Towards a Conceptual Model of Retention and
Success in Distance Education:
The Case of the University of South Africa
Presented at the Young Academics Programme
22 September, 2009
Prof George Subotzky
Executive Director: Information & Strategic Analysis
University of South Africa
Overview
• Background & Context
• Appropriate Measurement and Quantification of
the Retention and Success Challenge at Unisa
• Towards a (unique?) Conceptual Model for
Distance Education Retention and Success
Background
• Retention and Success a major focus of concern worldwide
and, consequently, of IR internationally
• A particular challenge at Unisa, given its institutional character
as a distance education mega-university in the developing
country, new democracy context of South Africa
• Strong external imperative to improve retention and success
rates from government outcomes-based funding and
enrolment planning framework
• Strong internal imperative: key focus in all institutional policy
and planning documents
– 2015 Strategic Plan
– Recent Institutional Operational Plan Reviews
– Recent QA Audit Reports: 3 cohort case studies conducted
• Coordinated initiative through Throughput Forum as part of
ODL development
ODL – preferred business
model for Unisa
Through blended learning and innovative application
of technology, this focuses on bridging various kinds
of distances between:
– Student and institution (counseling, academic &
administrative services)
– Student and study materials (learner support)
– Student and other students (social networks &
community of scholarship)
Therefore, engagement central to ODL model
University of South Africa:
Quantifying the Retention & Success
Challenge
Key concerns
• Appropriate measurement & benchmarks
for success in DE Context
• Part of bigger concern for regulatory
environment to accommodate the
characteristics & dynamics of DE
Measuring Retention &
Success
• Two key elements:
– Graduation rate: volume-based measure of
efficiency
– Time to completion: time-based measure of
efficiency
• Retention: 1-year rates – universal measure
Benchmarking Time
to Completion
Two key characteristics of DE pertinent here
– Underpreparedness (majority phenomenon)
• Difficult to factor in accurately
• Tinto (2008): uses time and a half benchmark in relation to
study on low-income students in the US
– Predominantly part-time study load
• Average FTE:headcount ratio around 0.5
• Signals that on average Unisa students carry half a course load
• Central claim: Expected minimum time to completion should be
around double minimum time of qualification
– Together: 3-year UG qualification = 7.5 years??
South African Graduation, Dropout & In-process
Rates by Institutional Type, 2000 Cohort
Graduated
within 5 years
Still registered
after 5 years
Left without
graduating
Universities
(excluding Unisa)
50%
12%
38%
Unisa
14%
27%
59%
All universities
Technikons
(excluding TSA)
38%
17%
45%
32%
10%
58%
Technikon SA
2%
12%
85%
All technikons
23%
11%
66%
All institutions
30%
14%
56%
Institutional Type
Source: (Scott, et al, 2007)
Unisa Cohort Dropout Rates, 2001-7
Cohort
N
Y2
Y3
Y4
Y5
Y6
Y7
Y8
2001 44,551
37.7%
54.8%
60.9%
62.4%
63.5%
64.4%
65.0%
2002 46,216
47.5%
61.9%
65.1%
66.9%
68.4%
69.6%
2003 41,190
51.6%
59.3%
63.6%
66.6%
69.0%
2004 43,191
38.5%
49.8%
56.8%
61.4%
2005 43,428
36.6%
51.5%
60.3%
2006 51,478
44.2%
59.7%
2007 60,456
44.4%
Calculating expected
minimum time ito study load
• Course load indicated by FTE: headcount ratio
Expected minimum time = minimum time X
1
FTE: headcount ratio
• For example, for one of the three case studies, namely the 2007
B Com cohort, the calculation is as follows. This 3-year
qualification had a FTE: headcount ratio of ,456
Expected minimum time = 3 years X 1
,456
= 6,6 years
Case studies: Sample
• Cohorts in 3 UG qualifications
• 3 largest qualifications within the main
undergraduate degree qualification types chosen
as follows:
– General 1st Bachelor’s Degree (minimum duration 3
years): B Com
– Professional 1st Bachelor’s Degree (minimum duration 3
years): B Compt
– Professional 1st Bachelor’s Degree (minimum duration 4
years or longer): LLB
1st Case: B Com
Graduation, Attrition & Retention
Rates
Graduates
Cohort Entering
Year
Students
No
%
Dropouts/Transfers
Average
Time
(Years)
No
%
Average
Time
(Years)
In process
No
%
Average
Time
(Years)
1998
8 602
1 226
14,3%
5,77
6 499
75,6%
2,48
877
10,2%
7,39
1999
8 265
1 076
13,0%
5,43
6 088
73,7%
2,45
1 101
13,3%
7,09
2000
9 297
1 020
11,0%
5,03
6 739
72,5%
2,38
1 538
16,5%
6,23
2001
11 548
1 015
8,8%
4,88
8 486
73,5%
2,28
2 047
17,7%
5,80
2002
