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Orchestration and
Learning Analytics
for Educational Innovation
Luis P. Prieto
Venia Legendi for a Senior Research Fellow position
Tallinn University, 30 May 2016
1. Orchestration and Learning
Analytics: A lecture
2. A vision to apply them in
CEITER (and beyond)
2
1. Orchestration and
Learning Analytics
3
https://goo.gl/qjJb4W
But first, a question…
4
Orchestration is…
“the process of
productively coordinating
supportive interventions
across multiple learning
activities occurring at
multiple social levels”
(Dillenbourg, Järvelä & Fischer, 2009)
5
why does orchestration
matter?
6
Lack of educational technology
adoption in authentic settings
• … in learning design (Mor, Craft & Hernández-Leo, 2013)
• … in collaborative learning (Looi, So, Toh & Chen, 2011)
• … in teacher inquiry (Emin-Martínez et al., 2014)
• …
7
8
9
How can orchestration
be used?
10
Application to edutech design
• GLUE!-PS: From an open architecture to solve the
fragmentation of learning design authoring tools…
• … to a tool to support orchestration of existing
VLEs and external tools (e.g., runtime changes, etc.)
(Prieto et al., 2014) 11
What does orchestration entail?
The ‘5+3 Aspects’ framework
(Prieto, Holenko-Dlab, Gutiérrez, Abdulwahed & Balid, 2011) 12
Application to edutech evaluation
• Does GLUEPS-AR support the orchestration of
mobile AR-based learning activities?
(Muñoz-Cristóbal et al., 2015)
13
… but technology alone
is not enough to
guarantee adoption
14
Modelling teacher orchestration:
observational studies
(Prieto et al., 2011)
15
Applications to teacher
professional development
Observational
studies
Successful
routines/
practices/
patterns
Professional
development
workshops
(Prieto et al., 2013)
16
Modelling teacher orchestration:
diving deeper with eye-tracking
17
Modelling teacher orchestration:
diving deeper with eye-tracking
• Study teacher cognitive
(orchestration) load
• Class-level interactions are
higher load
• Reading faces is higher load
• Novice teachers have clearer
load trends than experts
• …
(Prieto, Wen, Caballero, Sharma & Dillenbourg, 2014)
(Prieto, Sharma, Wen & Dillenbourg, 2015)
(Prieto, Sharma & Dillenbourg, 2015)
18
Learning Analytics
• Main goal: Aiding educators in understanding and
improving teaching and learning processes
• Main difference with Educational Data Mining
(EDM): human in the loop
• Aimed at interventions/supportive actions
• Cycle of data gathering, analysis, feedback/visualization
• Hence, LA can be seen as a very useful tool for
orchestration
• Awareness/Assessment aspect in ‘5+3’ framework
(Siemens & Long, 2011)
19
(Clow, 2012)
Orchestration + LA =
Teaching Analytics
• First attempt at automating the
observational modelling of orchestration
graphs using multimodal analysis
• Audio, video, eyetracking, accelerometers, EEG
• Exploration of basic, general-purpose
features and algorithms
(Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016) 20
(Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016)
21
Orchestration + Learning Analytics
= Teaching Analytics
• First attempt at automating the observational
modelling of orchestration graphs using
multimodal analysis
• Audio, video, eyetracking, accelerometers, EEG
• Exploration of basic, general-purpose features and
algorithms
• Results:
• Predicting teacher activity accuracy: 65%
• Predicting social plane accuracy: 90%
• Audio-video channels most useful
• Random forest and GBM as best algorithms
(Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016) 22
2. A vision to apply them
in CEITER (and beyond)
23
https://goo.gl/LeNN7F
But, just before we finish the lecture…
24
Previously, on this
Venia Legendi…
• Orchestration as a (complex) metaphor for
teaching practice
• Focus on an innovation’s potential for adoption
within ecosystem of authentic educational setting
• Applications to educational technologies as well as
the analysis of (adoption) practice
• Learning Analytics (LA)
• “Orchestration-flavored” take on EDM?
