The document discusses the challenges of student dropout in distance education, highlighting statistics on dropout rates and factors influencing students' decisions to leave their programs. It outlines consequences of dropping out for both students and institutions, emphasizing the importance of motivation and proactive support to improve retention. Additionally, it presents a retention formula focusing on appropriate course choice, early identification of at-risk students, and continuous motivational support as key strategies to reduce dropout rates.

1. 1
'Student dropouts in distance education
- how many, who, when, what are the consequences for
them, why they dropout and how do we reduce dropout?‘
Ormond Simpson
Visiting Fellow, Centre for Distance Education, University of London
Previously Visiting Professor, Open Polytechnic of New Zealand
Previously Senior Lecturer in Institutional Research, UK Open University
September 2016

2. 'Supporting Students for Success
in Online and Distance Education'
(2013) - now out with Routledge
http://tinyurl.com/
supporting-students
2
Website www.ormondsimpson.com
- has articles, podcasts and videos

3. Understanding student dropout in distance education
1. How many students drop out of distance education?
2. Who drops out?
3. When do they drop out?
4. What are the consequences of dropping out
- for students? - for distance institutions?
5. Why do students drop out?
6. So how do we reduce dropout?

4. 4
1. How many students drop out?
82
39
61.5
15.7
22
5.3 2.5 0.5
14
6
0
10
20
30
40
50
60
70
80
90
100
Conventional institutions
Distance institutions
Conventional and distance graduation rates compared

5. 0
10
20
30
40
50
60
70
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
CumulativeOUGraduationratesbyyear ofentry
1971entry 1976entry 1981entry 1997entry
5
1971 - 59%
1976 - 52%
1981 - 48%
1997 - 22%

6. UKOU % graduation rates by year of entry
0
10
20
30
40
50
60
70
6

7. 7

8. Early Identification of vulnerable students
‘Binary regression analysis’ - calculates a ‘predicted
probability of success’ for every OU student.
0
2000
4000
6000
8000
10000
12000
14000
0-10 11-20 21-30 31-40 41-50 51-60 61-70 71-80 81-90 91-100
numberofstudentsinband
predicted probability of success band
8
2. Who drops out?

9. Most important predictors of dropout
9
2. Who drops out?
Student factors in dropout Predictive
coefficient
1. ‘Wrong’ course choice 0.77 Most
important
Less
important
2. Low previous education 0.70
3. Ethnic minority 0.36
4. Manual occupation 0.34
5. Being male 0.16
6. Age – both young and old 0.17

10. 3. When do students drop out?
10

11. 100
62 57 52
38
43
48
7
2
5
100 students start module. At each assignment some drop out into the ‘exit’ channel.
A very few re-enter the ‘progress’ channel having skipped the previous assignment.
Overall dropout during one module = 45%
Assignment 1 Assignment 2 Assignment 3
Progress
Exit
Dropout during one UKOU course module
A Retention ‘Rivergram’

12. Probability of students suffering depression, unemployment and
(women) partner violence, according to educational experience
(Bynner, 2002)
Probability of:
12
4 What are the consequences of dropping out
- for students?
dropouts

13. 13
4 What are the consequences of dropping out
- for distance institutions?
Reputational damage
Students not re-enrolling
for second or later years
Loss of institutional
income and government
support
E.g. The Open Universiteit Nederland could
face closure because of low retention rates
Open
Universiteit
Nederland

14. 14
5. Why do students drop out?
- student-related reasons
1. Analyse the statistics
– e.g. the predictive model
2. Ask them
Questionnaires and focus groups

15. 15
UKOU Withdrawal questionnaires

16. 16
UKOU Withdrawal questionnaires - responses

17. 17
UKOU Withdrawal questionnaires - responses

18. 18
Professor Edward Anderson
1942-2005
“The best predictor of student
retention is motivation.
“Retention services need to
clarify and build on motivation
and address motivation-
reducing issues.
“Most students drop out
because of reduced motivation”
6. So how do we reduce dropout?
- look at students’ motivation to learn

19. 19
Professor Edward Anderson
1942-2005
‘Student self-referral does not
work as a mode of promoting
persistence.
‘Students who need services
the most, refer themselves the
least.
‘Effective retention services
take the initiative in outreach
and timely interventions.’
6. So how do we reduce dropout?
- look at students’ motivation to learn
So we must do two things:
1. Ensure students are on the right course for them
2. Make proactive interventions with them

20. 20
Seidman’s ‘Retention Formula’
Retention = EId + (E + I + C)Iv.
where Eid = early identification,
E+I+C = Early Intensive and Continuous
Iv = Intervention
Dr. Alan Seidman
Editor ‘Journal of College
Student Retention’
6. So how do we reduce dropout?

