This document discusses legal and ethical issues related to intellectual property, copyright, fair use, and privacy policies when developing instructional content using modern technologies. It notes that intellectual property includes anything created and is easy to access today, blurring lines around usage. Copyright protects original works upon creation. Fair use allows educational sharing if for educational purposes, considering factors like use purpose, work type, amount used, and market effect. Privacy policies outline required behavior to keep information safe and confidential in today's technological world. Educational institutions must acknowledge these guidelines when using information to create learning content.
This document discusses information literacy, which it defines as the ability to recognize when information is needed and locate, evaluate, and effectively use that information. It outlines the abilities of an information literate individual and discusses ethical use of information according to principles like ownership, privacy, social responsibility, and self-respect. It also discusses plagiarism, summarizing key information literacy skills and both the advantages and disadvantages of information literacy.
Data is the new oil, privacy is the new green - Eye4Travel AmsterdamAurélie Pols
Personal information has become a form of currency to improve the user experience and target the consumer with relevant products. But where's the line between targeting and harassment? In this session you will hear the latest updates regarding privacy policies across Europe.
- Opportunities and Threats: Discuss the latest EU regulations and hear how become a transparent data-driven business
- Avoid excess data: when to collect data and how to use it to offer relevant products to your customer
- Privacy: The biggest barrier to personalised pricing in hospitality and travel?
The document summarizes Hendrik Drachsler's presentation at an NSF expert meeting on big data and privacy in human subjects research. Some key points from Drachsler's presentation include:
- He discussed issues around learning analytics research and how privacy concerns often stop innovation;
- He questioned if big data should be considered the "new truth" and highlighted examples where big data provided inaccurate insights;
- Drachsler advocated for transparency, data security, informed consent and data anonymization to prevent issues like what happened with the inBloom student database project in the US.
Ethics and Privacy in the Application of Learning Analytics (#EP4LA)Hendrik Drachsler
This document summarizes Hendrik Drachsler's presentation on ethics and privacy issues in learning analytics at an NSF expert meeting on Big Data and Privacy in Human Subjects Research. The presentation addressed several key issues:
1) Defining the boundaries of acceptable data collection for learning analytics purposes.
2) Concerns about outsourcing the collection and analysis of student data, including who owns the data.
3) Identifying circumstances where collecting student data would be unacceptable or undesirable.
4) Determining what types of data students should be able to access about themselves.
The presentation called for continued discussion on these issues to develop practical guidelines around privacy and ethics in learning analytics.
This document discusses open data and privacy concerns in the humanities. It outlines that while open data has benefits, some humanities and social science data contains personal details that require protections. Three examples show challenges with medical records, subscriber lists, and student work. The document examines how data can be anonymized but still useful, and questions if IRB rules are too strict. Overall, it argues that fully open or closed access are sometimes false dichotomies, and more nuanced policies are needed to both protect privacy and enable collaborative research.
Open Science and Ethics studies in SLE researchdavinia.hl
Beardsley, M., Santos, P., Hernández-Leo, D., Michos, K. (2019). Ethics in educational technology research: informing participants in data sharing risks. British Journal of Educational Technology, 50(3), 1019-1034, https://doi.org/10.1111/bjet.12781
Beardsley, M., Hernández-Leo, D., Ramirez, R., (2018) Seeking reproducibility: Assessing a multimodal study of the testing effect. Journal of Computer Assisted Learning, 2018, vol. 34, no 4, p. 378-386.
This document discusses legal and ethical issues related to intellectual property, copyright, fair use, and privacy policies when developing instructional content using modern technologies. It notes that intellectual property includes anything created and is easy to access today, blurring lines around usage. Copyright protects original works upon creation. Fair use allows educational sharing if for educational purposes, considering factors like use purpose, work type, amount used, and market effect. Privacy policies outline required behavior to keep information safe and confidential in today's technological world. Educational institutions must acknowledge these guidelines when using information to create learning content.