• Multimodal LA to model what happens outside the
box (face-to-face)
25
Image from https://www.flickr.com/photos/65092514@N08/18679295525
Have orchestration and
learning analytics research
solved adoption?
Well, not quite…
26
An example orchestration/LA
research project
• Prolearning: simple app to foster PD conversations
based on everyday data gathering by teachers
• Students are asked simple questions about their
experience in terms of school-emphasized practices
& teachers have to predict student response
• http://prolearning.realto.ch
• Successes:
• Teachers used it in ~70% of all their lessons for 2 weeks
• Recorded evidence of changes in student experience
• Takes 2 mins: “I can’t see how it can be more efficient”
27
What didn’t work
Teacher interviews:
“… any time you’re teaching
there is a hundred variables
that you have to account
for”
“[I would use it] if you can
demonstrate that these data
are reliable…”
28
Unsolved challenges
1. Trust, privacy, agency and other ethical factors
• Traditional top-down innovations quickly get subverted
2. The quest for added value
• Hard: Evidence of benefits for student learning
• Soft: Help with existing “chores”, social value…
3. Still does not scale well!
• Measure blended learning, but with ecological validity?
• Slow: cycles of analysis and reflection are loooooong
• Can we do better than final course assessment?
• Fail to create new practices that go with the technology
• Routines are how we deal with our complex environments
29
The CEITER project
• From project description:
• Teaching 21st century skills
• Innovative methods & learning environments  tailored to
learner’s development/needs/capabilities
• Improving the research staff capacity & new generation of
researchers
• Use Learning Analytics
• From Tobias’s talk (06.04.2016):
• Tech/Tools cannot be separated from teaching and learning
practices
• Educational innovation is taken up at different social entities
• Multiple levels of analysis (institutional, PD, learner…)
30
Can we change Estonian
education from the
“ivory tower”?
Probably not…
31
Fresh perspective
on Learning
Analytics
Ecosystem of
tools for evidence-
based orchestration
CEITER
Agency &
Ethics
Clear added
value
Adoption
& scale1 2 3
Blended LA in
distributed
LEs + ‘just
enough’
multimodal LA
Focus on
assessing
learning
Focus on
everyday
evidence
Capture
successful
practices
Teacher
training and
community
of practice
Open, privacy-
conscious
architecture +
specific tools
Integrate
existing
tools and
practices
Lightweight
assessment
techniques
Evidence-
based
training
Orchestr
ation-
aware
tools
32
33
CEITER’s
virtuous
cycle
Personal
practice
analysis
tools
Facilitate
certain
evaluation
“chores”
Evidence on
tool/practice
effectivenessEffective
practices
fed back
to CoP
Ecologically
-valid
educational
research
Evidence-
based policy
making to
reward/support
practices
Learning
Analytics’
vicious
cycle
Modus operandi
• Design-based research, mixed methods,
participatory…
• Lean startup model: start qualitative, slowly build
quantitative indicators, minimal prototypes
• Cross-functional teams/projects
• Eat your own dog food! 
• Promote international exchanges (students, faculty)
• Focus on EduTech entrepreneurship to attract
students & researchers
34
A path for (part of) CEITER
35
Phase 1
1st LA
prototypes
Application
in PD
(teachers &
researchers)CEITER as
a 1st
evidence-
based CoP
Basic practice
capture
Phase 2
1st
orchestrati
on tools
Application
in teacher
education
Pre-service
teachers
eb-CoP
Focused
capture, multi-
classroom
To phase 3
Why me?
Contributions to wide variety of
orchestration-related research
communities
• From CSCL to LD to HCI to LA…
Experience in international
projects & collaboration
Quanti & quali methods
Used to Enjoys inter-disciplinary
work
Motivated by innovation
practice, teacher PD, …
FP
6
FP
7LLP
36
… but not only me!