13 157
894
6,8%
4,44
9 431
71,7%
2,10
2 832
21,5%
5,17
2003
14 315
583
4,1%
4,14
10 131
70,8%
1,83
3 601
25,2%
4,39
2004
14 202
341
2,4%
3,50
9 355
65,9%
1,60
4 506
31,7%
3,68
2005
15 494
114
0,7%
2,82
8 932
57,7%
1,35
6 448
41,6%
2,89
2006
16 030
18
0,1%
1,83
6 745
42,1%
1,00
9 267
57,8%
2,00
2007
18 634
1
0,0%
1,00
18 633
100,0
1,00
B Compt: Graduation,
Attrition & Retention Rates
Graduates
Cohort
Year
Number
of
Entering
Students
No
%
Dropouts/Transfers
Average
Time
(Years)
No
%
Average
Time
(Years)
In process
No
%
Avera
ge
Time
(Years)
1998
3 430
1 008
29,4%
4,91
2 040
59,5%
2,90
382
11,1%
8,32
1999
3 205
881
27,5%
4,92
1 851
57,8%
2,80
473
14,8%
7,72
2000
3 593
831
23,1%
4,83
2 049
57,0%
2,70
713
19,8%
6,79
2001
4 035
717
17,8%
4,67
2 447
60,6%
2,50
871
21,6%
6,21
2002
3 931
588
15,0%
4,34
2 415
61,4%
2,22
928
23,6%
5,38
2003
4 351
486
11,2%
3,94
2 581
59,3%
1,91
1 284
29,5%
4,55
2004
4 364
298
6,8%
3,45
2 358
54,0%
1,66
1 708
39,1%
3,78
2005
4 873
127
2,6%
2,83
2 137
43,9%
1,37
2 609
53,5%
2,92
2006
5 167
23
0,4%
1,96
1 656
32,0%
1,00
3 488
67,5%
2,00
2007
6 519
6 519
100,0%
1,00
LLB: Graduation, Attrition
& Retention Rates
Graduates
Cohort
Year
Number
of
Entering
Students
1998
5 150
1 293
1999
3 125
2000
Dropouts/Transfers
In process
Average
Time
(Years)
No
%
Average
Time
(Years)
25,1%
3,95
3 378
65.59%
2,46
479
9.30%
7,39
577
18,5%
4,24
2 184
69.89%
2,44
364
11.65%
7,03
3 622
470
13,0%
4,68
2 538
70.07%
2,47
614
16.95%
6,07
2001
3 938
370
9,4%
4,55
2 888
73.34%
2,25
680
17.27%
5,79
2002
4 248
312
7,3%
4,31
3 014
70.95%
2,08
922
21.70%
5,26
2003
4 612
224
4,9%
3,89
3 155
68.41%
1,84
1 233
26.73%
4,52
2004
5 031
150
3,0%
3,13
3 180
63.21%
1,62
1 701
33.81%
3,74
2005
5 247
31
0,6%
2,48
2 893
55.14%
1,37
2 323
44.27%
2,90
2006
4 700
2
0,0%
2,00
1 988
42.30%
1,00
2 710
57.66%
2,00
2007
5 305
1
0,0%
1,00
5 304
99.98%
1,00
No
%
No
%
Average
Time
(Years)
B Com: Time to
completion by year
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
1
2
1998
3
4
1999
5
2000
6
7
2001
8
2002
9
10
B Compt: Time to
completion by year
7.0%
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
0.0%
1
2
1998
3
4
1999
5
2000
6
7
2001
8
2002
9
10
LLB: Time to
completion by year
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
1
2
1998
3
4
1999
5
2000
6
7
2001
8
2002
9
10
B Com: % entering students
dropping out by year
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
1
2
1998
3
1999
4
5
2000
6
2001
7
2002
8
9
B Compt: % entering students
dropping out by year
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
1
2
1998
3
1999
4
5
2000
6
2001
7
2002
8
9
LLB: Proportion of Entering
Students Stopping Out By Year
12.0%
10.0%
8.0%
6.0%
4.0%
2.0%
0.0%
1
2
1998
3
1999
4
5
2000
2001
6
2002
7
8
Conclusion
• Main Challenge: Reducing dropout as principal
focus to improve retention and success
• Time to completion satisfactory
• Time to dropout and stopout indicate risk
moments to be addressed through appropriate
interventions
University of South Africa:
Towards a DE Retention & Success Model
The UNISA Throughput Forum
• Strong external and internal imperative to improve
retention and success, especially in ODL context
• Co-ordinated and integrated effort to improve retention
and success
• Approach adopted: to achieve the comprehensive
understanding of all factors shaping retention and
success through modeling initiative
• Purpose of modeling initiative: to provide a systematic,
evidence-based, contextually-relevant foundation to
inform and guide initiatives to improve retention and
success
• This work undertaken by modeling Task Team
2-fold Framework for Enhancing
Retention & Success
1. Comprehensive modelling initiative
– Literature review (conducted by Dr Paul Prinsloo)
– Drawing from this, the conceptual/hypothetical modelling
of the positive and risk factors shaping the student
experience, retention & success in the ODL context of
Unisa (Modelling Task Team)
– Together, the literature review and conceptual model
released as a Strategic Discussion Forum discussion
document during April for expert response, comprehensive
engagement & feedback and then to STLSC & Senate, and
at two international and one local conferences
– Regarding the model, determining what variables are
knowable, measurable, (is/may be) available and actionable
– Utilising model to shape student tracking system, to gather
relevant and available quantitative and comprehensive
complementary qualitative data (myUnisa)
– Statistical and analytic modelling to determine factors
shaping success and to predict and address risk and
readjusting the model as necessary
