1. Paul Prinsloo
University of South Africa (Unisa)
@14prinsp
(Teaching) Maths + Online
+ Context = x3
Plenary Address, Master Maths Conference,
Indaba Hotel, Johannesburg, 9 February 2019
Imagecredit:https://pixabay.com/en/pay-digit-number-fill-count-mass-2446670/
2. Acknowledgement
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.
3. Overview of the presentation
1. Setting the context
2. Technology as solution: the hype, the reality, the snake-
oil and the potential
3. The collection, measurement, analysis and use of
student data for informing the effective and ethical use
of technology
4. Technology and the worlds and humans to come
5. Technology and education – between hype and
definitions
6. Six pointers for consideration
7. Concluding remarks
4. Evidence suggests that South African
education, and public Mathematics
education in particular, is mostly
dismal, ineffective, often unethical,
immoral and unjust.
10. Image credit: http://www.goodreads.com/book/show/13587160-to-save-everything-click-here
• Education is NOT broken and even if there
are challenges, technology on its own,
cannot and will not solve all of these
challenges
• We cannot (and should not) underestimate
how technology can enrich education, make
it more effective, more informative, more
fun, and expand our life-worlds and the life-
worlds of our students
• There are some things technology cannot
do
• There are some things that technology
should not be allowed to do
11. • To use technology to duplicate what is
happening in a classroom is a very poor
use of the potential of technology
• Ask rather: What does technology allow
us to do that we cannot do otherwise?
How can technology allow us to explain concepts
better, to create interactive and immersive
experiences, to provide immediate feedback, multiple
opportunities for self-assessment (with feedback), link
to additional, personalised resources and
supplemental learning experiences just-in-time?
Image credit: http://www.goodreads.com/book/show/13587160-to-save-everything-click-here
13. Key to optimising technology in
educational contexts is collecting,
measuring, analysing and using student
data
Imagecredit:http://blog.ceo.ca/wp-content/uploads/2015/02/oil-rigs.jpg
15. We know, take into account and we
measure: age, gender, race, street address
and zip code, occupation, pre-enrolment
educational data, registration data,
engagement data, academic data, library
data, financial aid data, behavioural data,
location data, who-are-in-their-networks-
data, their chances of failing, dropping out,
stopping out…
Image credit: https://pixabay.com/en/side-profile-black-male-student-1440176/
And we use this data to…
Image credit: https://pixabay.com/en/girl-library-education-student-1721436/
17. 1. As students engage with digital resources in online
environments, what data do we collect, for what
purposes?
2. What data do we have/need to create more effective,
more appropriate and more ethical online learning
environments?
3. Do students know what data we have, what data we
collect, who has access to their data for what purposes,
and can they provide input in our analyses and, correct
some of our assumptions and beliefs about their learning?
4. What data do they have/need to learn more effectively,
make more appropriate and ethical decisions in online
learning environments?
18. Technology and the worlds and humans
to come…
Source credit: https://pixabay.com/en/artificial-intelligence-brain-think-3382507/
32. Imagecredit:https://pixabay.com/en/binary-code-man-display-dummy-face-1327512/
Disruptive innovation as weasel word
Image credit: https://www.amazon.com/Watsons-Dictionary-Contemporary-Cliches-Management/dp/1740513215
“Weasel words are words that have been
sucked dry of meaning, they are mere
‘shells of words: words from which life has
gone, facsimiles, frauds, corpses.
Weasel words are the words of the
powerful, the treacherous and the
unfaithful, spies, assassins and thieves.
Bureaucrats and ideologues love them.
Tyrants cannot do without them”
(Watson, 2004, pp. 1-2)
39. The question is therefore not whether we
should use technology, but under what
conditions and for what purposes will online
learning be appropriate, effective, and ethical?
41. Distance education courses
Online courses
A/Synchronous online courses
Online programs
Blended/hybrid courses
[Not-for]Credit courses Online contract training
MOOCs and all its varieties
Imagecredit:https://commons.wikimedia.org/wiki/File:PikiWiki_Israel_35547_Birds_on_a_Wire_2.JPG
So how do we define online
[teaching and learning]?
43. Distance education courses. Distance education courses are those
where no classes are held on campus – all instruction is
conducted at a distance. Distance education courses may use a
variety of delivery methods, such as print-based, video/audio-
conferencing, 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.