• Other CEITER team members:
• Existing expertise in lifelong & workplace learning
• Infrastructure expert to communicate different data
sources and databases
• Psychology profile: to determine the “building blocks” of
learning and how to (micro-)assess them
• Pedagogical approach profile: to model existing
practices/tools and propose new ones
• Other researchers at U. Tallinn (or T.U. Tallinn)
• Partnerships with local HCI, Signal processing, Machine
learning, Sensors, (Estonian) voice recognition… experts
37
… but not only me! (II)
• My existing network of relevant contacts, e.g.:
• Orchestration: P. Dillenbourg (CH), P. Tchounikine (FR)
• Pedagogies, e.g., CSCL: Y. Dimitriadis (ES), D. Persico (IT)
• Multimodal Learning Analytics: X. Ochoa (EC), S.
D’Mello (US)
• Large-scale school innovation: C.K. Looi (SNG), J.
Roschelle (US)
• U. Tallinn’s own network of national & international
contacts
• Incl. Estonian teacher/school networks, policy-makers
38
Beyond CEITER
• This vision can be too ambitious for CEITER itself
• Once we have initial results, use them to “pitch”
consortium and proposals
• EU calls:
• Evidence-based policy aspect: SwafS-21-2017
• Explore prototypes’ market potential: SMEInst-12-2016-2017
• If things go well, ERC-STG-2018/2019…
• Other funding for non-EU countries, e.g.:
• US: Partnerships for International Research and Education (NSF
PIRE)
• Singapore (parallel for systemic change): advisors/expert for
national project (visit planned 2017)
39
This is just a modular vision…
CEITERBlended LA in
distributed
LEs + ‘just
enough’
multimodal LA
Teacher
training and
community
of practice
Open, privacy-
conscious
architecture +
specific tools
Lightweight
assessment
techniques
40
… within an ecosystem of interests
Blended LA in
distributed
LEs + ‘just
enough’
multimodal LA
Teacher
training and
community
of practice
Open, privacy-
conscious
architecture +
specific tools
Lightweight
assessment
techniques
Agile &
entrepreneurship
methods in
research
Scientific writing
& communication
support
Researcher
communities
of practice
MOOCs
Machine
learning
Learning
design
Creative
writing
Tangible
& paper
UIs
Data
literacy
Data
science
CSCL
Dissemination
to the public
41
Thank you! Questions?
Email: luis.prieto@epfl.ch
Website: https://people.epfl.ch/luis.prieto
LinkedIn: https://www.linkedin.com/in/lprisan
Google Scholar:
https://scholar.google.ch/citations?user=ySpnj0MAAAAJ
42

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2016-05-30 Venia Legendi (CEITER): Luis Pablo Prieto

  • 1. Orchestration and Learning Analytics for Educational Innovation Luis P. Prieto Venia Legendi for a Senior Research Fellow position Tallinn University, 30 May 2016
  • 2. 1. Orchestration and Learning Analytics: A lecture 2. A vision to apply them in CEITER (and beyond) 2
  • 5. Orchestration is… “the process of productively coordinating supportive interventions across multiple learning activities occurring at multiple social levels” (Dillenbourg, Järvelä & Fischer, 2009) 5
  • 7. Lack of educational technology adoption in authentic settings • … in learning design (Mor, Craft & Hernández-Leo, 2013) • … in collaborative learning (Looi, So, Toh & Chen, 2011) • … in teacher inquiry (Emin-Martínez et al., 2014) • … 7
  • 8. 8
  • 9. 9
  • 11. Application to edutech design • GLUE!-PS: From an open architecture to solve the fragmentation of learning design authoring tools… • … to a tool to support orchestration of existing VLEs and external tools (e.g., runtime changes, etc.) (Prieto et al., 2014) 11
  • 12. What does orchestration entail? The ‘5+3 Aspects’ framework (Prieto, Holenko-Dlab, Gutiérrez, Abdulwahed & Balid, 2011) 12
  • 13. Application to edutech evaluation • Does GLUEPS-AR support the orchestration of mobile AR-based learning activities? (Muñoz-Cristóbal et al., 2015) 13
  • 14. … but technology alone is not enough to guarantee adoption 14
  • 15. Modelling teacher orchestration: observational studies (Prieto et al., 2011) 15
  • 16. Applications to teacher professional development Observational studies Successful routines/ practices/ patterns Professional development workshops (Prieto et al., 2013) 16
  • 17. Modelling teacher orchestration: diving deeper with eye-tracking 17
