The document discusses strategies for fostering AI literacy in the workplace, emphasizing the importance of self-regulated learning and hands-on training. It suggests using technology to support goal setting and reflection, and highlights experiential learning activities that connect AI concepts to real-world problems. Additionally, mentoring is identified as a key factor in enhancing motivation and impact in AI education.

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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. © 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
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3. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics • 2019
Status Quo of Workplace Learning
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Widespread Approach
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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. © 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
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Eraut, M. (2000). Non-formal learning and tacit knowledge in professional work. The British Journal of Educational Psychology, 70(1), 113–36.
Eraut, M. (2004). Informal learning in the workplace. Studies in Continuing Education, 26(2), 247–273.
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. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics • 2019
Technology can help by…
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Supporting documentation

6. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics • 2019
Technology can help by…
6
Supporting discussion

7. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics • 2019
Technology can help by…
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Prompting goal setting and reflection
Learning Prompt
Reflective Prompt

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Two Promising Ways to AI-literacy
Hands-on Training & Self-Regulated Learning about AI
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https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png
Experiential

9. © 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. © 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. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics • 2019
Leverage Prompts for Goal Setting & Reflection!
Bridging Training & Organizational Context
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Explicate Value of Mentoring to Increase Impact and Motivation
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12. © 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…
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https://commons.wikimedia.org/wiki/File:Two-ways-of-life.png
Hands-on Training & Self-Regulation

13. © Know-Center GmbH
Know-Center GmbH
Research Center for Data-Driven
Business and Big Data Analytics
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gefördert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren Fördergebern:
General Manager
office@know-center.at
Prof. Stefanie Lindstaedt
Teamlead
vpammer@know-center.at
Viktoria
Senior Researcher
sdennerlein@know-center.at
Sebastian