Synchronous online courses. Courses where students need to
participate at the same time as an instructor, but at a separate
location other than an institutional campus. These courses may be
delivered by video conferencing, web conferencing, audio
conferencing, etc.
44. Asynchronous courses. Courses where students are not required
to participate in any sessions at the same time as the instructor.
These may be print-based courses, or online courses using a
learning management system, for instance
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. For the
purposes of this questionnaire, we are interested in those courses
where some, but not all, of the face-to-face teaching has been
replaced by online study.
45. Credit courses. These are courses that lead to institutional credits
(degrees, diplomas, etc.).
Online contract training. These are online training programs that
may or may not be for credit recognition but are designed to meet
a particular industry or training need.
MOOCs. These are massive, open, online courses. The key features
are:
• No fee (except possibly for an end of course certificate),
• The courses are open to anyone: there is no requirement for
prior academic qualifications in order to take the course,
• The courses are (mostly) not for credit.
46. The problem with definitions
What is already clear … is that we are trying to
describe a very dynamic and fast changing
phenomenon, and the terminology often
struggles to keep up with the reality of what is
happening.
47. 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 https://www.gov.za/ss/documents/higher-education-act-policy-provision-distance-education-
south-african-universities
48. OfflineOnline Fully online
Fully offline
Digitally supported
Internet supported
Internet dependent
Campus-based Blended/hybrid Remote
A
BC
50. How do we design for effective,
appropriate, ethical online
learning experiences?
1
51. The SECTIONS Model
• Students: what do we know about them? How appropriate
is our design for them?
• Ease of use and reliability: How easy/reliable is the
technology for both students and faculty?
• Costs: what are the cost implications?
[Also think scale – student: facilitator ratio]
• Teaching and learning: what kind of learning is needed?
What design/approach will serve us (teachers and students)
best? What technologies are appropriate? Disciplinary context?
• Interactivity: what [level of] interactivity is required?
• Organisational issues: Support? Barriers? Requirements?
Buy-in?
• Novelty: How new is this technology?
• Speed: what are the affordances of adopting this technology? Frequent
updates to content/software?
54. Quality
Access Cost
• The moment you increase access, what happens to quality
and cost?
• When you commit to quality learning experiences, what
happens to cost and access?
• Aiming to keep our costs as low as possible, how does this
impact on access and quality?
56. Quality
Access Cost
“[D]istance education can achieve any two of the
following: flexible access, quality learning experience
and cost-effectiveness – but not all three at once”
Kanuka & Brooks, 2010, in Power and Gould-Morven, 2011, p. 23)
58. So what happens when ensuring quality costs more and
limits access? What happens when costs are cut or
student numbers increased to ensure economies of
scale? And what happens when students demand high
quality at low/no cost?
Quality
Accessibility Cost-
effectiveness
Faculty
AdministrationStudents
59.
60. Student
TeacherContent
Student - Student
Teacher - TeacherContent - Content
Content - Teacher
Deep and
meaningful
learning
Anderson, T., & Garrison, D. R. (1998). Learning in a networked world: New roles and responsibilties. In Distance Learners in
Higher Education: Institutional responses for quality outcomes. Madison, Wi.: Atwood.
1998
61. How much interaction is
effective/necessary? How much
face-to-face engagement?
3
62. How much interaction is (really) needed for
effective (online*) learning? How does the
amount of interaction impact on the quality
and cost?
2003
65. How do we optimise human-
algorithmic decision-making ?
4
66. (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
Human-algorithm interaction in the collection, analysis and
use of student data
69. How do we use technology to
guide students into the worlds of
Mathematics and Science?
5
70. Four types of transition (Phelan, Davidson & Cao, 1991)
Congruent worlds
A smooth transition
Different worlds
Transition to be managed
Diverse worlds
Hazardous transitions
Discordant worlds
Transition is virtually impossible
Phelan,P.,Davidson,A.,&Cao,H.(1991).Students'multiplewords:
Negotiatingtheboundariesoffamily,peer,andschoolcultures.
AnthropologyandEducationQuarterly,22(2),224-250.