  • 18. Modelling teacher orchestration: diving deeper with eye-tracking • Study teacher cognitive (orchestration) load • Class-level interactions are higher load • Reading faces is higher load • Novice teachers have clearer load trends than experts • … (Prieto, Wen, Caballero, Sharma & Dillenbourg, 2014) (Prieto, Sharma, Wen & Dillenbourg, 2015) (Prieto, Sharma & Dillenbourg, 2015) 18
  • 19. Learning Analytics • Main goal: Aiding educators in understanding and improving teaching and learning processes • Main difference with Educational Data Mining (EDM): human in the loop • Aimed at interventions/supportive actions • Cycle of data gathering, analysis, feedback/visualization • Hence, LA can be seen as a very useful tool for orchestration • Awareness/Assessment aspect in ‘5+3’ framework (Siemens & Long, 2011) 19 (Clow, 2012)
  • 20. Orchestration + LA = Teaching Analytics • First attempt at automating the observational modelling of orchestration graphs using multimodal analysis • Audio, video, eyetracking, accelerometers, EEG • Exploration of basic, general-purpose features and algorithms (Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016) 20
  • 21. (Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016) 21
  • 22. Orchestration + Learning Analytics = Teaching Analytics • First attempt at automating the observational modelling of orchestration graphs using multimodal analysis • Audio, video, eyetracking, accelerometers, EEG • Exploration of basic, general-purpose features and algorithms • Results: • Predicting teacher activity accuracy: 65% • Predicting social plane accuracy: 90% • Audio-video channels most useful • Random forest and GBM as best algorithms (Prieto, Sharma, Rodríguez-Triana & Dillenbourg, 2016) 22
  • 23. 2. A vision to apply them in CEITER (and beyond) 23
  • 24. https://goo.gl/LeNN7F But, just before we finish the lecture… 24
  • 25. Previously, on this Venia Legendi… • Orchestration as a (complex) metaphor for teaching practice • Focus on an innovation’s potential for adoption within ecosystem of authentic educational setting • Applications to educational technologies as well as the analysis of (adoption) practice • Learning Analytics (LA) • “Orchestration-flavored” take on EDM? • Multimodal LA to model what happens outside the box (face-to-face) 25 Image from https://www.flickr.com/photos/65092514@N08/18679295525
  • 26. Have orchestration and learning analytics research solved adoption? Well, not quite… 26
  • 27. An example orchestration/LA research project • Prolearning: simple app to foster PD conversations based on everyday data gathering by teachers • Students are asked simple questions about their experience in terms of school-emphasized practices & teachers have to predict student response • http://prolearning.realto.ch • Successes: • Teachers used it in ~70% of all their lessons for 2 weeks • Recorded evidence of changes in student experience • Takes 2 mins: “I can’t see how it can be more efficient” 27
  • 28. What didn’t work Teacher interviews: “… any time you’re teaching there is a hundred variables that you have to account for” “[I would use it] if you can demonstrate that these data are reliable…” 28
  • 29. Unsolved challenges 1. Trust, privacy, agency and other ethical factors • Traditional top-down innovations quickly get subverted 2. The quest for added value • Hard: Evidence of benefits for student learning • Soft: Help with existing “chores”, social value… 3. Still does not scale well! • Measure blended learning, but with ecological validity? • Slow: cycles of analysis and reflection are loooooong • Can we do better than final course assessment? • Fail to create new practices that go with the technology • Routines are how we deal with our complex environments 29
  • 30. The CEITER project • From project description: • Teaching 21st century skills • Innovative methods & learning environments  tailored to learner’s development/needs/capabilities • Improving the research staff capacity & new generation of researchers • Use Learning Analytics • From Tobias’s talk (06.04.2016): • Tech/Tools cannot be separated from teaching and learning practices • Educational innovation is taken up at different social entities • Multiple levels of analysis (institutional, PD, learner…) 30
  • 31. Can we change Estonian education from the “ivory tower”? Probably not… 31
