Hawkins, A., Graham, C. & Barbour, M. K. (2010, October). Where are we losing them? (dis)Engagement patterns of virtual high school students. A paper presented at the annual convention of the Association for Educational Communication and Technology, Anaheim, CA. This study examined course completion and participation patterns of student enrollments at Utah’s Electronic High School from 2005-2008. Using descriptive statistics, researchers found that completion rates improved with the age of the program. Certain disciplines had higher completion rates as well as numbers of students who engaged in the course compared to other disciplines. A high percentage of students never engaged. Implications of the findings are discussed as well as areas for future research.

1. WHERE ARE WE LOSING
THEM?
(DIS)ENGAGEMENT
PATTERNS OF VIRTUAL
HIGH SCHOOL
Abigail Hawkins & Charles R. Graham, Brigham Young
University
Michael K. Barbour, Wayne State University

2. Study Context
 Attrition in K-12 online learning is aproblem.
(Barbour & Reeves, 2009; Berge & Clark, 2005; Bigbie&McCarroll,
2000; Cavanaugh, Gillan, Bosnick, Hess, & Scott, 2005; McLeod,
Hughes, Brown, Choi, & Maeda, 2005; Rice, 2006; Smith, Clark,
&Blomeyer, 2005; Zucker&Kozma, 2003).
 Targeted interventions = who, where, when, and
why of student drop outs (Institute for Educational Research,
2008).
 Study setting
 Oldest (est. 1994) and one of largest (2008
enrollments = 47,932)
 Asynchronous, self-paced, rolling-enrollment model
 Little published research
 High enrollments(i.e. 2008 =47,932) and attrition (i.e.
2008 = 68.9% )

3. Study Purpose
 Understand the WHERE and WHEN of
student dropout at EHS.
Study Questions
 When are students disengaging?
 Which disciplines are students
withdrawing/stopping out of?

4. Method
 Examined 85,297 enrollments from 2005 -
2008, descriptive statistics
 92 unique courses, 11 disciplines
 75 part-time teachers
 Student demographics limited
 50%credit acceleration, 30% credit recovery,
20% both
 Policy changes, Oct. 2007
 30 days inactivity = dropped
 Six-month completion time

5. Student Enrollments: 2005-
2008
60000
Significant growth over time.
50000
150% 47932
increase
# of students
40000
30000 32065
700%
20000 increase
10000
4493
0 802
2005 2006 2007 2008
years

6. Enrollments vs. Starters: 2005-
2008
60000 2008: 65% of students actually get out of the
gate.
50000 2007: 51% submit at least one assignment
# of students
40000
30000
All Enrollments
20000 Starters
10000
0
2005 2006 2007 2008
years

7. Completion Rates: All
enrollments
35
30 High attrition rates. 31.1
25
Improved retention over
% completion
time.
20 19.8
15
10.5 11.3
10
5
0
2005 (n=802) 2006 (n=4493) 2007 (n=32,065) 2008 (n=47937)
years

8. Completion rates: Enrollments vs.
Starter
60 Eliminate non-
50
starters, completions 52.3
jump by 20%.
% completion
40
34.5
30 31.1
All Enrollments
20 19.8 Starters
15.8
10 10.5
10.4 11.3
0
2005 2006 2007 2008
years
* Starters defined as enrolled and submitted at least one graded assignm

9. Reconsidering Non-Starters
 Old view:
lazy, unmotivated, ex
pect it will be easy
 Is there an alternative
way to view this
behavior?
 Alternative view:
smart, self aware
 Will this work for me?
 Does it meet my
expectations for
WHAT and HOW I
want to learn?
Image source: http://atlasschoolblog.files.wordpress.com/2009/08/lazy_student1.jpg

10. On Opening Access
Email dated Feb 21, 2010
Dear Ms. Walker,
Hey i am debating on whether or not to take U.S.
government with EHS, and i thought that by filling
out the class registration i would be able to see
how the class was like. However, i wasn't able to
and now am enrolled so i was wondering how i
can see what the class is like and also if i can get
of the enrolled waiting list, and how.
Thanks,
student

11. Non Starter Implications
 Students are enrolling without knowing what
they are getting into. Explore and
realize, “Hey, this isn’t for me.”
 If you were to make the content open for
students to examine BEFORE enrolling, then
the costs associated with
enrolling, withdrawing, seat space within
course can be reduced
 Gives more decision-making power /
ownership back to the student

12. Completion Rates by Discipline
Computer… * Financial literacy and
Fine Arts Health are required courses
World… and may attract credit
Science acceleration students
Language Arts
Mathematics
* Speculate that
Electives /…
FL, PE, and Driver’s Ed.
Social Studies are more applied
Driver's…
Health / PE
Financial…
0 20 40 60
%
completion

13. Completion Rates by Discipline
Computer…
Fine Arts Research indicates math may
World… be harder online. Not
Science
necessarily true at EHS.
Language Arts
Mathematics
Electives /…
Social Studies
Driver's…
Health / PE
Financial…
0 20 40 60
%
completion

14. Completion Rates by Discipline
Computer…
* Why computer science?
Fine Arts
* Why fine arts?
World…
* Factor of content? Tool?
Science
Teacher? Student?
Language Arts
Mathematics
Electives /…
Social Studies
Driver's…
Health / PE
Financial…
0 20 40 60
%
completion

