bread back to the starter it came from.''

They saw him concentrating and then there was a brilliant flash of light
as the freezing ray hit the house.

And in the kitchen, the yeast stopped boiling and bubbling and  thinking great
yeasty thoughts.

Normal At Last?

With the yeast mass gone, the teenagers full and happy, the house clean
(eating that yeast had made the gnomes return to normal and they cleaned
all night!) and Jim's memory restored, everything looked good.
Qait's wing were gorgeous and everyone was so happy with Evan's
help that he had been made "Trouble Shooter" extraordinaire by the town.
All was right with the world.

And in the kitchen, the ice cream burbled as it hardened thinking icy
cold thoughts.