This document discusses information literacy, which it defines as the ability to recognize when information is needed and locate, evaluate, and effectively use that information. It outlines the abilities of an information literate individual and discusses ethical use of information according to principles like ownership, privacy, social responsibility, and self-respect. It also discusses plagiarism, summarizing key information literacy skills and both the advantages and disadvantages of information literacy.
Data is the new oil, privacy is the new green - Eye4Travel AmsterdamAurélie Pols
Personal information has become a form of currency to improve the user experience and target the consumer with relevant products. But where's the line between targeting and harassment? In this session you will hear the latest updates regarding privacy policies across Europe.
- Opportunities and Threats: Discuss the latest EU regulations and hear how become a transparent data-driven business
- Avoid excess data: when to collect data and how to use it to offer relevant products to your customer
- Privacy: The biggest barrier to personalised pricing in hospitality and travel?
The document summarizes Hendrik Drachsler's presentation at an NSF expert meeting on big data and privacy in human subjects research. Some key points from Drachsler's presentation include:
- He discussed issues around learning analytics research and how privacy concerns often stop innovation;
- He questioned if big data should be considered the "new truth" and highlighted examples where big data provided inaccurate insights;
- Drachsler advocated for transparency, data security, informed consent and data anonymization to prevent issues like what happened with the inBloom student database project in the US.
Ethics and Privacy in the Application of Learning Analytics (#EP4LA)Hendrik Drachsler
This document summarizes Hendrik Drachsler's presentation on ethics and privacy issues in learning analytics at an NSF expert meeting on Big Data and Privacy in Human Subjects Research. The presentation addressed several key issues:
1) Defining the boundaries of acceptable data collection for learning analytics purposes.
2) Concerns about outsourcing the collection and analysis of student data, including who owns the data.
3) Identifying circumstances where collecting student data would be unacceptable or undesirable.
4) Determining what types of data students should be able to access about themselves.
The presentation called for continued discussion on these issues to develop practical guidelines around privacy and ethics in learning analytics.
This document discusses open data and privacy concerns in the humanities. It outlines that while open data has benefits, some humanities and social science data contains personal details that require protections. Three examples show challenges with medical records, subscriber lists, and student work. The document examines how data can be anonymized but still useful, and questions if IRB rules are too strict. Overall, it argues that fully open or closed access are sometimes false dichotomies, and more nuanced policies are needed to both protect privacy and enable collaborative research.
Open Science and Ethics studies in SLE researchdavinia.hl
Beardsley, M., Santos, P., Hernández-Leo, D., Michos, K. (2019). Ethics in educational technology research: informing participants in data sharing risks. British Journal of Educational Technology, 50(3), 1019-1034, https://doi.org/10.1111/bjet.12781
Beardsley, M., Hernández-Leo, D., Ramirez, R., (2018) Seeking reproducibility: Assessing a multimodal study of the testing effect. Journal of Computer Assisted Learning, 2018, vol. 34, no 4, p. 378-386.
What is sensitive data?
Can sensitive data be shared? 23 (research data) Things - Thing 10 Sharing Sensitive Data
Top five tips for sharing sensitive data
Framework for an Ethics of Open EducationRobert Farrow
A presentation on the role of ethics of open education from the Open Education Global 2016 conference held in Krakow, Poland. The full paper can be found in Open Praxis from May 2016 via http://dx.doi.org/10.5944/openpraxis.8.2.291
Louise Bezuidenhout - OpenCon Oxford, 1st Dec 2017Crossref
Louise Bezuidenhout, Institute for Science, Innovation and Society, Oxford:
Projects such as the CODATA-RDA School for Research Data Science highlight the need for building capacity in research data skills around the world. Indeed, without these key skills it is likely that many disciplines and communities will continue to miss out on the benefits of a growing pool of open data resources online. Educating researchers in data skills is thus fundamental in maximizing the benefits of Open Science, but it is also an opportunity to shape the future by educating for responsible data science.