  • 32. Fresh perspective on Learning Analytics Ecosystem of tools for evidence- based orchestration CEITER Agency & Ethics Clear added value Adoption & scale1 2 3 Blended LA in distributed LEs + ‘just enough’ multimodal LA Focus on assessing learning Focus on everyday evidence Capture successful practices Teacher training and community of practice Open, privacy- conscious architecture + specific tools Integrate existing tools and practices Lightweight assessment techniques Evidence- based training Orchestr ation- aware tools 32
  • 33. 33 CEITER’s virtuous cycle Personal practice analysis tools Facilitate certain evaluation “chores” Evidence on tool/practice effectivenessEffective practices fed back to CoP Ecologically -valid educational research Evidence- based policy making to reward/support practices Learning Analytics’ vicious cycle
  • 34. Modus operandi • Design-based research, mixed methods, participatory… • Lean startup model: start qualitative, slowly build quantitative indicators, minimal prototypes • Cross-functional teams/projects • Eat your own dog food!  • Promote international exchanges (students, faculty) • Focus on EduTech entrepreneurship to attract students & researchers 34
  • 35. A path for (part of) CEITER 35 Phase 1 1st LA prototypes Application in PD (teachers & researchers)CEITER as a 1st evidence- based CoP Basic practice capture Phase 2 1st orchestrati on tools Application in teacher education Pre-service teachers eb-CoP Focused capture, multi- classroom To phase 3
  • 36. Why me? Contributions to wide variety of orchestration-related research communities • From CSCL to LD to HCI to LA… Experience in international projects & collaboration Quanti & quali methods Used to Enjoys inter-disciplinary work Motivated by innovation practice, teacher PD, … FP 6 FP 7LLP 36
  • 37. … but not only me! • Other CEITER team members: • Existing expertise in lifelong & workplace learning • Infrastructure expert to communicate different data sources and databases • Psychology profile: to determine the “building blocks” of learning and how to (micro-)assess them • Pedagogical approach profile: to model existing practices/tools and propose new ones • Other researchers at U. Tallinn (or T.U. Tallinn) • Partnerships with local HCI, Signal processing, Machine learning, Sensors, (Estonian) voice recognition… experts 37
  • 38. … but not only me! (II) • My existing network of relevant contacts, e.g.: • Orchestration: P. Dillenbourg (CH), P. Tchounikine (FR) • Pedagogies, e.g., CSCL: Y. Dimitriadis (ES), D. Persico (IT) • Multimodal Learning Analytics: X. Ochoa (EC), S. D’Mello (US) • Large-scale school innovation: C.K. Looi (SNG), J. Roschelle (US) • U. Tallinn’s own network of national & international contacts • Incl. Estonian teacher/school networks, policy-makers 38
  • 39. Beyond CEITER • This vision can be too ambitious for CEITER itself • Once we have initial results, use them to “pitch” consortium and proposals • EU calls: • Evidence-based policy aspect: SwafS-21-2017 • Explore prototypes’ market potential: SMEInst-12-2016-2017 • If things go well, ERC-STG-2018/2019… • Other funding for non-EU countries, e.g.: • US: Partnerships for International Research and Education (NSF PIRE) • Singapore (parallel for systemic change): advisors/expert for national project (visit planned 2017) 39
  • 40. This is just a modular vision… CEITERBlended LA in distributed LEs + ‘just enough’ multimodal LA Teacher training and community of practice Open, privacy- conscious architecture + specific tools Lightweight assessment techniques 40
  • 41. … within an ecosystem of interests Blended LA in distributed LEs + ‘just enough’ multimodal LA Teacher training and community of practice Open, privacy- conscious architecture + specific tools Lightweight assessment techniques Agile & entrepreneurship methods in research Scientific writing & communication support Researcher communities of practice MOOCs Machine learning Learning design Creative writing Tangible & paper UIs Data literacy Data science CSCL Dissemination to the public 41
  • 42. Thank you! Questions? Email: luis.prieto@epfl.ch Website: https://people.epfl.ch/luis.prieto LinkedIn: https://www.linkedin.com/in/lprisan Google Scholar: https://scholar.google.ch/citations?user=ySpnj0MAAAAJ 42