Architecture For Inquiry
Jon Awbrey <[email protected]> Thu, 18 Dec 2003 09:56:09 -0500
| Newsgroups | gmane.comp.inquiry,gmane.comp.misc.ontology.general |
|---|---|
| Message-ID | <[email protected]> |
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<div class=Section1>
<p class=MsoTitle>An Architecture for Inquiry:<span style="mso-spacerun: yes">
</span><br>
Building Computer Platforms for Discovery</p>
<p class=Author>Susan M. Awbrey, Jon L. Awbrey*</p>
</div>
<b style='mso-bidi-font-weight:normal'><span style='font-size:12.0pt;
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</span></b>
<div class=Section2>
<p class=Heading>Abstract</p>
<p class=Text>More and more we hear the complaint that the gap between research
and instruction is widening and a vital sense of motivation is falling between
the cracks.<span style="mso-spacerun: yes"> </span>It is our vision that
intelligent computing systems will become a partner in the reintegration of
discovery and learning within the inquiry process.<span style="mso-spacerun:
yes"> </span>We will address certain issues that must be faced if computer
media are to have the characteristics necessary to support this
integration.<span style="mso-spacerun: yes"> </span>The development of the
computer to date has required a careful attention to the syntax and semantics
of the rather limited symbol systems we have induced them to use.<span
style="mso-spacerun: yes"> </span>A capacity for communicating in multiple
modalities with non-uniform communities of symbol users--for sharing in the
discovery of a pluralistic universe--will demand a quantum leap in our
understanding of the pragmatic dimensions of symbol use.<span
style="mso-spacerun: yes"> </span>In the future the capacity for inquiry must
permeate the living architecture of the computer system.<span
style="mso-spacerun: yes"> </span>A computer program that begins to embody
these ideas will be discussed.</p>
<p class=Heading>Introduction</p>
<p class=Text>Today, we are recognizing that students must become active
learners and problem-solvers to cope with the increasing complexity of their
current and future worlds.<span style="mso-spacerun: yes"> </span>At the same
time faculty are disheartened by the growing gap between their research and
instructional roles.<span style="mso-spacerun: yes"> </span>What is called for
is a reintegration of the discovery and learning processes to rekindle
essential motivation.<span style="mso-spacerun: yes"> </span>For the student
this implies the development of an inquiry approach to real world problems.<span
style="mso-spacerun: yes"> </span>For the instructor, it is the opportunity to
merge two currently disparate functions.<span style="mso-spacerun: yes">
</span>It is our thesis that computers, intelligent systems in particular, can
play a vital role in this reintegration.</p>
<p class=Heading>The Inquiry Process</p>
<p class=Text>Inquiry is focused exploration.<span style="mso-spacerun: yes">
</span>We may define it as the search for reasoned explanation or as an attempt
to find laws that govern and predict outcomes.<span style="mso-spacerun: yes">
</span>According to philosopher Charles Sanders Peirce (ref 1), inquiry is a
process involving three forms of reasoning.<span style="mso-spacerun: yes">
</span>First, a phenomenon catches our attention.<span style="mso-spacerun:
yes"> </span>It may surprise or annoy us but it does not fit with our
expectations.<span style="mso-spacerun: yes"> </span>We guess at principles
that might explain it.</p>
<p class=Text>*Susan M. Awbrey, Assistant Professor, Director of Learning
Resource Center; Jon L. Awbrey, Faculty Associate: Computer Specialist, School
of Nursing, University of Texas Medical Branch, Route J-30, Galveston, Texas,
USA, 77550</p>
<p class=Text>Peirce refers to this process of positing a possible explanation
as abductive reasoning.<span style="mso-spacerun: yes"> </span>We can also
term it hypothesis generation.<span style="mso-spacerun: yes"> </span>Next,
the results and consequences of the proposed explanation are considered.<span
style="mso-spacerun: yes"> </span>This is the process of deductive
reasoning.<span style="mso-spacerun: yes"> </span>Finally, actual consequences
are compared to those projected.<span style="mso-spacerun: yes"> </span>It is
inductive reasoning that determines their fit.</p>
<p class=Text>The information that anyone (interpreter) has about a phenomenon
(object system) is expressed in symbols (signs).<span style="mso-spacerun:
yes"> </span>This relationship Peirce referred to as the sign relation.<span
style="mso-spacerun: yes"> </span>For purposes of our discussion, there are
two important aspects of this relation.<span style="mso-spacerun: yes">
</span>First, the roles within it may change.<span style="mso-spacerun: yes">
</span>For example, a person may act as an interpreter or he may be a sign to
someone else, as when he smiles or frowns.<span style="mso-spacerun: yes">
</span>Secondly, it points out the importance of the interpreter to any
discovery since abductive reasoning is done by the interpreter and, therefore,
the initial hypothesis generation is subject to all of the constraints placed
on it by the interpreters knowledge base and assumptions.</p>
<p class=Heading>Architecture for Discovery</p>
<p class=Text>How then can computers assist with learning about and performing
this process of inquiry?<span style="mso-spacerun: yes"> </span>What
advantages do they offer us?</p>
<p class=Text>As noted earlier, the problems facing us today in all facets of
life from socioeconomics to ecology are characterized by complexity.<span
style="mso-spacerun: yes"> </span>Computers provide a way of handling data
about complex phenomena.<span style="mso-spacerun: yes"> </span>For some time
computers have been used to store and retrieve large databases of
