Understanding student success in distributed and online learning: a perspective from the Global South

Paul Prinsloo
University of South Africa (Unisa)
14prinsp
Understanding student
success in distributed
and online learning
Keynote at “Change and Constants:
The Realities of Successful Teaching and
Learning.”
McMaster University, Hamilton, Ontario
Friday February 23, 2018
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I do not own the copyright of any of the images in this
presentation. I therefore acknowledge the original
copyright and licensing regime of every image used.
This presentation (excluding the images) is licensed
under a Creative Commons Attribution 4.0 International
License.

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roadmap
Brief overview of the main elements in the
presentation
• Locating myself/disclosing my location
• What do we mean by distributed/online/
blended and how does this impact on
student success?
• Who defines student success and why it
matters
• Brief overview of some (historical) models
• Towards understanding student persistence
and success
• 7 Pointers for consideration and action

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We are “condemned to context”
(Tessmer & Richey, 1997, p. 88)
“[c]ontext is everything”
(Jonassen, 1993, in Tessmer & Richey, 1997, p. 86)
Locating myself
Revised title: Understanding student success
in distributed and online learning: a
perspective from the Global South
Tessmer, M., & Richey, R. C. (1997). The role of context in learning and instructional design. Educational technology
research and development, 45(2), 85-115.
Image credit: https://commons.wikimedia.org/wiki/File:Map_of_Africa_by_Hermann_Moll.jpg

Image credit: https://commons.wikimedia.org/wiki/File:Uitsig_oor_Unisageboue,_Lukasrandtoring.jpg
The University of South Africa (Unisa)-
The African University shaping futures
in the service of humanity

Unisa in a nutshell
• Student numbers (2017): 350,503 / (2018, so far) 305,647
• Student profile (race) (2016): 72,4% African, 5,6% Coloured,
6,5% Indian, 15% White
• Student profile (gender) (2016): 64,6% female, 35,4% male
• Student course success (2016): 71,9%
• Number of qualifications (2016): 643
• Pedagogical model: Blended, 7 College specific fully online
Signature modules
• Student graduation: ± 40,000 graduates per year
• Regional centres: 8 (including Ethiopia)
Source: 2016 statistics as per Institutional Annual Report. Retrieved from
http://unisa.ac.za/static/corporate_web/Content/News%20&%20Media/Publications/docs/10085798_UNISA_Annual_Report_2016.pdf
Image credit: https://pixabay.com/en/walnut-nut-shell-nutshell-open-3072681/

Unisa in a nutshell:
• Total staff (2016): 6,176
• Staff profile (race)(2016): 69.3% African, 24,1% White
• Staff profile (gender)(2016): 57,5% female, 42,5% male
• Staff profile (roles)(2016): 33,3%
(instructional/professional), 55,7% (non-professional
administrative)
• Faculty profile (race)(2016): Of a total of 564
professors/associate professors, only 147 are Black, and 294
are White (excluding foreign nationals)
• Faculty profile (gender)(2016): Male (327),
female (237)(including foreign nationals)
Source: 2016 statistics as per Institutional Annual Report. Retrieved from
http://unisa.ac.za/static/corporate_web/Content/News%20&%20Media/Publications/docs/10085798_UNISA_Annual_Report_2016.pdf
Image credit: https://pixabay.com/en/walnut-nut-shell-nutshell-open-3072681/

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What do we mean by distributed and online
learning?