A 2-fold framework for enhancing
throughput & success
2. Transforming institutional identity, attributes &
practices
–
Utilising consolidated findings (as actionable
intelligence) to inform and guide existing and new
Learner Support Framework and initiatives and
academic practices and operational improvements in
order to improve success, throughput and the
student experience;
– Monitoring and evaluating these initiatives over time
as part of continuous reflection and improvement
and ongoing QA
MANAGEMENT OF STUDENT EXPERIENCE, RETENTION, SUCCESS & GRADUATENESS
Shaped by modeling process
Conceptual
Modeling
M&E
Learner
Support
Interventions
and other
academic &
administrative
changes
Identifying
what is
relevant,
measurable,
available &
actionable
Tracking
System
Statistical &
Analytic
Modelling
producing
Actionable
Intelligence
Overview of the literature
review
1. The comprehensive review covered the literature from
the earliest model proposed by Spady in 1970 to
current theoretical developments
2. This included retention models
• In international HE (Spady, Bean, Tinto, EPI)
• In international distance education (Kember,
Simpson)
• In South Africa (REAP, Koen, CHE).
3. Theoretically, the models range from strictly
sociological (Baird, Berger) to anthropological
(Hurtado), social-critical (Tierney) and psychological
(Bean and Eaton)
28
2
Some pointers
1. Student retention is a complex, layered and dynamic
set of events.
2. International models are not appropriate to the specific
African, developing country and ODL context of Unisa.
3. In particular, they do not recognise need for
institutional transformation – an especially prominent
issue in SA HE policy.
4. Self-efficacy, attribution and locus of control are
important constructs in explaining students’ academic
and social trajectories (extrapolated in the model to
explain institutional attributes as well).
29
Some pointers
5. In an ODL context, non-cognitive and institutional factors
may impact more on student success than in residential
settings.
6. While important to identify relevant variables in the Unisa
context, even more important will be to determine the
combined effects of, and relationships between different
variables at different points in the student journey.
7. Research into student retention and success should be
quantitative and qualitative.
• Relatively low proportion of retention variance explained
by current statistical models
• Complementary strategy: Obtain rich qualitative
information as part of ‘thick’ student profiling and
ongoing intensive 2-way engagement
30
Key Constructs
• Situated agents: student and institution
– Historical, geographical and socio-cultural backgrounds
– Capital
– Habitus
• Student Walk
– Mutual engagement
– With regard to academic & non-academic factors
• Broad definition of success
• Transformation process
– Managing risks and opportunities
– Domains: student – Intra-personal and inter-personal
institution – academic, administrative & social
– Modalities: attribution, locus of control, self-efficacy
Key explanatory claims
• Success broadly defined:
– Fit at each stage of the student walk from preadmission to participation in workplace & society
– Includes course success, graduation & positive
student experience
• Success as the outcome of sufficient fit
• Sufficient fit as the outcome of mutual transformation to
ensure necessary preconditions
• Mutual transformation as the outcome of mutual
engagement
• Mutual engagement as the outcome of mutual
knowledge and co-responsibility
SHAPING CONDITIONS: (predictable as well as uncertain)
• Social structure, macro & meso shifts: globalisation, political economy, policy; National/local culture & climate
• Personal /biographical micro shifts
STUDENT
IDENTITY & ATTRIBUTES:
• Situated agent: SES, demographics
• Capital: cultural, intellectual, emotional,
attitudinal
• Habitus: perceptions, dispositions,
discourse, expectations
THE STUDENT WALK:
Multiple, mutually constitutive
interactions between student, institution
& networks
• Managing complexity/ uncertainty/
unpredictability/risks/opportunities
• Institutional requirements known &
mastered by student
• Student known by institution through
tracking, profiling & prediction
INSTITUTIONAL
IDENTITY & ATTRIBUTES:
• Situated organisation: history, location,
strategic identity, culture, demographics
• Capital: cultural, intellectual, attitudinal
• Habitus: perceptions, dispositions,
discourse, expectations
TRANSFORMED STUDENT IDENTITY & ATTRIBUTES:
Processes:
• Informed responsibility & ‘choice’
• Ontological/epistemological dev.
