This document discusses knowledge management for educational information systems. It addresses several key topics: [1] the dimensionality of analyzing educational data including levels, frameworks, data structures, and infrastructure; [2] the differences between data, information, and knowledge; [3] the goals of knowledge management projects such as creating knowledge repositories and improving access; and [4] challenges such as the mismatch between time cycles for assessments and the lack of communication hindering systemic improvement.

1. Knowledge Management for
Educational Information Systems
What is the state of the field?
Christopher A. Thorn
Center for the Study of Systemic Reform

2. Information Networks &
Systemic Reform
 Dimensionality of analysis
 Unit/level – states, districts, schools,
classrooms, individuals (students, teachers,
administrators)
 Analytical framework – student assessment,
program effectiveness, fiscal efficiency, etc.
 Data structures – state records, student record
systems, lesson plans, portfolios, test scores, etc.
 Technical infrastructure – networking,
technical skills, availability of support, etc.

3. Data, Information, and Knowledge
Knowledge…is not data and it is not information. Data
are objective facts, presented without any judgment or
context. Data becomes information when it is
categorised, analysed, summarised, and placed in
context.
Information therefore is data endowed with relevance and
purpose. Information develops into knowledge when it
is used to make comparisons, assess consequences,
establish connections, and engage in a dialogue.
(Empson, 1999).

4. What do KM projects attempt to do?
 Create knowledge repositories
 External knowledge, structured internal knowledge, and
informal internal knowledge
 Improve access
 Technical expert referral, expert networks, and turn-key
video conferencing
 Enhance knowledge environment
 Change organizational norms and values
 Manage knowledge as an asset
 Attempts to measure the contribution of knowledge to
bottom line

5. The unit of analysis: individuals
 All assessments, programs, treatments, referrals, etc.
are delivered to individual students. Data systems
that do not collect and keep information at this level
will have limited utility.
 The lowest common unit of analysis (sometimes
referred to as an atomistic unit) should drive data
collection efforts and processes. If the student is the
smallest entity that will be studied, then attributes of
that entity should be collected.

6. How Information Creates Value
Add Value
Organization A Organization B
Manage Reduce
Risks Costs
Organization C
Create New reality

7. Mismatch in time cycles for
assessment at different levels
 State-level assessment systems focus on
school and district performance and have
slow turn around time that follows an annual
reporting calendar.
 School- and classroom-level assessments
are used almost immediately for diagnosis
and student feedback
 District-level assessment falls in between

8. Benefits to introducing KM
 Enthusiasm for knowledge
 Staying ahead in knowledge
 Tight coupling of complementary skill sets
 Iteration in activities
 Higher order learning

9. The case of 8th grade promotion:
the context
 District-wide technology strategic plan
 Classroom management in a decentralized
organization
 School management in a decentralized
organization
 Accountability in a decentralized organization
 Ambitious modernization of all central IT
 District-wide rewiring of all schools and
classrooms

10. Timeline of policy & outcomes
Data Warehouse
Middle School Proficiencies
Student Management System
Middle School Collaborative Districtl Level
School Level
High Stakes
for 8 th Grade
1996/97 1997/98 1998/99 1999/00 2000/01 2001/02

11. Where is this heading?
 The district did not look at this emergency as
a wake-up call. There is no systemic effort to
improve communication
 The SMS and data warehouse are now
several years behind schedule and are likely
to be completely reworked before ever rolling
out district wide
 The introduction of all-grades testing in
multiple subjects will impose additional
burdens on the system in the near future

12. For more information
Christopher A. Thorn
Wisconsin Center for Education Research
http://www.wcer.wisc.edu
cthorn@wcer.wisc.edu
608-263-2709