Department of Higher Education and Training. (2014). Policy for the provision of distance education in South African universities in the context of
an integrated post-school system. Retrieved from http://www.saide.org.za/sites/default/files/37811_gon535.pdf
OfflineOnline Fully online
Fully offline
Digitally supported
Internet supported
Internet dependent
Campus-based Blended/hybrid Remote
A
BC
Distance, digitally supported
Distance, fully onlineCampus-based,
fully online

Source credit: http://contactnorth.uberflip.com/h/i/341120700-what-is-online-learning-seeking-definition
Going blended – the Canadian way
Distance education courses. Distance education courses are those where
no classes are held on campus – all instruction is conducted at a distance,
including print-based, video/audioconferencing, as well as internet-
based.
Online courses. A form of distance education where the primary delivery
mechanism is via the internet. These could be delivered synchronously
or asynchronously. All instruction is conducted at a distance.
Online programs. A for-credit program that can be completed entirely by
taking online courses, without the need for any on-campus classes.
These could be delivered synchronously or asynchronously.
Blended/hybrid courses. These are courses designed to combine both
online and face-to-face teaching in any combination.
Also issues of (a)synchronous and (non)credit

Department of Higher Education and Training. (2014). Policy for the provision of distance education in South African universities in the context of
an integrated post-school system. Retrieved from http://www.saide.org.za/sites/default/files/37811_gon535.pdf
OfflineOnline Fully online
Fully offline
Digitally supported
Internet supported
Internet dependent
Campus-based Blended/hybrid Remote
BC
Distance, digitally supported
Distance, fully onlineCampus-based,
fully online
Depending on the ‘mix’ of elements
constituting the delivery, factors
impacting on student success will/may
differ
A

Who defines student success and how is it defined?
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Looking for something/someone to blame…

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In most of our attempts to understand the
complexities of student success, we assume that
students are the ones to blame
• We call them
dropouts
• Failures
• Students-at-risk

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So we implement bridging courses, compulsory support
classes and various other corrective measure to address
their deficits…

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Many of our strategies aim to make them ‘fit’ into our
moulds, our ontologies and epistemologies and if all our
attempts fail…

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… we can always find comfort in the fact that we tried
to make them fit, but maybe higher, distributed learning
was not for them

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How do we understand student success in
online and distributed learning environments?

Source credit: http://timoelliott.com/blog/2013/02/gartnerbi-emea-2013-part-1-analytics-moves-to-the-core.html
Understanding precedes
predictive analytics and
prescriptive analytics

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Understanding student success…
Some examples…

Spady (1970): a sociological model
Spady, W.G. (1970). Dropouts from higher education: An interdisciplinary review and synthesis.
Interchange, 1, 64–85. doi: 10.1007/BF02214313

Tinto(1975): an integration model
Tinto, V. (1975). Dropout from higher education: a theoretical synthesis of recent research. Review of Educational Research, 45:89-125.

Ozga and Sukhnandan (1998): an
explanatory model
Ozga, J. & Sukhnandan, L. (1998). Undergraduate non-completion: developing an explanatory model. Higher Education Quarterly,
52(3): 316-333.

Bean & Eaton (2000): a psychological model
Bean, J.P., & Eaton, S.B. 2000. A psychological model of college student retention, in J.M. Braxton (Ed.) Reworking the student
departure puzzle. Nashville, TN: Vanderbilt University Press, 48-61.

Kember (1989): a distance education
model
Kember, D. (1989). A longitudinal-process model of drop-out from distance education. The Journal of Higher
Education, 60(3): 278-301.

Available at:
http://uir.unisa.ac.za/handle/10500/6035

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How do we make sense of all of this?

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Just when
you think you
see the ,
you don’t…

What do we know… (on the side of students)
• Socioeconomic circumstances
• Primary and secondary school
background
• Educational background of parents
and immediate family
• Geographical distance between
family home and institution
• Subjects and subject marks on
school level
• Proficiency in the language of tuition
• Support networks or lack of
• Peer pressure
• Family and community pressure
• Access to resources
• Mathematics on school level
• Role models or lack of
• Locus of control
• Attribution
• Self awareness
• Self-discipline
• Habits and behaviours
• Parental status
• Health status
• Employment status
• Probability of employment
or career progress
Image retrieved from http://envirolaw.com/wp-content/uploads/black-
student.jpg

What do we know… (on the side of the institution)
• Institutional efficiencies or inefficiencies
• Complexity of curricula
• Curriculum coherence
• Epistemologies and ways of seeing the world
• Assessment strategies
• Tuition periods
• Examination schedules
• Server reliability
• Faculty understanding of ODL
• Faculty expertise
• Institutional culture
• Whether the institution is the choice of last resort for students
• Integration of student support, curriculum, pedagogy and
technology

Students
The
institution
What do we know… (re the influence of macro-
societal factors

What we don’t know
(yet), and possibly
never will know…

Student success is the result of mostly non-linear,
multidimensional, interdependent interactions at
different phases of students’ journey in the nexus
between student, institution and broader societal factors.