This talk will examine the ethics/Open Science component of the CODATA-RDA school and highlight how the commitment to responsible research underpins all areas of instruction. It will also discuss some of the difficulties of educating for data ethics and responsible practice in a field that is multi-disciplinary and multi-national. Finally, the talk will cover the practice-oriented, modular approach to ethics that has been developed in the CODATA-RDA school to specifically address these challenges.
Information experience design: activating information research in practiceKate Davis
This document provides an overview of an information experience design (IXD) workshop held by Dr. Elham Sayyad Abdi and Dr. Kate Davis. The workshop consisted of an introduction to information experience (IX) and IXD. In the morning, participants learned about key concepts in IX research including information behavior, practice, and literacy. They discussed definitions of information and participated in an activity to understand different forms of information. In the afternoon, participants continued an IXD activity and discussed applying IXD concepts to their own contexts. The workshop aimed to provide tools and approaches for understanding people's experiences with information in various contexts.
Perspectives on the Information Literate UniversitySheila Webber
This was presented by Sheila Webber (Sheffield University Information School) at an internal seminar at the Open University, Milton Keynes, UK, on 29 March 2011. After unpacking the concept of information literacy, I look at contextual aspects of information literacy: the disciplinary perspective, the teaching perspective and the learner perspective. I finish by presenting the picture of the Information Literate University that was developed some years ago by Bill Johnston and me.
Managing and publishing sensitive data in the social sciences - Webinar trans...ARDC
Transcript of the 29th March ANDS webinar.
Slides and recording are available from the ANDS website: http://www.ands.org.au/news-and-events/presentations/2017
Kicking off the INCENTIVE project with an intro to the CS Principles and Char...Margaret Gold
-The Citizen Science Lab at Leiden University
- The core concept of the INCENTIVE project
- The ECSA 10 Principles of Citizen Science
- The ECSA Characteristics of Citizen Science
Elsevier CWTS Open Data Report Presentation at RDA meeting in Barcelona Elsevier
The Open Data report is a result of a year-long, co-conducted study between Elsevier and the Centre for Science and Technology Studies (CWTS), part of Leiden University, the Netherlands. The study is based on a complementary methods approach consisting of a quantitative analysis of bibliometric and publication data, a global survey of 1,200 researchers and three case studies including in-depth interviews with key individuals involved in data collection, analysis and deposition in the fields of soil science, human genetics and digital humanities.
The document discusses methodologies for sharing long-tail data and what has been learned. It notes that unique identifiers (PIDs) are important for identifying entities across contexts. Standards like MINI and common data elements (CDEs) help ensure data is findable, accessible, and reusable. The Neuroscience Information Framework (NIF) aggregates ontologies and searches over 200 data sources to organize information. What we have learned is that data should be in repositories, not personal servers; people are key to these efforts; and resources should be comprehensive and support each other to advance open data sharing.
The document discusses key challenges in the field of learning analytics, including connecting analytics to pedagogy and learning science, developing ethical guidelines, focusing on learner perspectives, and addressing issues of consent, privacy, equality and data ownership. It presents ten reflection questions to prompt thinking on these challenges, such as how pedagogy links to analytics work, the problems analytics aim to solve for learners, important ethical decisions made, and potential changes in response to the challenges. Six core challenges are also summarized: building learning science connections, using diverse data sets, considering learner views, establishing ethics protocols, ensuring consent and safeguarding, and promoting equality and data control.
Presentation at LASI 2016 - Bilbao, Spain
The field of learning analytics (LA) is working on the definition of frameworks that structure the legal and ethical issues that stakeholders have to take into account regarding LA solutions. While current efforts in this direction focus on institutional and development aspects, this paper reflects on small-scale classroom oriented approaches that aim at supporting teachers in their practice. This reflection is based on three studies where we applied our teacher-led learning analytics approach in higher education and primary school contexts. We describe the ethical issues that emerged in these learning scenarios, and discuss them according to three dimensions: the overall learning analytics approach, the particular solution to learning analytics adopted, and the educational contexts where the analytics are applied.
