RICHARD GOLDEN HOME PAGE
Text Comprehension and Memory Research
When a reader reads a text, an "understanding" of the text is
created in the reader's mind. It is convenient to introduce the
technical term "situation model" in order to refer to
this understanding of a text which is created in the mind of a reader.
The process of constructing a situation model is called the
"comprehension process", while operations such as "text recall",
"text summarization", and "text question-answering" generate
scientifically observable events as a by-product of the interactions
of the situation model and other knowledge structures in the
Dr. Golden is currently developing a statistical model which
allows the user to incorporate prior knowledge about the semantic
and syntactic relationships among the elements in a text. This statistical
model is called
Knowledge Digraph Contribution (KDC) Analysis.
The parameters of the
model can be estimated from human recall, summarization, and question-answering
data. Each parameter may be interpreted as the relative strength of a different
knowledge schema. The
parameters of the KDC model are uniquely determined and the large
sample probability distribution of the estimates of the parameters can
be derived for large sample sizes. These mathematical results are relevant
for deriving customized statistical tests for testing hypotheses about the
relevance of specific knowledge schema weighting parameters. Statistical
tests for deciding which of several text knowledge schemata "best-fits"
a given set of recall data have also been developed. More recently, methods
of sampling from the KDC probability model have been derived which allow one
to generate synthetic recall protocols and then compare these synthesized recall
protocols with actual human recall protocols for the purpose of evaluating the
validity of the user-specified "knowledge analyses" of the text.
Dr. Golden and his graduate students are also working on the
AUTOCODER project which
is a software tool that facilitates the coding of recall,
summarization, talk-aloud, and question-answering protocol data.
In collaborating with Dr. Susan Goldman, Dr. Golden and his
graduate students recently completed a feasibility study
ARCADE (Automated Reading Comprehension and Diagnostic Evaluation)
which was supported by the National Science Foundation Information
Technology Research Initiative within the REC Division through
the Research and Learning On Education Award (0113369).
RICHARD GOLDEN HOME PAGE