[education-wg] My Race to the Top Public Comment

[Tom Hoffman]

My public comment on the $350 million Race to the Top Assessment
Program (subsection Technology and Innovation) ended up being pretty
specific, but certainly relevant to open source and open data.

In general, among the participants and general discussion at the
forum, there was a general sense that almost everyone acknowledges at
least in principle that there is a role for "open" stuff, and that the
task now is to figure out how much, where, etc.

Anyhow, my comment, which I managed to present in exactly five minutes:


My name is Tom Hoffman, from Providence, Rhode Island.  I am a
technology consultant, specializing in student information and
assessment systems.  I am project manager of SchoolTool, an open
source administrative platform for schools.  I also work with the
CanDo project, which is an open source competency tracking application
used by Career and Technical Centers in Virginia.  I am a former
English teacher in the Providence Public Schools with a Masters in
Teaching English from Brown University.

I would like to recommend some specific facets of the technology
platform for assessment, particularly in reference to Race to the Top
Criteria:

B.(C)(2) Accessing and using State data:  ...support decision-makers
in the continuous improvement of efforts in such areas as policy,
instruction, operations, etc...

B.(C)(3)(iii) Making the data from instructional improvement systems,
together with statewide longitudinal data system data, available and
accessible to researchers...

These requirements suggest a high degree of data portability,
interoperability, and integration, with aspirations for complex data
warehousing, business intelligence and inferencing expert systems.

One of the technical foundations of this type of platform is the
development of ontologies, defined as "a formal representation of a
set of concepts within a domain and the relationships between those
concepts." (1)  Dr. Baker introduced this concept earlier.

The potential role of ontologies in educational research and
throughout the implementation of educational technologies and data
systems parallels to their growing role in biomedical research.

I would specifically propose funding the creation of a National Center
for Educational Ontology, modelled on the National Center for
Biomedical Ontology, which is funded by the National Institutes of
Health (NIH).

"The goal of the Center is to support biomedical researchers in their
knowledge-intensive work, by providing online tools and a Web portal
enabling them to access, review, and integrate disparate ontological
resources in all aspects of biomedical investigation and clinical
practice." (2)

The Center is funded by the NIH Roadmap for Biomedical Research's
Bioinformatics and Computational Biology initiative.  The Roadmap "was
launched in September, 2004, to address roadblocks to research and to
transform the way biomedical research is conducted by overcoming
specific hurdles or filling defined knowledge gaps... These are
programs that might not otherwise be supported by the NIH ICs because
of their scope or because they are inherently risky." (3)

With a consistent, ongoing commitment to the development and use of
ontologies, the National Institute of Health's Recovery Act fund is
already supporting 61 current research projects using or contributing
to biomedical ontologies. (4)

By comparison in education, despite contributions from a disparate set
of actors including the National Center for Research on Evaluation,
Standards, & Student Testing (CRESST) at UCLA and Jes and Co., a 501c3
education research organization, there is no central hub for research,
development and use of ontologies, individual projects tend to emerge
and disappear, and in particular there is no commitment to the kind of
open and collaborative environment that now typifies biomedical
ontology.

For example, the National Forum on Educational Statistics at the
Department of Education has created a National Educational Data Model.
 It is similar to an ontology, but the data model is more constrained
and potentially much less rich and powerful than an ontological
approach.  However, it would be an obvious foundation for development
of a subsequent set of educational ontologies.

CRESST has developed several detailed domain ontologies for specific
subjects such as Algebra as part of their research, however, unlike
their peers in biomedical research, publishing, collaborating and
promoting those ontologies does not seem to be a priority, which
limits their influence and impact.

Similarly, I can see from their presentations that CRESST have
developed a tool called CRESST Knowledge Mapper that looks quite
useful, but does not seem to be publicly available, either
commercially or for free, and thus does not contribute to or promote
further development of domain ontologies in education.  In contrast,
the National Center for Biomedical Ontology's Protege editor is an
active and prosperous open source software project that has become an
industry standard application.

As was the case in the biomedical field, an investment in educational
ontology is relatively high risk and does not fit obviously into
existing programs.  If we don't start the process while we have this
unique stimulus windfall, I don't know when we will.

Be assured, however, that this is essential foundational research.
Given the vast ambition for educational data systems, ontologies will
become as integral to educational research as they have become in the
biomedical field, and sooner or later the value of our solutions will
be bottlenecked by the quality of our ontologies.



(1) http://en.wikipedia.org/w/index.php?title=Ontology_(information_science)&oldid=324836821

(2) http://www.bioontology.org/about-ncbo

(3) http://nihroadmap.nih.gov/about.asp

(4) http://projectreporter.nih.gov/reporter_SearchResults.cfm