The document discusses the human-centered design approach to data as a service. It emphasizes engaging with communities to understand local contexts and involving stakeholders throughout the research process. The presentation outlines steps for responsible research, including obtaining ethics approval, engaging gatekeepers, sensitizing researchers to cultural practices, and documenting engagement activities. It also discusses challenges around community research fatigue and ensuring information meets recipient needs in terms of being the right information, at the right time, for the right purpose.
Learning Analytics – Ethical questions and dilemmasTore Hoel
Workshop presentation using the Potter Box model of ethical reasoning to discuss concerns and dilemmas of Learning analytics - Open Discovery Space and Learning Analytics Community Exchange projects #laceproject #ods_eu
1) The document discusses three paradigmatic positions that institutions may take regarding ethics and privacy in learning analytics: proceed with caution and respect existing policies, proceed with caution while still trying to be respectful, or adopt a data-driven approach and adapt policies accordingly.
2) Technical infrastructure is a major concern, as it can constrain or determine an institution's data policies. Systems developed by commercial platforms may not prioritize privacy and individual control.
3) The discussion activity prompts reflection on an institution's current position, any conflicts between stakeholder views, the technical systems that influence policy, and open questions about technology and privacy.
This document discusses the ethics of conducting internet research. It begins with an introduction to ethical frameworks like Kant versus Mill and discusses challenges like ensuring anonymity, informed consent, and avoiding harm when directly interacting with individuals online. It also addresses analyzing interactions in virtual environments and issues around privacy, identity disclosure, and data capture. Big data research ethics are covered, including issues of total knowledge, manipulation, and the difference between academic and commercial contexts. The document emphasizes the importance of sensitivity to context, not overburdening participants, taking responsibility, and writing transparently about ethical decision making in internet research.
This document discusses challenges for the higher education sector in implementing learning analytics at scale. It begins with an overview of learning analytics and its potential uses. Key challenges mentioned include developing a consensus approach for Norway, addressing privacy issues, establishing infrastructure for data handling and analysis, and developing standards and competencies. The document calls for establishing several resources to help institutions, including tools for assessing readiness, developing strategies, conducting research, and managing data and analytics processes according to privacy standards.
Smart Learning Environments - a framework for standardisation?Tore Hoel
1) Smart learning environments (SLEs) could provide a framework for standardizing learning technologies, but the term "smart" is problematic without a clear definition.
2) Existing SLE frameworks from researchers like Koper could structure standards work but may not reflect market needs.
3) Taking a pragmatic approach by developing smaller, self-contained standards informed by—but not dictated by—SLE frameworks may be more effective than large, multipart standards.
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What is sensitive data?
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Framework for an Ethics of Open EducationRobert Farrow
A presentation on the role of ethics of open education from the Open Education Global 2016 conference held in Krakow, Poland. The full paper can be found in Open Praxis from May 2016 via http://dx.doi.org/10.5944/openpraxis.8.2.291
Louise Bezuidenhout - OpenCon Oxford, 1st Dec 2017Crossref
Louise Bezuidenhout, Institute for Science, Innovation and Society, Oxford:
Projects such as the CODATA-RDA School for Research Data Science highlight the need for building capacity in research data skills around the world. Indeed, without these key skills it is likely that many disciplines and communities will continue to miss out on the benefits of a growing pool of open data resources online. Educating researchers in data skills is thus fundamental in maximizing the benefits of Open Science, but it is also an opportunity to shape the future by educating for responsible data science.
This talk will examine the ethics/Open Science component of the CODATA-RDA school and highlight how the commitment to responsible research underpins all areas of instruction. It will also discuss some of the difficulties of educating for data ethics and responsible practice in a field that is multi-disciplinary and multi-national. Finally, the talk will cover the practice-oriented, modular approach to ethics that has been developed in the CODATA-RDA school to specifically address these challenges.
Information experience design: activating information research in practiceKate Davis
This document provides an overview of an information experience design (IXD) workshop held by Dr. Elham Sayyad Abdi and Dr. Kate Davis. The workshop consisted of an introduction to information experience (IX) and IXD. In the morning, participants learned about key concepts in IX research including information behavior, practice, and literacy. They discussed definitions of information and participated in an activity to understand different forms of information. In the afternoon, participants continued an IXD activity and discussed applying IXD concepts to their own contexts. The workshop aimed to provide tools and approaches for understanding people's experiences with information in various contexts.
