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息 Know-Center GmbH, www.know-center.at
How to encourage lifelong learning at work?
Sebastian Dennerlein, Dr., Graz University of Technology
LAYING THE FUNDAMENT FOR AN AI-LITERATE WORKFORCE
AI4GOOD Summit - BT1: AI Education and Learning, Geneva
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Learning about AI and Acquiring AI-literacy
Leveraging AI-Solutions Requires AI-literacy
2
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Status Quo of Workplace Learning
3
Widespread Approach
3
https://www.lynda.com/
https://www.coursera.org/
https://badgeos.org/developers/
https://pixabay.com/illustrations/graduation-certificate-diploma-2663918/
https://www.codlearningtech.org/2015/11/23/5-questions-what-you-need-to-know-about-moocs/
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Not learning for the Sake of Learning
Gaining Action-Oriented Knowledge via Self-Regulation and Reflection
4
Eraut, M. (2000). Non-formal learning and tacit knowledge in professional work. The British Journal of Educational Psychology, 70(1), 11336.
Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26(2), 247273.
Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into practice, 41(2), 64-70.
Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Charting collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24(3), 226-238.
Goal Setting and
Actuation is
Important
(Zimmermann, 2002;
Littlejohn, Milligan &
Margaryan, 2012)
Reflecting on
Personal Experience
& Received
Knowledge is
Important
(Eraut, 2000/2004)
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Technology can help by
5
Supporting documentation
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Technology can help by
6
Supporting discussion
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Technology can help by
7
Prompting goal setting and reflection
Learning Prompt
Reflective Prompt
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Two Promising Ways to AI-literacy
Hands-on Training & Self-Regulated Learning about AI
8
https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png
Experiential
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
AI Familiy Challenge: 40h of Learning
Build 3 types of
models to practice
Machine
Learning training
Brainstorm
and identify
problem in your
community
Build your invention
Hands-on design
challenges to
introduce
foundational
concepts
(neural networks,
sensors)
Hands-on
Experience in AI,
but no relation
to working context
of mentors!
Largest AI-literacy and mentoring program
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Two Promising Ways to AI-literacy
Hands-on Training & Self-Regulated Learning about AI
10
https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png
Contextualization
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Leverage Prompts for Goal Setting & Reflection!
Bridging Training & Organizational Context
11
Explicate Value of Mentoring to Increase Impact and Motivation
11
息 Know-Center GmbH  Research Center for Data-Driven Business and Big Data Analytics  2019
Most Promising Way to AI-literacy
Best to be implemented in combination
12
https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png
Hands-on Training & Self-Regulation
息 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
gef旦rdert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren F旦rdergebern:
General Manager
office@know-center.at
Prof. Stefanie Lindstaedt
Teamlead
vpammer@know-center.at
Viktoria
Senior Researcher
sdennerlein@know-center.at
Sebastian

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How to Encourage Lifelong Learning with Technology Enhanced Learning

  • 1. 息 Know-Center GmbH, www.know-center.at How to encourage lifelong learning at work? Sebastian Dennerlein, Dr., Graz University of Technology LAYING THE FUNDAMENT FOR AN AI-LITERATE WORKFORCE AI4GOOD Summit - BT1: AI Education and Learning, Geneva
  • 2. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Learning about AI and Acquiring AI-literacy Leveraging AI-Solutions Requires AI-literacy 2
  • 3. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Status Quo of Workplace Learning 3 Widespread Approach 3 https://www.lynda.com/ https://www.coursera.org/ https://badgeos.org/developers/ https://pixabay.com/illustrations/graduation-certificate-diploma-2663918/ https://www.codlearningtech.org/2015/11/23/5-questions-what-you-need-to-know-about-moocs/
  • 4. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Not learning for the Sake of Learning Gaining Action-Oriented Knowledge via Self-Regulation and Reflection 4 Eraut, M. (2000). Non-formal learning and tacit knowledge in professional work. The British Journal of Educational Psychology, 70(1), 11336. Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26(2), 247273. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into practice, 41(2), 64-70. Littlejohn, A., Milligan, C., & Margaryan, A. (2012). Charting collective knowledge: Supporting self-regulated learning in the workplace. Journal of Workplace Learning, 24(3), 226-238. Goal Setting and Actuation is Important (Zimmermann, 2002; Littlejohn, Milligan & Margaryan, 2012) Reflecting on Personal Experience & Received Knowledge is Important (Eraut, 2000/2004)
  • 5. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Technology can help by 5 Supporting documentation
  • 6. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Technology can help by 6 Supporting discussion
  • 7. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Technology can help by 7 Prompting goal setting and reflection Learning Prompt Reflective Prompt
  • 8. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Two Promising Ways to AI-literacy Hands-on Training & Self-Regulated Learning about AI 8 https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png Experiential
  • 9. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 AI Familiy Challenge: 40h of Learning Build 3 types of models to practice Machine Learning training Brainstorm and identify problem in your community Build your invention Hands-on design challenges to introduce foundational concepts (neural networks, sensors) Hands-on Experience in AI, but no relation to working context of mentors! Largest AI-literacy and mentoring program
  • 10. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Two Promising Ways to AI-literacy Hands-on Training & Self-Regulated Learning about AI 10 https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png Contextualization
  • 11. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Leverage Prompts for Goal Setting & Reflection! Bridging Training & Organizational Context 11 Explicate Value of Mentoring to Increase Impact and Motivation 11
  • 12. 息 Know-Center GmbH Research Center for Data-Driven Business and Big Data Analytics 2019 Most Promising Way to AI-literacy Best to be implemented in combination 12 https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png Hands-on Training & Self-Regulation
  • 13. 息 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 gef旦rdert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren F旦rdergebern: General Manager office@know-center.at Prof. Stefanie Lindstaedt Teamlead vpammer@know-center.at Viktoria Senior Researcher sdennerlein@know-center.at Sebastian