The Know-Center in Graz, Austria researches innovative computer technologies and co-design of work practice, learning, and technology to revolutionize learning in organizations. Specifically: - The Know-Center has over 15 years of experience researching and developing learning technologies for workplaces. - Their Learning 4.0 initiative aims to personalize and contextualize learning for professionals using blended learning approaches and technologies like learning management systems and intelligent mentoring. - Their current projects include developing information literacy and digital competencies for professionals through micro-learning and reflective prompts, as well as designing complex blended learning ecosystems and living organizational memory systems.

1. b
b
© Know-Center GmbH, www.know-center.at
Learning 4.0: Learning and EdTech @ Know-Center
Univ.-Prof. Dr. Stefanie Lindstaedt
Ass.-Prof. Dr. Viktoria Pammer-Schindler, Hermann Stern
INNOVATING WORKPLACE LEARNING

2. © Know-Center GmbH, www.know-center.at
UNTERNEHMEN2001GEGRÜNDET
50PARTNER
120FORSCHENDE
COMETEU-WEIT VERNETZT
© 2018 Know-Center GmbH www.know-center.at

3. © Know-Center GmbH, www.know-center.at
© 2018 Know-Center GmbH www.know-center.at
Knowledge Discovery
Social Computing
Knowledge Visualization
Data-Driven Business
Data Management
Data Security

4. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
MISSION LEARNING 4.0
We aim to revolutionize learning in
organisations via
Ø innovative computer technologies
Ø co-design of work practice, learning and
technology
Data-Driven Business

5. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
Track Record
Research & Innovation
We do so based on a long track record and multiple
perspectives on learning and edtech @ work
• Contextualised and personalised
learning guidance
• Work-integrated learning
• Knowledge maturing and knowledge
gardening
• Learning in Networked Environments
• Data-Driven and Reflective Learning
• Learning Analytics
5

6. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
Visibility and Activities
Research, innovation, and implementation of learning
and educational technology in workplaces
• International visibility and networks
• Representation in European and International Research
Associations for Learning + EdTech (IAALDE, EATEL)
• European research projects
• National visibility and networks
• Represented in Taskforce “Digitale Kompetenzen” of BMDW
• Invited to speak as experts
• National research and innovation projects
6

7. © Know-Center GmbH
gefördert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren Fördergebern:
b
INTERESTED? CONTACT US
CEO and Scientific Director: Univ.-Prof. Dr. Stefanie Lindstaedt, slind@know-center.at
Key Researcher Learning and EdTech: Ass.-Prof. Dr. Viktoria Pammer-Schindler, vpammer@know-center.at
Business Area Manager Learning 4.0: Hermann Stern, hstern@know-center.at
7

8. b
b
© Know-Center GmbH, www.know-center.at
Blended Learning for Professionals
Ass.-Prof. Dr. Viktoria Pammer-Schindler
Graz, Learning 4.0 – May 28, 2019, Know-Center

9. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WHY IS WORKPLACE
LEARNING IMPORTANT?
9

10. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
FIRST: AGELESS SPECIFICITIES OF
WORKPLACE LEARNING
• Contextualisation of knowledge
• Reflection and construction
of knowledge
10

11. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
LEARNING AS A MEANS TO DEAL WITH
CONSTANT AND FAST CHANGE
• The more dynamic the environment of an organisation,
the more necessary it is for the organisation to learn.
• Acquired expertise needs to be continuously updated.
11

12. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
MORE KNOWLEDGE WORK
• Knowledge work is increasing
• Tasks are getting more complex
• more specialised
• in parallel require more interdisciplinary
collaboration
• jobs are increasingly designed
acknowledge work in all sectors.
• De-centralisation
• Trend to de-centralise decision-making
• Increase flexibility
• Consequence: increasingly high-level
knowledge in operative positions needed
12

13. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
LEARNING MATERIALS AND EXPERTS ARE
EVERYWHERE/ANYWHERE
• Information/knowledge that is not available in-house
is being retrieved otherwise.
• Organisations need to
• quality-check
• systematically attach to new
knowledge sources and networks
• offer more engaging
modern in-house training
13
… but guidance (=teachers, coaches, mentors) is needed

14. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
EXPECTATIONS TOWARDS TECHNOLOGY
THAT SUPPORTS LEARNING
• From private life, people are used to engaging, fun apps
– easy to understand, aesthetically pleasing, addictive
14

15. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
CHALLENGES FOR
DESIGNING TECHNOLOGIES
FOR WORKPLACE LEARNING
15

16. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
IT’S INTERDISCIPLINARY!
16
Learning
Science
Computer
Science
Domain
Knowledge
Critical!
Design-oriented!
Practice-
oriented!

17. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
REQUIRES INNOVATIVE CONTEXT-AWARE
DESIGN
Respects
• Different goals and motivations of learners (and their
employer organisations)
• Work structure
• Tools – IT and conceptual
17

18. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
TEAM
OF EXPERTS
Senior
Researchers
PhD
Students
Junior Researchers and
Research Developers
Business
Area
Manager
Research
Area
Manager
External Co-
Supervision @
NTNU w Monica
Divitini
Co-Supervision
w Eduardo
Veas

19. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
EDTECH BUILDING
BLOCKS
19

20. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
CO-DESIGN AND BLENDED LEARNING
There‘s a time and place for everything: working, learning
and technology
• Methods: Contextual design, co-design
• Socio-technical concept: Blended learning
• Technologies can be simple: Moodle, OpenEdx,
standard office and productivity tools as mediating
technologies for learning.
20

21. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
LEARNING ≠ TRAINING
Before
Training –
Work and
Prepare
Training
After
Training –
Work and
Apply
21
Interactive media –
quizzes, simulations,
online materials (in LMS,
MOOCS, etc.)
Offline, synchronous/
asynchronous
communication software
Intelligent technologies
for self-regulated
learning; learning
analytics; learning and
reflection guidance
That’s one of our
core research
challenges!

22. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WORKING – LEARNING / INDIVIDUAL -
ORGANISATION
Team practice
develops
Organisational
performance
(KPIs) and
learning
Operative
work
Individual
professional
development
22
Workplace learning closely connects with operative work!
Work-process support –
supporting working AND
learning in one digital
environment
Knowledge management
Compliance
Continuous process
improvement
Content management
Communication / social
software
That’s one of our
core research
challenges!

23. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
LEARNING AND REFLECTION GUIDANCE
• Minimal guidance only works for (domain) experts
Therefore: Research on Intelligent mentoring –
reflection guidance @ Know-Center
• This supports:
• Navigating the learning domain
• Understanding data about own work practice (learning analytics
in workplace learning)
• Identifying learning strategies
23
EdTech Building Blocks
5
1
2
3
4

24. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WHAT NOW? GOING IN-
DEPTH
24

25. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
SELECTED RESEARCH STREAMS
• Information Literacy and Digital
Competences via Micro-Learning
• Learning Analytics and Co-Design
• Designing for complex Blended Learning
Ecosystem – Learning goals as master
representation for trainings
• Living organizational memory and
knowledge 4.0
25
Discussed at the Learning 4.0 event on May 28

26. b
b
© Know-Center GmbH, www.know-center.at
Information Literacy and Digital Competences
via Micro-Learning
DI Dr. Angela Fessl
LERNEN 4.0 – NEUE ARBEITSWELTEN, NEUE LERNWELTEN
Data-driven Future Forum, Graz, 28.5.2019

27. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
THE MOVING PROJECT
(http://moving-project.eu/)
27
MOVING: TraininG towards a society of
data-saVvy inforMation prOfessionals to
enable open leadership INnovation

28. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
DAS MOVING PROJEKT
28
• 2016 - 2019
• Budget: 3,5Mio €
• Anwendungspartner:
• Studenten (TU Dresden)
• Ernst & Young
This project has received funding from the
European Union’s Horizon 2020 research
and innovation action programme under
grant agreement No 693092

29. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
HERANGEHENSWEISE
29
ZIELGRUPPE
• Junge Forscher
• WissensarbeiterInnen –
Use Case: AuditorInnen
• EU Bürger/Bewohner
MOVING bietet
• Ausbildung und Arbeiten
bezüglich datenintensiven
Forschungsaufgaben
• Benutzerführung zur
Selbst-Reflektion
PROJEKT ERGEBNIS
• Daten-versierte
Informationsfachleute
• Kompetente
Wissensgesellschaft

30. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics 30
INFORMATION LITERACY UND DIGITALE
KOMPETENZEN – MIT HILFE VON MICRO-
LEARNING UND REFLEXIONS-UNTERSTÜTZUNG

31. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
INFORMATION LITERACY AND DIGITAL
COMPETENCE
31
• Information Literacy und Zugang und die Verwendung
von Wissen …
• Ist eine Voraussetzung um im sozialen, wirtschaftlichen,
kulturellen und politischen Bereichen aktiv teilnehmen zu können
• Information Literacy = fundamentale Kompetenz
• Ähnlich wie lesen, schreiben, rechnen
• Information Literacy = „Überlebenstechniken” im
Informationszeitalter

32. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics 32
• Curriculum: Information Literacy und Digital Competency
• 3 verschiedene Module
• Searching information in digital environments
• Communication and collaboration in digital environments
• Content creation in digital environments
• Jedes Modul besteht aus Sub-Kompetenzen und
unterschiedlichen Kompetenz Levels
INFORMATION LITERACY AND DIGITAL
COMPETENCY

33. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
BEISPIEL AUS DEM CURRICULUM
33
LERN MODUL SUB-KOMPETENZEN LERNZIELE
SEARCHING INFORMATION IN
DIGITAL ENVIRONMENTS
Browsing, searching and filtering
data, information and digital
content
to articulate information needs,
turn a (research) question into a
search strategy,
to search and access data,
information and content;
to create and update personal
search strategies;
Evaluating data, information and
digital content
to analyse, compare and critically
evaluate the credibility and
reliability of sources and the
data, information and content;
Managing data, information and
digital content
to organise, store, retrieve and
process data, information, and
content;

34. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
VERWENDETE LERNSTRATEGIEN
34
• Micro Learning
• „Micro-learning refers originally to taking short-term-focused
learning activities on small learning content units“
• Reflektives Lernen
• … ist das bewusste Nachdenken über vergangene Erfahrungen
um daraus zu Lernen und das zukünftige Verhalten zu steuern.
(Kovachev et al, 2011)

35. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
ZIEL: AUTOMATISCHE LERN-UNTER-
STÜTZUNG
35
Forschungsfragen
• Information Literacy and Digital Competences via Micro-
Learning
• Ziel 1: Zusammenspiel “Micro Learning” und “Reflective
Learning”
• Ziel 2: Reflektive Prompts formulieren, die zum Nachdenken
anregen und zum Lernen motivieren
• Ziel 3: Lernziele automatisch erkennen

36. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics 36
IMPLEMENTIERUNG – MICRO-LERNEN UND
REFLEXION IN EINEM CURRICULUM
REFLECTION WIDGET

37. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
MOVING PLATTFORM
37
• MOVING Plattform:
• Suchplattform mit unterschiedlichen Suchmöglichkeiten, Filtern,
Visualisierungen, etc.
• Speichert Activity Log Data
Ø In diese Plattform wurde die Lernunterstützung integriert
• User Model: Besteht aus Informationen die ein System
über einen Benutzer besitzt
• MOVING Plattform speichert alle Interaktionen von
BenutzerInnen im User Model, sowie Aktivitäten bzgl. Konkreter
Lernziele

38. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
MOVING PLATFORM - SCREENSHOT
38
(https://moving.mz.tu-dresden.de)

39. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WIDGET: DAS KONZEPT
Information Literacy
Curriculum
Micro Learning
Content
MOVING Platform
CURRICULUM
User Model
Activity Tracking
MOVING Platform
Prior Knowledge
Assessment
USER MODEL WIDGET
Curriculum
Reflection Widget
Reflective Prompts
Learning Prompts

40. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
PRIOR KNOWLEDGE ASSESSMENT
40
• Fragebogen um das Widget zu initialisieren
• Ergebnis wird im User Model gespeichert

41. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WIDGET …
• … zeigt einen “Learning
Prompt” der zur
Lernumgebung führt.
• … schlägt den Prompt
und den Inhalt
entsprechend dem
Kompetenzlevel und dem
Lernfortschritt der
BenutzerIn vor.

42. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WIDGET …
• … zeigt einen reflektiven
Prompt an um zum
Nachdenken über den gerade
gelernten Inhalt anzuregen.
• Prompts wurden auf 3 Levels
implementiert abhängig von
Benutzererfahrung und Wissen
in Bezug auf die Platform.

43. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
WIDGET …
• … zeigt den
Gesamtfortschritt der
BenutzerIn für die drei
Module des Information
Literacy und Dig Comp
Curriculums an.
Ø Könnte Basis für
Nachweis von informell
erworbenen
Kompetenzen sein!
Lernfortschritt in den 3 Modulen

44. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
44
DISKUSSION & ZUSAMMENFASSUNG

45. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
ZIEL 1+2: “MICRO LEARNING” UND
“REFLECTIVE LEARNING”
• Vorteile:
• Inhalt wird in kleinen „bits and pieces“ aufbereitet
• Widget führt BenutzerInnen automatisch durch das Curriculum
• Alle Themen sind abgedeckt
• Gibt Lernpfad vor – BenutzerInnen müssen nicht selber über
Reihenfolge entscheiden; können aber.
• Die Anzeige des gesamten Lernfortschritts motiviert um weiter
zu lernen
• Offen:
• Automatisches Feedback auf Reflexionen von BenutzerInnen

46. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
ZIEL 3: LERNZIELE AUTOMATISCH ZU
ERKENNEN
46
• Hintergrund: Lerninhalte sollen entsprechend dem
Kompetenzlevel angeboten werden
• Activity Logging wird verwendet um festzustellen, mit welchen
Lerninhalten sich der/die Lernende befasst hat.
• Klick auf den NEXT Button als Indikator für „Verstanden“
Ø Funktioniert für reflektierte BenutzerInnen, kann aber nicht
verwendet (in dieser Implementierung) um gesichert
festzustellen was BenutzerInnen können.

47. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
LIVE DEMO
47
• Probieren Sie es selber aus!
• https://moving.mz.test.tu-dresden.de/

48. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics
PUBLIKATIONEN
Automatische Anleitung zur Reflexion:
• Angela Fessl, Gudrun Wesiak, Veronica Rivera-Pelayo, Sandra Feyertag, Viktoria Pammer.
In-app Reflection Guidance: Lessons Learned across Four Field Trials at the
Workplace. IEEE Transactions on Learning Technologies, Vol 10/4, pp 488-501, 2017.
DOI: https://doi.org/10.1109/TLT.2017.2708097
Curriculum Reflection Widget:
• Angela Fessl, Ilja Simic, Sabine Berthold, Viktoria Pammer-Schindler. Concept and
Development of an Information Literacy Curriculum Widget. In: Proceedings of
Conference on Learning Information Literacy across the Globe, 2019. PDF
• Angela Fessl, Alfred Wertner, Viktoria Pammer-Schindler. Challenges in Developing
Automatic Learning Guidance in Relation to an Information Literacy Curriculum. In:
Proceedings of the 1st Workshop on Analytics for Everyday Learning, CEUR Workshop
Proceedings, Vol. 2209, 2018. PDF
48
… und lesen Sie nach!

49. © Know-Center GmbH
Know-Center GmbH
Research Center for Data-Driven
Business and Big Data Analytics
Inffeldgasse 13/6
8010 Graz, Austria
Firmenbuchgericht Graz
FN 199 685 f
UID: ATU 50367703
gefördert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren Fördergebern:
Senior Researcher
afessl@know-center.at
Dr. Angela Fessl