Perspectives on the Information Literate UniversitySheila Webber
This was presented by Sheila Webber (Sheffield University Information School) at an internal seminar at the Open University, Milton Keynes, UK, on 29 March 2011. After unpacking the concept of information literacy, I look at contextual aspects of information literacy: the disciplinary perspective, the teaching perspective and the learner perspective. I finish by presenting the picture of the Information Literate University that was developed some years ago by Bill Johnston and me.
Managing and publishing sensitive data in the social sciences - Webinar trans...ARDC
Transcript of the 29th March ANDS webinar.
Slides and recording are available from the ANDS website: http://www.ands.org.au/news-and-events/presentations/2017
Kicking off the INCENTIVE project with an intro to the CS Principles and Char...Margaret Gold
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- The core concept of the INCENTIVE project
- The ECSA 10 Principles of Citizen Science
- The ECSA Characteristics of Citizen Science
Elsevier CWTS Open Data Report Presentation at RDA meeting in Barcelona Elsevier
The Open Data report is a result of a year-long, co-conducted study between Elsevier and the Centre for Science and Technology Studies (CWTS), part of Leiden University, the Netherlands. The study is based on a complementary methods approach consisting of a quantitative analysis of bibliometric and publication data, a global survey of 1,200 researchers and three case studies including in-depth interviews with key individuals involved in data collection, analysis and deposition in the fields of soil science, human genetics and digital humanities.
The document discusses methodologies for sharing long-tail data and what has been learned. It notes that unique identifiers (PIDs) are important for identifying entities across contexts. Standards like MINI and common data elements (CDEs) help ensure data is findable, accessible, and reusable. The Neuroscience Information Framework (NIF) aggregates ontologies and searches over 200 data sources to organize information. What we have learned is that data should be in repositories, not personal servers; people are key to these efforts; and resources should be comprehensive and support each other to advance open data sharing.
The document discusses key challenges in the field of learning analytics, including connecting analytics to pedagogy and learning science, developing ethical guidelines, focusing on learner perspectives, and addressing issues of consent, privacy, equality and data ownership. It presents ten reflection questions to prompt thinking on these challenges, such as how pedagogy links to analytics work, the problems analytics aim to solve for learners, important ethical decisions made, and potential changes in response to the challenges. Six core challenges are also summarized: building learning science connections, using diverse data sets, considering learner views, establishing ethics protocols, ensuring consent and safeguarding, and promoting equality and data control.
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The field of learning analytics (LA) is working on the definition of frameworks that structure the legal and ethical issues that stakeholders have to take into account regarding LA solutions. While current efforts in this direction focus on institutional and development aspects, this paper reflects on small-scale classroom oriented approaches that aim at supporting teachers in their practice. This reflection is based on three studies where we applied our teacher-led learning analytics approach in higher education and primary school contexts. We describe the ethical issues that emerged in these learning scenarios, and discuss them according to three dimensions: the overall learning analytics approach, the particular solution to learning analytics adopted, and the educational contexts where the analytics are applied.
The document discusses the human-centered design approach to data as a service. It emphasizes engaging with communities to understand local contexts and involving stakeholders throughout the research process. The presentation outlines steps for responsible research, including obtaining ethics approval, engaging gatekeepers, sensitizing researchers to cultural practices, and documenting engagement activities. It also discusses challenges around community research fatigue and ensuring information meets recipient needs in terms of being the right information, at the right time, for the right purpose.
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1) The document discusses three paradigmatic positions that institutions may take regarding ethics and privacy in learning analytics: proceed with caution and respect existing policies, proceed with caution while still trying to be respectful, or adopt a data-driven approach and adapt policies accordingly.
2) Technical infrastructure is a major concern, as it can constrain or determine an institution's data policies. Systems developed by commercial platforms may not prioritize privacy and individual control.
