Fred,

I certainly agree that K-12 education has retention issues related to
mobility; however, the difference as I see it is twofold. First of all,
most schools run on a 180 cycle and children are expected to attend
every day that they're healthy and reside in the district. Secondly,
while an individual teacher may structure his/her instructional
segments, most students don't have the ability to choose whether or not
to attend a given session. I suspect that the attendance issue in K-12 -
at least up until 9th or 10th grade - is related to the family's
mobility rather than to student motivation.

 

Most adult education programs in Pennsylvania, have an average
attendance of 60 to 100 hours per year. Mobility is certainly a factor,
but in my experience most adults "stop out" for many reasons other than
mobility. As a program director, I have tried various combinations of
intensity and duration. One of the ways we've worked on retention is to
have each teacher create a scattergram of his/her retention patterns.
One axis of the graph is the number of hours available, the other axis
is the duration of the class. What we found is that different patterns
emerge on the scattergram with different teachers. We then work with
teachers individually to develop improvement strategies based on their
individual patterns. For example, a teacher with students who cluster in
the low intensity/low duration quadrant would use very different
retention strategies than a teacher who has students clustering in the
low intensity/high duration quadrant or a teacher whose scattergram is
evenly distributed across the four quadrants. Ultimately, the teacher's
goal is to see his/her students clustering in the high intensity, high
duration quadrant. Our experience suggests that working with teachers on
their scattergrams and retention strategies has a positive impact on
student retention.

 

If Larry's research can be replicated, it speaks to a couple of very
important issues for our field. Open entry/open exit is one of them. The
second is the length of the instructional segment, regardless of
intensity. Our program has operated under the assumption that low
intensity classes need to be longer in duration. For example, our night
classes tend to run in 14 week segments whereas our daytime, high
intensity classes tend to run about 7 weeks. This research certainly
challenges this assumption. 

 

Sandy

 

________________________________

From: assessment-bounces at nifl.gov [mailto:assessment-bounces at nifl.gov]
On Behalf Of Fred Lowenbach
Sent: Wednesday, April 18, 2007 5:15 PM
To: The Assessment Discussion List
Subject: [Assessment 749] Re: Using Data for Program Improvement

 

Hopefully everyone participating in this discussion regarding adult
literacy is aware that almost everything you are saying applies to the
results for students in school as well.  Coming from a public school
background you could always see the effect that high mobility rates had
on overall student results.  Schools with those highest rates almost
always struggled to meet standard on state measures connected to NCLB.
This was the case with overall populations as well as various subgroups
that were tested.  The same applies to student retention, or for that
matter attendance.  As a rule, student who attended regularly achieved
much higher grades than students whose attendance was far less
consistent.  This then followed suit with results on standardized
testing and ultimately on graduation rates.

 

The entire education community, whether it is involved with adult
literacy, or the traditional K-12 curriculum is faced with the same
thing.  The key to increasing literacy and to closing achievement gaps
starts with getting and retaining students.

 

________________________________

From: assessment-bounces at nifl.gov [mailto:assessment-bounces at nifl.gov]
On Behalf Of Condelli, Larry
Sent: Wednesday, April 18, 2007 3:33 PM
To: The Assessment Discussion List
Subject: [Assessment 748] Re: Using Data for Program Improvement

 

Sandy,

 

A few years ago I did a study on adult ESL literacy students that
focused primarily on instruction.  But we also looked at retention.  We
found that the proportion of time an ESL literacy student attended
(measure by hours attended over total hours class was scheduled) had a
positive effect on oral English skills and reading comprehension, all
else being equal (using a complex statistical model).

 

The possible reasons for this effect are intriguing and need more
research.  Because this measure showed an effect regardless of how many
hours the student actually attended (or how many hours per week a
student attended), my interpretation is that this measure is a measure
of motivation (although I have no data or other information to check
this).  In other words, the student who continues to attend over time,
despite all of the other competing demands on time, is one that is more
motivated.  This motivation helps learning.  

 

I think if true, it does have implications for structuring instructional
segments.

 

________________________________

From: assessment-bounces at nifl.gov [mailto:assessment-bounces at nifl.gov]
On Behalf Of Sandy Strunk
Sent: Tuesday, April 17, 2007 5:38 PM
To: The Assessment Discussion List
Subject: [Assessment 736] Re: Using Data for Program Improvement

Larry,

Could you tell us more about the ESL research on percentage of possible
time attended? This is a new idea to me. Does it reflect greater
intensity as opposed to lesser intensity for a longer duration - or do
you think something else is going on? If your research is correct, there
are certainly implications for how we structure instructional segments. 

 

Sandy Strunk

 

________________________________

From: assessment-bounces at nifl.gov [mailto:assessment-bounces at nifl.gov]
On Behalf Of Condelli, Larry
Sent: Tuesday, April 17, 2007 5:31 PM
To: The Assessment Discussion List
Subject: [Assessment 735] Re: Using Data for Program Improvement

 

Hi Ella,

 

Disaggregating by class can be very effective to understanding of what
is going on.

 

I wanted to comment on your last remark about tracking consistency of
attendance.

 

Attendance and persistence are a very popular topics these days and most
data systems allow for tracking of student attendance and persistence
patterns.  One thing you might consider looking at learners who "stop
out" -- have sporadic attendance patterns, attending for a while and
coming back later. Another measure is the percent of time possible that
learners attend.  You compute this by dividing the attended hours by
total possible (e.g., learner attends 8 hours a week for a class
scheduled 10 hours a week=80%).  Some research I did on ESL students
showed that those who attended a higher proportion of possible time
learned more, independent of total hours.  I think this is so because
this measure reflects student motivation to attend.

 

Identifying and studying "stop out" learners might tell you a lot about
why these type of students don't attend more regularly and can inform
you of needs, which could help in designing classes and programs for
them.

 

________________________________

From: assessment-bounces at nifl.gov [mailto:assessment-bounces at nifl.gov]
On Behalf Of EllaBogard at cs.com
Sent: Tuesday, April 17, 2007 4:47 PM
To: assessment at nifl.gov
Subject: [Assessment 732] Re: Using Data for Program Improvement

Dear Collegues:

Here at Franklinton Learning Center, we use data everyday in our program
to help us track and improve the end results coming out of our program.
We use enrollment data to check the reach of our program, average hours
attended data to check the depth of engagement of students, and numbers
of students throught he door versus number completeing enrollment to
help us improve retention in the crucial orientation period of classes.

We have a program called ABLELink here in Ohio that has made it very
easy to track some areas. It has also allowedus to compare statistics
from one year to another so we know how we are doing in comparison to
previous years. By tracking information collected on attendance,
educational gain, hours of engagement and accomplishments, we have been
able to improve all of these efforts. 

Tracking and constantly checking this data is what has made it possible
to improve. We can easily pull up reports on testing, who has tested,
progress made, who hasn't tested, attendance, etc. We can organize that
information by class, by teacher, by program, or by site, which allows
us to compare effectiveness of programs and staff and assign
responsibility for improvement where needed.

I would like to be able to track consistency of attendance over time not
just total hours attended. I think this might give a better picture of
the progress to be expected than the total time attended does. I would
also like to understand more about how I can use all of the ABLELink
data collected to improve my programs overall effectiveness.

Respectfully submitted by,
Ella Bogard

Ella Bogard, Executive Director
Franklinton Learning Center
1003 West Town Street
Columbus, Ohio 43222-1438

Phone: (614) 221-9151
Fax: (614) 221-9131

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