21. The ‘Retention Formula’
Retention = AC + EId + (E + C).PaMS + ExS
1. AC = Appropriate Course Choice,
2. EId = Early Identification of vulnerable students
3. (E + C) = (Early and Continuous)
4. PaMS = Proactive Motivational Support
6. ExS = External Support
(the Simpson-Seidmann formula…?!)
21

22. Retention Formula - term 1
AC = Appropriate Course Choice
1. Taster Packs
- samples of course content and assignments
2. Students’ Reviews
- comments on courses they’ve taken
3. Diagnostic quizzes
- course specific and generic
Retention = AC + EId + (E + C).PaMS + ExS
22

23. Appropriate Course Choice – 1. Taster Packs
23
UKOU Taster Pack contents
Course sample, specimen assignment questions,
specimen answers and tutors’ comments

24. 24
Appropriate Course Choice – 2. Student reviews

25. 25

26. 26
Appropriate Course Choice – 3. Diagnostic quizzes
(a) Course specific
- for maths, science and technology subjects
(b) Generic
- and for humanities and social science subjects

27. HOW GOOD ARE YOUR CHANCES OF PASSING?
Start with 60 points
1.Are you male or female?
Male : Subtract 5 Female: No change
Revised Score: points
2. How old are you?
Under 30 : Subtract 13
Age 30 or above : No change
Revised Score: points
3. What level is this course?
Level 1: Add 23 Level 2 : Add 11
Other: No change
Revised Score: points
4. What Faculty is this course?
A : Add 16 D or L: Add 8
E or K: Add 7 M : Add 6
S : Subtract 3 T : Add 1
Other: No change
Revised Score: points
27
Generic diagnostic quizzes

28. How did you score?
• 100 or above: (70%+ chance of success) The outlook is very bright for
you. You’ll undoubtedly have your share of challenges but you should
be able to get things off to a good start.
• 75 to 99: (50-60% chance of success) This will be a challenge you’ve
taken on and it will be good to increase your point score in some way.
For example think about changing to a lower level course – you can
speed up later on. If you are taking more than one course think about
switching to just one.
• Under 75: (50% or lower chance of success) You’ll still be able succeed
but if you can increase your score that would really improve your
chances. You won’t want to change sex(!) but you could change to a
simpler course to start, increase your current qualifications by taking a
short course of some kind, and so on.
28

29. (E + C).PaMS = Early and Continuous Proactive
Motivational Support
- taking initiative to contact individual students
interactively as early as possible.
1. Early? – because students drop out very
early in their courses
2. Proactive? – because ‘we must reach the
quiet student’ (Bogdan Eaton, 1997)
3. Motivational? – because students drop out
through loss of motivation (Anderson)
Retention = AC + EId + (E + C).PaMS + ExS
29

30. 30
Learning motivation
‘What do we know about motivating students to learn?’
- podcast
‘Motivating learners in open and distance learning: do we
need a new theory of student support?‘
- article
Both on www.ormondsimpson.com

31. Proactive student support - evidence
Study Method Finding Notes
Rekkedahl
‘82 Norway
Postcards 46% increase in retention
Case et al
’97 US
Phone calls 15-20% increase in
retention
2 - 5 calls most
effective
Visser
‘90 UK
Postcards 27% increase in retention Small scale study
Chyung
‘01 US
Phone calls Dropout reduced 44% to
22%
Mager
‘03 US
‘Telecounselling’ 5% increase in retention Cost-effective
625% return
Simpson
‘06 UK
Phone call before
course start
5.04% Cost–effective
460% return
Twyford
‘07 Aus.
Motivational emails 11.7% increase over control
Huett
‘08 US
Motivational emails 23.4% increase over control Significant at 0.5%
Simpson
‘01 UK
Phone calls plus
motivational emails
18.9% increase over control
31

32. 3232
ExS = External Support
- UKOU survey of sources of support to students
Importance to students Source
Most important
Least important
From families and friends
From tutors
From other students
From employers
From the institution directly
(Asbee and Simpson 2001)
Retention = AC + EId + (E + C).PaMS + ExS

33. 33

34. 343434

35. ‘Student mentoring’
Students who’ve completed a course
mentoring new students on that course.
- Increased retention by 35% over
non-mentored group
(Boyle et al 1998 – joint project UKOU, KNOU and OPNZ)
35

36. “The biggest reason for student dropout
in an institution is the institution itself”
- Johnston (2002)
36
5. Why do students drop out?
- institution-related reasons

37. 37
1. Poor course design
- see podcast 'Distance course design for retention‘
2. Institutional attitudes – “We must weed out the unfit”
- see article ‘Retentioneering higher education in the UK:
attitudinal barriers to addressing higher education
student retention in UK universities‘
3. Insufficient funding for student support
- but there can be! – see ‘Cost benefits of student
retention policies and practices‘
All on www.ormondsimpson.com
5. Why do students drop out?
- institution-related reasons

38. 38
Reducing student dropout
$ More funds for student support and teaching
Increases student
retention
More students
carrying on to the
next year -
increased student
fee income
A positive funding triangle?

39. “If a tutor phones me I love them already” - NZ student
So make individual proactive contact with your students
Thank you!
www.ormondsimpson.com
39
“R = AC + EId + (E + C).PaMS + ExS”
The ‘Simpson-Seidman’ formula