3) The discussion activity prompts reflection on an institution's current position, any conflicts between stakeholder views, the technical systems that influence policy, and open questions about technology and privacy.
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Data protection and privacy framework in the design of learning analytics sys...Tore Hoel
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2) It notes that learning analytics could be considered unlawful if students do not have control over and consent to how their data is used.
3) The presentation raises important questions about data ownership, student consent, and limiting data collection and use to only what is necessary for educational purposes.
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Tore Hoel presented on the need for open architectures and interoperability standards for learning analytics. Key challenges include a lack of trust, different data schemas and sources being used, and privacy and data ownership issues. Standards are needed for activity streams, vocabularies, storage designs, and algorithms. While initiatives exist, there is no single European leader coordinating standardization efforts for learning analytics.
Learning Analytics – Opportunities for ISO/IEC JTC 1/SC36 standardisationTore Hoel
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Learning Analytics - Vision of the FutureTore Hoel
The document summarizes a presentation about the future of learning analytics given by Tore Hoel. Some key points:
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- Seven visions of the future of learning analytics in 2025 are presented, including scenarios where analytics are used for educational management, support self-directed learning, or are rarely used due to privacy and data issues.
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Workshop on Learning Analytics @ EDEN15 in Barcelona - June 2015Tore Hoel
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
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9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
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occur natural.
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Strategies for Dealing with Privacy in the context of Learning Analytics
1. Strategies
for
Dealing
with
Privacy
in
the
context
of
LA
Tore
Hoel
Oslo
and
Akershus
University
College
of
Applied
Sciences
Norway
September
2014
2. What
is
the
problem
with
Privacy?
2
Medical
Privacy
Various
methods
have
been
used
to
protect
patient's
privacy.
This
1822
drawing
by
Jacques-‐Pierre
Maygnier
shows
a
"compromise"
procedure,
in
which
the
physician
is
kneeling
before
the
woman
but
cannot
see
her
genitalia.
(Wikipedia)
3. Privacy,
Interoperability
&
Data
Sharing
"Silos,
Acatlán,
Hidalgo,
México,
2013-‐10-‐11,
DD
03"
by
Diego
Delso
-‐
Own
work.
Licensed
under
Creative
Commons
Attribution-‐Share
Alike
3.0
via
Wikimedia
Commons3
4. Control
or
Limitations?
Privacy
is
out
of
scope
for
LA
–
it
is
dealt
with
by
basic
infrastructure
or
front-‐end
applications
"Silos,
Acatlán,
Hidalgo,
México,
2013-‐10-‐11,
DD
03"
by
Diego
Delso
-‐
Own
work.
Licensed
under
Creative
Commons
Attribution-‐Share
Alike
3.0
via
Wikimedia
Commons4
I
want
control
over
my
own
data!
I
want
to
grant
limited
access
to
your
data!
5. Privacy
defined…
• Privacy
is
not
simply
an
absence
of
information
about
us
in
the
minds
of
others;
rather
it
is
the
control
we
have
over
information
about
ourselves.
-‐-‐Charles
Fried
• Privacy
is
a
limitation
of
others’
access
to
an
individual
through
information,
attention,
or
physical
proximity.
-‐-‐Ruth
Gavison
5
Or…
6. Privacy
as
Contextual
Integrity
• Norms
of
Appropriateness
• Norms
of
Distribution
(Flow,
transfer)
• S
shares
information
with
R
at
S’s
discretion
• R
requires
S
to
share
information
• R
may
freely
share
information
about
S
• R
may
not
share
information
about
S
with
anyone
• R
may
share
information
about
S
under
specified
constraints
• Information
flow
is/is
not
reciprocal
• etc.
6 Source:
Helen
Nissenbaum
7. Integrity
–
respected
or
violated
Contextual
Integrity,
is
respected
when
norms
of
appropriateness
and
distribution
are
respected;
it
is
violated
when
any
of
the
norms
are
infringed.
7
8. ‘Contexts’
is
the
strategic
word
–
so
what?
