Lak18 - Driving Data Storytelling from Learning Design
1. Driving Data Storytelling
from Learning Design
Vanessa Echeverria, Roberto Martinez-Maldonado, Roger
Granda, Katherine Chiluiza, Cristina Conati, Simon Buckingham
Shum
2. “A learning dashboard is a
single display that aggregates
different indicators about
learner(s), learning processes,
or learning contexts into one or
multiple visualisations”
Learning Dashboards
Schwendimann, et al., 2017
3. Growing concern about rolling out
dashboards
(Bodily & Verbert, 2017, Reimers & Neovesky,
2015)
poor InfoViz design
(Reimers & Neovesky, 2015)
lack of users’ participation
(Schwendimann, et al., 2017, Jivet el al., 2018)
(Greller & Drachsler, 2012)
(Bakharia et al., 2016)
(Aguilar, 2016; Corrin & de Barba, 2015; Teasley,
2017)
disconnection with the learning context and
audience
misalignment with the learning
design
data literacy requirements
possible negative effects on learning!
14. Data storytelling
elements
Description
Heading Shows a straightforward message from the graph
Lines to Emphasise relevant information
Key data points Focus attention on key data
Decluttering Remove elements that do not add value to the graph
Text labels Add narratives to the graph
Shaded areas Add context to a group of data points
16. Adapted from Verbert et al.
Learning Design driven conceptual model
Learning design driven
data storytelling approach
Data
DS processing
DS Visual analytics
17. Adapted from Verbert et al.
Learning Design driven conceptual model
Learning design driven
data storytelling approach
Data
Learning
design
DS processing
DS Visual analytics
Data storytelling (DS)
elements
18. Adapted from Verbert et al.
Learning Design driven conceptual model
Learning design driven
data storytelling approach
Data
Learning
design
DS processing
DS Visual analytics
Learning intentions
(rules)
Data storytelling (DS)
elements
19. Adapted from Verbert et al.
Learning Design driven conceptual model
Learning design driven
data storytelling approach
Data
Learning
design
DS processing
DS Visual analytics
Responses
Actions
Analytics
Learning intentions
(rules)
Data storytelling (DS)
elements
Questions
20. Equal participation
Highlight where
there are not equal
participation
Text label, colours,
data points
Learning design Learning intentions
Data storytelling
elements
21. Potential role that data
storytelling elements play to
support interpretations of visual
learning analytics
29. Previous Study Evaluation
with teachers
15 students - 5 groups
Collaborative
Design activity
Participation
Performance
6 teachers
M1: Focus of attention
(Eye tracker)
M2: Helpfulness of data
storytelling elements
(ranking tool)
2 groups
Data
Storytelling
Participation
Performance
M3: Orchestration support
and interpretation of
stories
(interview/think aloud)
30. M1: Focus of attention
http://bit.ly/teachersHeatmaps
31. M1: Focus of attention
http://bit.ly/teachersHeatmaps
33. M2: Helpfulness of data storytelling elements
Add context to the visualisation
34. text labels "add noise and graph complexity"
M2: Helpfulness of data storytelling elements
prescriptive title carefully crafted, due to possible
misunderstandings
35. "… these visualisations (with data storytelling
elements) show me exactly what I need. I don’t have
to guess what happened in the activity"
M3: Orchestration support and interpretation of
stories
Interpretation
36. " … the visualization (with data storytelling elements)
shows me what elements students have created
very clearly, compared to the other (original
)visualization "
M3: Orchestration support and interpretation of
stories
Interpretation
37. " With the original visualisation, I would have to
explore the whole visualisation in order to
understand team’s performance"
M3: Orchestration support and interpretation of
stories
Interpretation
38. " … the shaded area in the graph made me aware
that groups took very different amounts of time to
reflect and so, with this information, I would
encourage students to reflect for a longer time
before submitting a final version of the task"
M3: Orchestration support and interpretation of
stories
Orchestration
39. " … the title in the graph made me think that this
group needed to collaborate more equally"
M3: Orchestration support and interpretation of
stories
Orchestration
40. Summary
Learning design driven
data storytelling approach
Data
Learning
design
DS processing
DS Visual analytics
Responses
Actions
Analytics
Learning intentions
(rules)
Data storytelling (DS)
elements
Questions
41. Summary
Learning design driven
data storytelling approach
Data
Learning
design
DS processing
DS Visual analytics
Responses
Actions
Analytics
Learning intentions
(rules)
Data storytelling (DS)
elements
Questions
42. Equal participation
Highlight where
there are not equal
participation
Text label, colours,
data points
Learning design
Rules
Data storytelling
elements
participant = dominates(P1,P2,P3, time)
msg = ‘participant %d did not have an equal
participation during %d time’, (participant,time)
Learning intentions
43. Implementation of learning design rules
Generate dashboard close to real time
Look impact on debriefing to teachers/learners
Further directions
What it is important? What story is the data telling them?
Dashboard that can be used quickly and efficiently, information and a glance
From recent literature, we have found that learning dashboards have some criticisms such as:
In short, these can be considered as analytics dashboards rather than for supporting learning
learning dashboards - generic charts - how can we enhance these dashboards tru the use of DS
Plots, narratives, call to action
Exploratory vs. explanatory dashboards
communicate a key message clearly and effectively emphasizing the context and meaning
These principles are taken from an Info Vis perspective (data and visual) and data storytelling techniques (narratives, plot, call to action)
Exploratory vs. explanatory dashboards
explain data storytelling - info vis approach
1. enhance sm through DS
use this in one slide
These principles are taken from an Info Vis perspective (data and visual) and data storytelling techniques (narratives, plot, call to action)
Exploratory vs. explanatory dashboards
explain data storytelling - info vis approach
1. enhance sm through DS
use this in one slide
This is a pre-post questionnaire applied to children who participated in a pilot science program
A project manager wants to convince the board committee to continue with a science program from children at a school
budget
IT manager wants to show to the board committee that they need another technician in their team
adapted from previous work, here we can see the data-driven visual analytics approach. From the data captured by logs, clickstreams, etc, one can generate visualisations and then, the user will reflect upon this, based on the exploration of the vis
If the tutor will be sitted with the learner, what would s/he said? what would recommend?
our approach takes the learning design as part of the generation of analytics.
The learning design, which describes the educational process of the whole teaching/learning experience, has valuable information about the pedagogical scenario. From this, now we can know what are the right things that tutors and learners need to be informed.
First DS
How to use them using the learning design
With DS elements, our aim is to reduce cognitive load of interpretation of vis, give a very concise take away message to the audience
From the learning design, we can take some learning intentions, and convert them into rules, to then automatically add DS elements into the processind and visualisation of learning data.
It is important to note that, this takes and explanatory approach
- not exploratory that is up to the analyst
- this is the idea, we are here, we are aiming to this
add table with one rule
The purpose of this research is to
all white
change fig
remove icons
left - previous study right - evaluation with teachers
visualisations were used for debrief - for both users - teacher and learner
change fig
remove icons
left - previous study right - evaluation with teachers
explain about both facing
split the figures
put in english version (figs)
split the figures
put in english version (figs)
before and after vis removing the buubles
change fig
remove icons
left - previous study right - evaluation with teachers
we randomly selected the visualisations
assiting for debriefing, make debriefing more effective
thumbnails of other vis
big hotspots on the right
thumbnails of other vis
big hotspots on the right
show only 1 example
we started to experimenting with eye tracking to assess the impact of visual attention
how we can experimenting with eye trackers
- one message
-explanatory diagram - venn diagram
- one message
-explanatory diagram - venn diagram
generate dashboard close to real time and look impact on debriefing to teachers/learners