Reporting and Analysis
Estudias Enterprise provides
several types of reports built-in
Enterprise Reports
Enterprise Reports are based on an OLAP database. We have OLAP cubes that describe all the main
concepts that are needed by the typical IR office. Because these
reports can be modified interactively (via drag and drop, dropdown
filtering), potentially millions of different Enterprise Reports can
be generated. For example, users can drag other fields such as
academic program, gender, ethnicity.
Other sample reporting areas: Time to degree (normalized by degree type), Financial Aid Awards
Completion Point Reports
The Completion Point Reporting Engine
is a powerful tool for calculating conditional probabilities and
time series analyses. Users can ask questions like:
- Once a student enrolls in class
X, how long does it take him/her to pass it? How long before
he/she will enroll in/pass the subsequent class?
- Gatekeeper Course Analysis:
Once a student passes class X,
what is the probability that he/she will graduate in 3 more
years?/li>
- Gatekeeper Course Analysis: What is the probability of
success in a class given that the student succeeded/completed
another class?
- Placement Analysis: What is the probability of
achieving an associate degree given that student received a
given score in a placement test?
- What percentage of students in a
particular cohort (academic program, gender, ethnicity)
graduated within 8 terms of enrolling?
 Comparing cohorts with Term Index
Ad-hoc Reports
Not all queries can be handled with OLAP cubes. Those that involve arbitrary ranges (i.e. students with
GPA < 2.25) or those that involved very complicated criteria (i.e.
students who failed in one term and are retaking classes in another
term) cannot be done well in OLAP cubes. Estudias includes a
specialized engine for handling these types of requests. These
reports are created by first selecting the entities to report on—for
example, the set of students to include in the report. Then a
report is chosen from a list of reports which can be extended by the
end-user. The report is then applied to the list of selected
entities.
The mechanism used to select
students, is called the Navigator in Estudias. It allows the user
to select students by using almost any conceivable criteria. It
also allows the user to use more than one criterion at a time. This
is done in a very intuitive user interface that is meant for
non-technical people. The navigator can be extended by end-users if
additional ways of selecting entities / building blocks are
required.
The reports that are provided are
quite extensive and can be extended by end-users. The process of
selecting students is decoupled from the reporting so that any
report can be run on any group of students. The end result of this
style of report generation is that literally millions of different
reports can be generated without the need to customize the product.
The student groups are implemented as
simple SQL statements, so it is almost trivial to add new groups
Identifying students who may be at risk
Student Engagement Reports
Schools that license the Student Engagement
module can effectively link the services they are providing to
learning outcomes. This data can be used operationally: how many
students are we seeing per day/week/time of day? Which departments
are most successful at helping students improve GPA?
The data can also be used strategically. i.e.
We are making an effort to reach out to at-risk students. Is it
having an impact on retention, graduation, GPA? How much? If we
expand by X number of students, how many additional advisors will we
need?
IR offices can use the student engagement
module to send out graduation surveys and measure responses.
Contact Summary by Reason
Predictive Analytics
It’s almost a cliché now,
but the maxim is still true: Reporting on the past is like driving
by looking through the rear view mirror. Predictive analytics such
as enrollment prediction allow colleges to look towards the future.
ZogoTech is able to offer some of the strongest predictive analytics
by working off of the tools that Microsoft includes with
SQL-Server. Whereas other companies have spent millions on
developing proprietary data mining algorithms, ZogoTech is able to
leverage Microsoft tools and focus its time on customizing those
algorithms for higher education.
Geo-Spatial Analysis
Analyze students by incoming zip code or address looking at
metrics such as Average
Education, •Household
/ Disposable income,
Population, Age, Ethnicity, and Crime.
Geo-Spatial Analysis
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