• Contexts
are
Structured
Social
Settings
(“Institutions”)
• Characterized
by
roles,
relationships,
power
structures,
canonical
activities,
strategies,
norms
(rules),
enforcement
mechanisms,
and
internal
values
(goals,
ends,
purposes)
(Nissenbaum)
8
Health-‐care
Education
Politics
Religious
observance
9. More
about
‘contexts’…
9
• Evolve
over
time
in
cultures
and
societies,
subject
to
historical,
cultural,
geographic
contingencies
• May
be
nested,
overlap,
conflict
• May
be
more
or
less
explicit,
formalized,
institutionalized
• May
be
more
or
less
“complete”
10. Education
as
context(s)
• Learning,
Education
and
Training
• Levels
–
K12,
HE,
LLL
• Types
of
learning
• Informal
vs
formal
learning
• Pedagogies
• Learning
styles
10
11. Privacy
a
concern
for
LA
research
community?
• Not
really,
it
seems…
• LAK14
papers:
12
of
47
contained
word
‘privacy’
• we
anonymised
data
before
analysis
• barrier
&
restriction
• users
are
«concerned»
-‐
privacy
as
a
risk
• «Learners
need
to
be
convinced
that
they
are
reliable
and
will
improve
their
learning
without
intruding
into
their
privacy»
(Ferguson,
2014)
• «Many
myths
surrounding
the
use
of
data,
privacy
infringement
and
ownership
of
data
need
to
be
dispelled
and
can
be
properly
modulated
once
the
values
of
learning
analytics
are
realized»
(Arnold,
2014).
11
12. LACE
LA
Quality
Indicator
study
12
Data
Privacy
–
a
major
area
of
concern (Scheffel
et
al.,
in
press)
13. What
are
the
optimal
contexts
for
discussing
Privacy
in
Education?
13
14. Privacy
by
Design
14
• «The
principles
of
data
protection
by
design
and
data
protection
by
default»
(European
Commisson,
2012)
• 7
Foundational
Principles
by
PbD
• Proactive
not
Reactive;
Preventative
not
Remedial
• Privacy
as
the
Default
Setting
• Privacy
Embedded
into
Design
• Full
Functionality
-‐
Positive-‐Sum,
not
Zero-‐Sum
• End-‐to-‐End
Security
-‐
Full
Lifecycle
Protection
• Visibility
and
Transparency
-‐
Keep
it
Open
• Respect
for
User
Privacy
-‐
Keep
it
User-‐Centric
15. Strategies
for
design
of
interoperable
LA
applications
• Give
Privacy
priority
–
Privacy
is
in
scope!
• Follow
Privacy
by
Design
principles
• Be
aware
of
contexts
• Focus
on
well
defined
and
autonomous
contexts
first
• When
multiple
contexts
are
involved,
go
for
lightweight,
low-‐
ambitious
solutions
15
16. Questions
• What
are
the
relevant
educational
contexts
from
a
Privacy
perspective?
• What
contexts
generate
the
most
interesting
data
from
a
LA
perspective?
• If
Social
Media
contexts
are
relevant
for
learning
–
how
do
we
avoid
contextual
integrity
infringements?
• How
are
responsibilities
balanced
between
learner
and
institution
when
it
comes
to
the
different
contexts
of
Learning,
Education
and
Training?
16
17. www.laceproject.eu
@laceproject
“Strategies
for
Dealing
with
Privacy
in
the
context
of
LA”
by
Tore
Hoel,
Oslo
and
Akershus
University
College
of
Applied
Sciences,
was
presented
at
EC-‐TEL
workshop,
Graz,
Austria,
on
16
September
2014.
!
tore.hoel@hioa.no
@tore
This
work
was
undertaken
as
part
of
the
LACE
Project,
supported
by
the
European
Commission
Seventh
Framework
Programme,
grant
619424.
These
slides
are
provided
under
the
Creative
Commons
Attribution
Licence:
http://creativecommons.org/
licenses/by/4.0/.
Some
images
used
may
have
different
licence
terms.
17