• Managing risks/opportunities/
uncertainty: Integration, adaptation,
socialisation & negotiation
F
I
T
F
I
T
Domains:
• Intrapersonal
• Interpersonal
Modalities:
• Attribution
• Locus of
control
• Selfefficacy
F
I
T
F
I
T
FIT
F
I
T
Retention/Progression/Positive experience
Choice,
Admission
Learning
activities
Course
success
Graduation
Employment/
citizenship
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
TRANSFORMED INSTITUTIONAL IDENTITY & ATTRIBUTES:
Processes:
• Informed responsibility & choice
• Managing risks/opportunities:
Transformation, change
management, org. learning,
integration & adaptation
Domains:
• Academic
• Operational
• Social
Modalities:
• Attribution
• Locus of
control
• Selfefficacy
SHAPING CONDITIONS: (predictable as well as uncertain)
• Social structure, macro & meso shifts: globalisation, internationalisation, political economy, technology, social demand
• HE/ODL trends, policy
• Institutional biography & shifts; Strategy, business model & architecture, culture & climate, politics & power relations
Success
FIT
Proposition 1
Student success is broadly interpreted and indicated by
course success, retention and reasonably quick progression
through the main phases of the student walk, and
ultimately successful graduation and effective
participation in the labour market and/or citizenship.
Success also incorporates a positive student experience as
a result of student-centred service excellence and efficient
operations provided by the institution.
Proposition 2
Student success and positive experience is the outcome of
sufficient fit between the identity and attributes of the
student and the institution through all phases of student
walk.
Proposition 3
Fit arises when elements of the student and institutional
identity and attributes (capital and habitus) are optimally
aligned at each successive stage of the student walk. Fit at
these various points is the outcome of the specific
individual student and institutional preconditions.
Proposition 4
In order for fit to arise at each successive stage of the
student walk, relevant transformative changes in the
identity and attributes of the student and the institution
are required.
Student & Institutional Transformation
• Processes
– Crucially dependent on relevant mutual actionable
knowledge
– This is an essential precondition in the management
of risks, uncertainties and opportunities
– Student: understanding institutional expectation &
requirements & executing these
– Institution: tracking, profiling, predicting relevant
activities, risks & opportunities and adapting practices
accordingly
Institutional Transformation
• The institution’s obligation is to continually reflect on its
assumptions and practices not only in order to improve
delivery but to eradicate hidden socio-economic and
cultural barriers to equitable student access & success
and thus to achieve the QA criterion of fitness to
purpose
• This captures the transformative approach, failing which
the institution perpetuates the social reproduction of
elites
Proposition 5
The student walk comprises a series of multiple, mutually
constitutive interactions between the situated student and
the situated institution and between them and their
various respective networks through all points of the walk
(Articulation with ODL model)
Proposition 6
The formation and transformation of student and
institutional identity and attributes is continuously shaped
by overarching conditions at the macro, meso and micro
levels
Conclusion
1.
2.
3.
4.
5.
6.
7.
8.
Unisa: Integrated, comprehensive approach to addressing the imperative of
improving success, throughput & student experience – modelling approach
Literature Review: Rich field of enquiry, with interesting array of theoretical
perspectives
International models not appropriate to developing country ODL context and
do not recognise imperative for institutional transformation
Unique features of Unisa Model: Key constructs and propositions, especially
the central component of the need for mutual knowledge, engagement &
transformation on the part of both student and institution
Evidence suggests that non-cognitive and institutional variables impact
equally (if not more) on student retention and success
The initial indications from the literature and the conceptual model, as well
as the envisiged qualitative and quantitative actionable intelligence should
provide the basis of a much more comprehensive understanding of the
student experience, retention & success at Unisa: key area of IR
On the basis of this, the risks facing students and the institution can be
identified, predicted, monitored & proactively addressed
In turn, this should provide an important basis for fulfilling the objectives of
the ODL model by helping to bridge the various distances between the
student and retention and success, as well as a positive student experience.
Thank you!
Professor George Subotzky
Executive Director: Information & Strategic Analysis
University of South Africa
subotg@unisa.ac.za