15. Non Starters by Discipline
•Where are students not even
Driver's Education starting?
Financial Literacy
Electives / Career
Health / PE
Science
Social Studies
Computer Education
Fine Arts
World Languages
Language Arts
Mathematics
0 10 20 30 40 50 60 70 80
% of non starters

16. Non Starters by Discipline
•Why?
Driver's Education
•Course quality low?
Financial Literacy •Instructional approach
Electives / Career mismatch?
Health / PE •Pure exploration?
Science
Social Studies
Computer Education
Fine Arts
World Languages
Language Arts
Mathematics
0 10 20 30 40 50 60 70 80
% of non starters

17. Mathematics Completion Rates
60% What does this data tell you?
50%
% compeltion
40%
Pre Algebra
30% Algebra I
Algebra II
20% Geometry
Calculus
10%
0%
Q1 Q2 Q3 Q4
quarters

18. Mathematics Completion Rates
Quarter 1 has higher attrition
than other quarters.
60% What is happening in Algebra II
and Calculus?
50%
% compeltion
40%
Pre Algebra
30% Algebra I
Algebra II
20% Geometry
Calculus
10%
0%
Q1 Q2 Q3 Q4
quarters

19. Language Arts Completion Rates
(2008)
12 (n=814)
Grade Level
11 (n=1771)
10 (n=1461)
9 (n=2683)
0 5 10 15 20 25 30
Percentage

20. Grade Distribution: 2005 - 2008
Non Complete
Grade Awarded
D
* Bimodal grade
C 2008
distribution
2007
* Over time more 2006
B
credits awarded 2005
A
with higher grades
0 20 40 60 80 100
% of credits awarded

21. Time to Completion*
Year Mean in n Std.
Days Deviation
2005 630.51 86 421.99
2006 500.03 497 250.98
2007 260.44 6,159 162.79
2008 141.56 14,213 102.03
* Filtered out days with post dated grades.
Included length in class >= 3 days

22. Time to Completion by
Discipline
Computer… Completing faster
Fine Arts as program
World… stabilizes
Science
Language Arts
2008
Mathematics
2007
Electives /…
2006
Social Studies
2005
Driver's…
Health / PE
Financial…
0 500 1000 1500

23. Duration of Activity in Calculus
Course for Non Completers
80
70
60
What does this data tell
you?
# of students
50
40
30
20
10
0
0
4
7
71
14
18
29
35
48
58
81
94
121
131
141
153
168
183
202
230
259
300
days

24. Duration of Activity in Calculus
Course for Non Completers
(n=149)
80
70
60
Majority of non-completers
stop all activity within first
# of students
50
three days of enrollment.
40
30
20
10
0
0
4
7
71
14
18
29
35
48
58
81
94
121
131
141
153
168
183
202
230
259
300
days

25. Duration of Activity in English 9
Course for Non Completers
(n=1,679)
Frequency
300
250 Majority of non-completers
stop all activity within first
# of students
200
week of enrollment
150
100
50
0
302
332
103
124
139
163
187
212
245
273
383
420
472
570
0
14
28
42
56
72
86
days

26. Duration of Activity in English 9
Course for Non Completers
(n=1,679) Frequency
300
250 Non completer duration of
# of students
200 activity mean: 64 days
150 Completer duration of
activity mean: 132 days
100
50
0
103
124
139
163
187
212
245
273
302
332
383
420
472
570
0
42
14
28
56
72
86
days

27. Study Implications
 Necessity of tracking
 Data driven decision making
 Minimum: who, where, when…why
 Opening access to allow for preview
 Ormond Simpson – Open University, UK Samplers
 David Wiley – Brigham Young University, Courses
 Examination of Discipline
 Content? Medium? Teacher? Age?
 Increase research on affordances, limitations w/in dis.
 Mismatch between how do it online and how think
learn online?

28. Future Directions
1. Quantitative understanding
 Who?
 When?
 Where?
2. Qualitative understanding
 Why?
 Challenging. Common Patterns? Common
barriers?

29. References
 Barbour, M. K., & Reeves, T. C. (2009). The reality of virtual schools: A review of the
literature. Computers & Education, 52(2), 402-416.
 Berge, Z. L., && Clark, T. (2005). Virtual schools planning for success. New York:
Teachers College Press.
 Bigbie, C., &McCarroll, W. (2000). The florida virtual high evaluation 1999-2000
report. Retrieved October 15, 2007, from
http://www.flvs.net/educators/documents/pdf/archived_evals/FLVS%20Annual%20Ev
aluations/99-2000/99-2000%20Year%20End%20Evaluation.pdf
 Cavanaugh, C., Gillan, K. J., Bosnick, J., Hess, M., & Scott, H. (2005). Succeeding
at the gateway: Secondary algebra learning in the virtual school. Jacksonville, FL:
University of North Florida.
 McLeod, S., Hughes, J. E., Brown, R., Choi, J., & Maeda, Y. (2005). Algebra
achievement in virtual and traditional schools. Naperville, IL: Learning Point
Associates.
 Rice, K. L. (2006). A comprehensive look at distance education in the K-12 context.
Journal of Research on Technology in Education, 38(4), 425-448.
 Smith, R., Clark, T., &Blomeyer, R. (2005). A synthesis of new research in K-12
online learning. Naperville, IL: Learning Point Associates.