Wilhelm Klat, Bielefeld Universität, zum Thema „A.I. in E-Learning“ Das EdTech Hamburg Meetup ist ein Treffen für jeden, der sich für den Einsatz von Bildungstechnologie in Schulen und Hochschulen, als auch in anderen Bereichen, interessiert. Mach mit! Besuche unsere Website: http://www.edtech.hamburg Folge uns auf Twitter: http://www.twitter/edtechhamburg Like EdTech Hamburg auf Facebook: https://www.facebook.com/edtechhamburg/

3. A.I. in E-Learning
4th EdTech Meetup Hamburg
Wilhelm Klat (M.Sc.)
Former Research Assistant
at the Bielefeld University
Chairman of the Gesellschaft für
Bildungsinnovation e.V.
wilhelm.klat@uni-bielefeld.de
Dipl. Betriebswirt (FH) Michael Johner
MJohner Consulting & Training
Member of the SAGSAGA board - (Swiss
Austrian German Simulation And Gaming
Association: sagsaga.org)
info@mjohner.de
Dr. Kristina Schaaff
Consultant at Inform GmbH

4. Introduction
Hi, I’m Clippy.

5. Simulation Games and A.I.
I try help you with
your virtual job.
I simulate jobs.
And together we are more than the sum of our parts.

6. Simulation Games: An Effective Learning Instrument
It allows and focuses on the training of higher cognitive skills*:
Remembering
Understanding
Application
Analysing
Evaluating
Synthesizing
* based on Bloom’s taxonomy (1956)
1
2
3
4
5
6

7. Time
Participants
/ Instructor
Computer
Web
A.I.
✓ calculation
✓ administration
✓ flexibility
✓ standardization
✓ administration
201620001990
✓ learning analytics
✓ learning support
40
20
60
The Core Challenge of Simulation Games

8. Our Work on A.I. in E-Learning
Enable A.I. to support instructors and participants.
PROJECT
GOAL
CHALLENGE Enable A.I. to detect missing knowledge of participants.
STATUS QUO
NEXT
GENERATION
analyze decisions
and results
What decisions have been made?
Are these decisions good?
>
Why decisions have been made?>
analyze
tracking data
track decision
making process

9. Tracking
1 2Physiological senses Emotions
bitspersecond
10M
1M
0.1M 0.1M 0.01M
Sight Touch Smell Hearing Taste
“Flow”
Tension,
Anger
Relaxation,
Resignation
performance
arousal
Yerkes & Dodson (1908)
Heart rate
Blood pressure
Vocal expression
Facial expression
Body movement
and much more..
Skin conductance

10. Tracking: Sight (Web Analytics)
>
Implications:
Requires a complete redesign of user interfaces and learning processes
84-88% correlation with eye movement
(Chen et al., 2001)
Movement
(Heatmaps)
Mouseover & Clicks
(Clickmaps)
Scrolling
(Scrollmaps)

11. Tracking: Sight (Eye Tracking)
integrated remote mobile
Pros:
Cons:
no costs, easy
application
sub-optimal accuracy
costs (~2,000 €), poor
mobility
accuracy
best accuracy, soon
“bring your own device”
not yet available, costs
(~500-800 €)
>
Implications:
Breakthrough of mobile eye-tracking expected in 2016 (e.g., MS HoloLens).

12. Tracking: Emotions
>
Implications:
Wearable technology provides new opportunities for cheap and easy emotion
tracking on a large scale.
mouse & touchpadsactivity trackerssmart watches
heart rate: optical pressureheart rate: optical &
infrared

13. Missing Information Approach (MIA)
decision
give feedback for information 3
no feedbackseen
not
seen
important
information
1
2
3
4
5
Data Analysis using an Expert System

14. Data Analysis using an Expert System
Emotional Reaction Approach (ERA)
time
emotion tracking
(heart rate)
eye tracking
(seen information)
A B
expected heart rate
give feedback for
information B

15. Data Analysis using a Neural Network
Search Path Approach (SPA)
Search path of experts
Search path of beginners

16. Learning Testing
Universities
Companies
Individuals MOOCs
Bachelor and MBA
Corporate Training
Individual Assessment
(for LinkedIn, Xing)
Post-graduate MBA test
(see e.g., GMAT)
(Online) Assessment
centers
Fields of Application

17. Summary
❏ Stand-alone virtual learning assistants cannot provide learning support
❏ They need to be embedded and integrated in a learning environment that
produces the required data (e.g., simulation games)
❏ Window of opportunity from web technologies, the internet of things, and
wearable devices
❏ Huge global impact: High quality E-Learning becomes accessible and
affordable for everybody
❏ Measure what is measurable and make measurable what is not. (Galilei)

18. Thank you for your attention!
Wilhelm Klat (M.Sc.)
wilhelm.klat@gmail.com
Dipl. Betriebswirt (FH) Michael Johner Dr. Kristina Schaaff