Lecture by Pablo Moreno Ger on the potential and implications at the crossroads of Learning Analytics and Serious Games
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Pablo Moreno Ger [email protected] Pori July 22nd, 2014 GALA
Summer School Pablo Moreno Ger (et al.) Learning Analytics in
Serious Games
Hello! Lets start with a story An online course on how to use
Excel With online delivery of exercises Delivering the exercises on
time is a requisite for attending the final face-to-face exam
The story develops A few days before the exam, I receive an
email: I have been following the course, reading the materials
carefully and delivering my exercises. The last two exercises have
been really difficult, and I have been trying different solutions
and seeking help from some friends. In the end I managed to
complete them and tried to upload them last night. But the website
kept showing me errors and I have been unable to upload them. Can I
send them via email and still be eligible for the exam?
A slow look at the Moodle log Course opens: February 21st
2013/02/27-18:35:43 - NameOmitted - Course View Main *** 28 hits in
30 minutes Chapter 1, Chapter 2, forums, exercise delivery tools,
etc. *** March 7th 2013/03/07-18:35:43 - NameOmitted - Course View
- Main 2013/03/07-18:37:45 - NameOmitted - Resource View Exercise 1
2013/03/07-19:01:19 - NameOmitted - Assignment View - Exercise 1
2013/03/07-19:01:38 - NameOmitted - Assignment View - Exercise 1
2013/03/07-19:01:43 - NameOmitted - Course View Main This is a
typical pattern: - Study the exercise (he does not open the course
materials) - Complete it (24 minutes) - Submission (two steps,
Moodle does not differentiate)
A slow look at the Moodle log March 10th The exercise is
corrected and an email is sent 2013/03/11-08:55:43 - NameOmitted -
Course View - Main 2013/03/11-08:55:51 - NameOmitted - email_list
view_all_mail 2013/03/11-08:55:55 - NameOmitted - email_list
view_110652 2013/03/11-09:01:19 - NameOmitted - Assignment View
Exercise 1 May 19th Instructor sends mass email notifying exam
dates May 21st First student log in in two months
2013/05/21-22:27:06 - NameOmitted - Course View Main
2013/05/21-22:27:11 - NameOmitted - email_list view_all_mail
2013/05/21-22:27:13 - NameOmitted - email_list view_123657 Another
typical pattern: - Log in - Read mail - Check grade & comments
(from link in email)
What we can do with Web Analytics Web Analytics for Dummies How
are my keywords working? Which are my landing pages? Where are my
customers coming from? Which days/hours have more traffic?
What we can do with Web Analytics Web Analytics for Pros Which
ads are generating more traffic? Which ads are generating more
revenue? From which pages are my users departing? And the really
advanced stuff: Cycles Dead ends Losses of revenue Dead pages
Facebook
Thats ok but OK, enough corporate, lets talk about
learning!
Analytics, Analytics, Analytics! Web Analytics Learning
Analytics
And now its 2014 LA was an obscure term in 2007 Today: Learning
Analytics is featured in H2020-ICT-20 as a key learning technology
Most TEL conferences include a track on LA And some summer schools,
a lecture Special issues on LA in major TEL journals
From business to (TEL)-research What happened?
A perfect storm
No, really, what happened? 2006-2010 steady increase of
Learning Analytics In 2009, Big Data explodes In 2010, GALA starts
In 2010, MOOCs happen Learning Analytics become a Big Data
problem.
What we can do with Learning Analytics Learning Analytics for
dummies Most accessed contents Least accessed contents Time spent
in each resource Average grades in quizzes Easy/hard questions on
quizzes Students that drop out Trends and timelines
What we can do with Learning Analytics Learning Analytics for
pros Changes in usual patterns (potential issues) Study of the
impact of changes (see Facebook) Local / Regional / National data
aggregation Big data problems (if your population is large enough
And the really advanced stuff: Predict student dropout Predict
grades Automatic adaptation
Dimensions of Learning Analytics The what we measure dimension
Activity on a virtual campus (e- or b-learning) Usage patterns by a
spefic students Usage patterns by groups of students Detailed
assessment (per question, per answer) Forum participation Time
spent on each resource Access frequency
Dimensions of Learning Analytics The why we measure dimension
Assessment of learning effectiveness Assessment of the learning
process Assessment for learning Assessment of the e-learning
platform And of course Predictive assessment Usability
Validation
Dimensions of Learning Analytics The where we measure dimension
(or scope) Individual analytics Classroom analytics School /
Institution analytics Regional analytics National / International
analytics
LA is here to stay But theres more!
And now for something completely different
Analytics, Analytics, Analytics! Web Analytics Game Analytics
Learning Analytics
Game Analytics
Game Analytics Game Analytics for Dummies Time spent on each
level Barriers and game issues Dead scenes Usability Assessment
Game Analytics for Pros Monetization
Candy Crush Saga
Enough about money Can we get back to learning?
And here, we, go!
Analytics, Analytics, Analytics! Web Analytics Game Analytics
Game Analytics for LearningLearning Analytics
Stop and think HTML files vs. Game Quiz vs. In-game performance
Forum vs. MMORPG
Stop and think Single player in a single gameplay
Stop and think An entire school playing the same game
Stop and think A 1-million student MOOC with a game
Stop and think An edX-like platform filled with games
Stop and think All schools in Europe playing games
So much power in our hands!
But we have no clue on how to use it
What we (GALA) do ANGEL SERRANOLAGUNA LEARNING ANALYTICS AND
SERIOUS GAMES GLEANER "The gleaners", Jean-Franois Millet
GLEANER
Stuff we can do Generic traces Mouse clicks (left/right/middle)
Mouse movement (free movement, drag) Key presses (up / down /
press)
Stuff we can do Engine-specific traces (for eAdventure game
engine) Actions performed Speech bubbles Answers in multiple choice
questions Scene transitions Changes in variable values
Case Study: The Big Party
GLEANER traces 100,000 lines for a 40-minute playthrough
Heatmaps
Case study 2: The Foolish Lady
Analytics-based assessment
Case Study 3: Lost in XML Space
Case Study 3: Lost in XML Space
Realtime Dashboard
Real Time dashboard REALTIME DASHBOARD
But this is not about what WE do
What you can do Figure out how to use generic traces in your
games Figure out new traces specific to your games Try to
standardize and share GLEANER or your own approach There is
standard stuff to exchange data (e.g. xAPI)