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Image detail soccer player: https://static.pexels.com/photos/50713/football-ball-sport-soccer-50713.jpeg
Student persistence and success:
Learning to play (on) the field

Discipline
Online/distributed/blended
Public higher education
Macro-societal factors

Discipline
Some factors to consider:
• What are the rules of admission, of play? What is the history of the
rules? What are the historical, often inter-generational effects of
these rules?
• What is the state of the field? Who/what ‘maintains’ the field?
• What are the competencies required to play on this field?
• How many players are allowed on the field?
• Who are the referees, the guardians of the state of play?
• What are the definitions of success and who determines the
criteria?
• How do we celebrate those who are successful? What are the
narratives that flow from their success? Who maintains and
expands on these narratives?
• What are the stories we tell of those who were not successful?
What are the narratives that flow from their dropout or failure?
Who maintains and expands on these narratives?

An elephant in the
learning analtics room
–
the obligation to act
By Paul Prinsloo (University of South Africa) &
Sharon Slade (Open University, UK)
Image credit:
https://www.flickr.com/photos/lollyman/4941417146
[(habitus) (capital)] + field = practice/agency
(Bourdieu 1984, p. 101)
Bourdieu, P. (1984). Distinction: a social critique of the judgement of taste. Richard Nice (Trans), Cambridge: Harvard University Press.

An elephant in the
learning analytics
room –
Image credit:
Image credit:
http://thesociologicalcinema.tumblr.com/post/142531355075/youre-
playing-monopoly-one-player-is-given-all
The idea of habitus was born
from trying to make sense of
choices we have and make ,
considering our context, our
past and present, our
behaviors, our capital and
dispositions, and our
gendered and raced role(s),
relations and positions in a
particular context/field and
time - as embodied, as
‘structured and structuring
structure’ (Bourdieu, 1994, p. 170)
Bourdieu, P. (1994). In other words: essays towards a reflexive sociology. (M. Adamson, Trans). Cambridge, UK: Polity Press.

An elephant in the
–
Image credit:
(Bourdieu 1984, p. 101)
Bourdieu, P. (1984). Distinction: a social critique of the judgement of taste. Richard Nice (Trans), Cambridge: Harvard University Press.
What are the implications for our understanding of
student (non)persistence and success?
Image credit: https://pixabay.com/en/football-football-goal-2101738/

Subotzky, G., & Prinsloo, P. (2011). Turning the tide: a socio-critical model and framework for
improving student success in open distance learning at the University of South Africa. Distance
Education, 32(2): 177-19.

Processes
Inter & intra-
personal
domains
Modalities:
• Attribution
• Self-efficacy
Processes
Modalities:
• Attribution
• Locus of
control
• Self-efficacy
Domains
Academic
Operational
Social
TRANSFORMED INSTITUTIONAL IDENTITY & ATTRIBUTES
THE STUDENT AS AGENT
IDENTITY, ATTRIBUTES, HABITUS
Success
THE INSTITUTION AS AGENT
SHAPING CONDITIONS: (predictable as well as uncertain)
Choice,
Admission
Learning
activities
Course
success
Gradua-
tion
THE STUDENT WALK
Multiple, mutually constitutive
interactions between student,
institution & networks
F
I
T
FIT
F
I
T
FIT
Employ-
ment/
citizenship
TRANSFORMED STUDENT IDENTITY & ATTRIBUTES
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
Retention/Progression/Positive experience