information.<span style="mso-spacerun: yes"> </span>Models of quantitative
data have also been developed to make predictions about complex systems.<span
style="mso-spacerun: yes"> </span>However, the difficult task of developing
computer programs that can facilitate inquiry has not yet been fully
addressed.<span style="mso-spacerun: yes"> </span>When developed, computer
systems that facilitate inquiry can become a valuable resource for both forming
deductions from complex theories and for handling qualitative and sequential
data from complex phenomena.</p>
<p class=Text>A computer program capable of forming logical models based on its
environment could provide the following advantages to the faculty
researcher.<span style="mso-spacerun: yes"> </span>First, by modeling the
knowledge base of the researcher it would (1) make the researchers expressed
knowledge base visible and (2) identify implicit knowledge that the researcher
has and is using but which has not been incorporated into the proposed
theory.<span style="mso-spacerun: yes"> </span>Secondly, such a program might
assist in hypothesis generation by identifying constraints and assumptions the
researcher brings to the problem.</p>
<p class=Text style='mso-pagination:widow-orphan lines-together'>This
intelligent computer program could assist the faculty member as an instructor
by making the student's knowledge base related to a specific inquiry
visible.<span style="mso-spacerun: yes"> </span>It could provide an
environment for the students to perform inquiry based on the real world data
gathered by the faculty researcher using the program.<span style="mso-spacerun:
yes"> </span>It would be possible to begin with the faculty performing the
abductive process and pointing out a phenomenon of interest which the student
would then pursue through the deductive and inductive stages.<span
style="mso-spacerun: yes"> </span>Later, the student might perform all stages
of the inquiry process.</p>
<p class=Heading>Modeling the Inquiry Process</p>
<p class=Text>The following diagram presents a dynamic model of the inquiry
process.</p>
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<p class=Text><b style='mso-bidi-font-weight:normal'>Figure 1:<span
style="mso-spacerun: yes"> </span>Dynamics of Inquiry<o:p></o:p></b></p>
<p class=Text>When a phenomenon presents itself, our task is to explain
it.<span style="mso-spacerun: yes"> </span>We observe the features of the
phenomenon (1) and make a guess about its explanation (abduction). We form a
theory which we<span style="mso-spacerun: yes"> </span>represent in terms of
observed features and events. This expressed theory (2), is comprised of
the<span style="mso-spacerun: yes"> </span>laws and principles believed to govern
the phenomenon. Using this theory we can deduce the possible consequences and
outcomes it would predict (deduction) and formulate a model of it (3).<span
style="mso-spacerun: yes"> </span>We can then compare the model with the
properties of the original phenomenon, some of which may need to be elicited by
further experiment (induction).<span style="mso-spacerun: yes"> </span>When a
theory is expressed, the investigator may not have included all of the
necessary underlying knowledge in the expressed theory. By representing the
theory computationally, this missing implicit knowledge (4) often comes to
light and assists in clarifying the theory (explication).</p>
<p class=Heading>A Beginning:<span style="mso-spacerun: yes"> </span><i
style='mso-bidi-font-style:normal'>Theme I</i></p>
<p class=Text style='mso-pagination:widow-orphan lines-together'>Developing a
computer program for inquiry that recognizes events, forms models of its
environment, and formulates rules based on experience means careful attention
to the fundamentals of the symbol systems used.<span style="mso-spacerun:
yes"> </span>The authors have developed a prototype, PC-based program designed
to integrate inductive and deductive reasoning.<span style="mso-spacerun:
yes"> </span><i style='mso-bidi-font-style:normal'>Theme I</i> is comprised of
two components, called <i style='mso-bidi-font-style:normal'>Index</i> and <i
style='mso-bidi-font-style:normal'>Study</i>.<span style="mso-spacerun: yes">
</span><i style='mso-bidi-font-style:normal'>Index</i> is a learning algorithm
for sequential data.<span style="mso-spacerun: yes"> </span>It acquires a
two-level formal language that describes the qualitative features of a given
domain.<span style="mso-spacerun: yes"> </span><i style='mso-bidi-font-style:
normal'>Study</i> builds logical models of this domain using propositional
calculus.<span style="mso-spacerun: yes"> </span><i style='mso-bidi-font-style:
normal'>Theme I</i> has been applied to studies on family interaction, and a
study involving its use in clinical reasoning is in process.</p>
<p class=Heading>Conclusion</p>
<p class=Text>The development of a computer program for inquiry that uses
artificial intelligence is underway.<span style="mso-spacerun: yes">
</span>The ultimate goal of the project is development of an interactive tool
for research that assists students and investigators in inquiries involving
qualitative data.<span style="mso-spacerun: yes"> </span>In the future such
programs could provide an environment for students to participate in and become
proficient at abductive, deductive, and inductive reasoning.<span
style="mso-spacerun: yes"> </span>It is hoped that development of a computer
architecture for inquiry will assist in the reintegration of discovery and
learning and restore the vitality of exploration to the educational process.</p>
<p class=Heading>References</p>
<p class=Ref>1.<span style='mso-tab-count:1'> </span>C S<span
style="mso-spacerun: yes"> </span>Peirce, Collected Papers of Charles Sanders
Peirce (Harvard University Press, Cambridge, MA, 1931-1960).</p>
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