71. Inside outsiders: worlds of
family and friends are
irreconcilable with the world of
higher education, but potentially
compatible with the world of
science
The world of
science
Potential scientists: worlds of
family and friends are congruent
with the worlds of higher
education and science
Other smart kinds: worlds of
family and friends are congruent
with the worlds of higher
education but inconsistent with
the world of science
“I don’t know” students: worlds
of family and friends are
inconsistent with the worlds of
higher education and of science
Outsiders: worlds of family
and friends are discordant
with the worlds of higher
education and of science
Costa,V.B.(1995).Whenscienceis'anotherworld':Relationshipsbetween
worldsoffamily,friends,school,andscience.ScienceEducation,79(3),313
333.
72. A case study from Mathematics
Bohlmann, C. A., & Pretorius, E. J. (2002). Reading skills and mathematics: the practice of higher
education. South African Journal of Higher Education, 16(3), 196-206.
Reading mathematical texts involve both decoding and
comprehension
“Decoding involves those aspects of a reading activity
whereby written signs and symbols are translated into
language. “Comprehension” refers to an overall
understanding process whereby meaning is assigned to the
whole text. The interaction between decoding and
comprehension in skilled readers happen rapidly and
simultaneously” (Bohlmann & Pretorius, 2002, p. 196)
73. Successful decoding does not, however, imply
comprehension. Mathematical texts are also
“hierarchical and cumulative, in the sense that
understanding each statement or proposition is
necessary for understanding subsequent
statements” (Bohlmann & Pretorius, 2002, p. 277)
Their research results indicate “that the weaker
students regularly miss vital clues that aid in
constructing and keeping track of a meaning in a text”
(Bohlmann & Pretorius, 2002, p. 205)
74. If students cannot resolve an anaphor, conditional or
constrastive relations, they will miss the point
Also see:
Pretorius, E. J., & Bohlmann, C. A. (2003). A reading intervention programme for
mathematics students: the practice of higher education. South African Journal of
Higher Education, 17(2), 226-236.
Bohlmann, C. A., & Fletcher, L. (2008). Diagnostic assessment for mathematics in a
distance learning context. South African Journal of Higher Education, 22(3), 556-574.
Feedback, and timely feedback is crucial in student
learning. What data do we have available that they
may miss a crucial point? What will it take to notice
the ‘miss’, respond and assist in them realising what
they (don’t) know
75. • If we know what they miss, what alert systems
can we build in to alert us and them?
• If they don’t know what they don’t know, what
does this mean for admission requirements,
student support, and the costing of student
support?
76. What difference can the effective
use of technology make in making
more students more successful?
6
77. Image credit: https://pixabay.com/en/side-profile-black-male-student-1440176/
Image credit: https://pixabay.com/en/girl-library-education-student-1721436/
Macro-societal factors, e.g. economic, political, social,
technological, environmental and legal factors.
Institutional/lecturer/student inactions, inefficiencies, or
lack of control impacting and shaping students’ behaviour,
chances of failing, dropping out, stopping out…
78. Processes
Inter & intra-
personal
domains
Modalities:
• Attribution
• Locus of control
• 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
IDENTITY, ATTRIBUTES, HABITUS
SHAPING CONDITIONS: (predictable as well as uncertain)
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
(Subotzky & Prinsloo, 2011)
80. 1. Be critical of the hype, the promises, the
assumptions and the beliefs surrounding the use
of technology in education
2. Don’t underestimate the potential of carefully
designed technological solutions to increase the
effectiveness and appropriateness of learning in
online and blended learning environments
3. The collection, measurement, analysis and use of
student data increasingly forms the backbone of
technology use in education. Don’t be evil.
81. 4. Effective online learning is much more than
drop-off-and-go
5. Accept the reality of compromise when it
comes to balancing cost, quality and access
6. Machine Learning and Artificial Intelligence
form the basis for much of new
developments in educational technology. Be
critical.
7. Use technology to ease students into the
world of Mathematics and Science
82. 8. Student success remains a puzzle –
embrace understanding student
learning, be careful in explaining
student learning, be critical and wary
of predicting student learning, and
when you prescribe personalised
learning solutions, consider the cost
of being wrong
83. THANK YOU
Paul Prinsloo (Prof)
Research Professor in Open Distance Learning (ODL)
College of Economic and Management Sciences,
Samuel Pauw Building, Office 5-21, P.O. Box 392
Unisa, 0003, Republic of South Africa
T: +27 (0) 12 433 4719 (office)
prinsp@unisa.ac.za
Skype: paul.prinsloo59
Personal blog:
http://opendistanceteachingandlearning.wordpress.com
Twitter profile: @14prinsp