Some pointers for consideration and
action
Image credit: https://pixabay.com/en/doors-choices-choose-open-decision-1587329/

Image credit: https://pixabay.com/en/question-mark-pile-question-mark-1481601/
Pointer 1: Understanding student success
in the nexus of student, institution and
macro-societal agencies and context

Discipline
Pointer 2: We need to understand the
generative mechanisms in/on these
field(s) and how they shape students’
chances, and how they make
persistence/success (im)possible

An elephant in the
–
(Bourdieu 1984, p. 101)
Pointer 3: Understand what informs and
sustains student agency
Image credit: https://pixabay.com/en/football-football-goal-2101738/

Page credit: http://www.npr.org/sections/ed/2017/01/11/506361845/the-higher-ed-learning-revolution-tracking-each-
students-every-move
2017
Pointer 3: Do we need more data?

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Processes
Inter & intra-
personal
domains
Modalities:
• Attribution
• Self-efficacy
Processes
Modalities:
• Attribution
• Locus of
control
• Self-efficacy
Domains
Academic
Operational
Social
TRANSFORMED INSTITUTIONAL IDENTITY & ATTRIBUTES
THE STUDENT AS AGENT
Success
THE INSTITUTION AS AGENT
Choice,
Admission
Learning
activities
Course
success
Gradua-
tion
THE STUDENT WALK
Multiple, mutually constitutive
interactions between student,
institution & networks
F
I
T
FIT
F
I
T
FIT
Employ-
ment/
citizenship
TRANSFORMED STUDENT IDENTITY & ATTRIBUTES
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
F
I
T
Retention/Progression/Positive experience
Why focus only on learner’s data as if they are
the only actors?

Student Success
Fail
What data do we need to describe, understand, predict and
prescribe the learning journey?
What data do we already have, in which formats, for what
purposes, where are the data stored and governed by who?
What data don’t we have and that we need to describe,
understand, predict and prescribe the learning journey?
What are our assumptions about learning, and data-as-evidence?
What data do students need (also about us) to make better
informed choices and to take ownership of their learning
journey?

Image credit: https://pixabay.com/en/sand-footprint-beach-nature-foot-1009755/
Student data is an
invitation to start a
conversation

Quality
Access Cost
Ethics
Social justice
Pointer 4: Breaking the ‘iron triangle’

Image credit: http://www.goodreads.com/book/show/13587160-to-save-everything-click-here
(Don’t) just add
technology…
Pointer 5: Adding technology

Image credit: https://pixabay.com/en/boy-child-sad-alone-sit-1636731/

Retrieved from http://www.irrodl.org/index.php/irrodl/article/view/149/708
Pointer 6: Getting the mix right

(1)
Humans
perform the
task
(2)
Task is
shared with
algorithms
(3)
Algorithms
perform task:
human
supervision
(4)
Algorithms
perform task:
no human
input
Seeing Yes or No? Yes or No? Yes or No? Yes or No?
Processing Yes or No? Yes or No? Yes or No? Yes or No?
Acting Yes or No? Yes or No? Yes or No? Yes or No?
Learning Yes or No? Yes or No? Yes or No? Yes or No?
Danaher, J. (2015). How might algorithms rule our lives? Mapping the logical space of algocracy. [Web log post]. Retrieved from
http://philosophicaldisquisitions.blogspot.com/2015/06/how-might-algorithms-rule-our-lives.html
Pointer 7: Artificial Intelligence

Paul Prinsloo (Prof)
Research Professor in Open Distance Learning (ODL)
College of Economic and Management Sciences, Office number 3-15, Club 1,
Hazelwood, P O Box 392
Unisa, 0003, Republic of South Africa
T: +27 (0) 12 433 4719 (office)
T: +27 (0) 82 3954 113 (mobile)
prinsp@unisa.ac.za
Skype: paul.prinsloo59
Personal blog: http://opendistanceteachingandlearning.wordpress.com
Twitter profile: @14prinsp
Thank you

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