Rebo is the first reflection guidance chatbot that systematically guides appren-tices through successive levels of reflection on a learning experience. I firstly investigate general conditions for designing computer-mediated learning inter-ventions for apprentices. I aim to predict their computer literacy by determin-ing computer usage and self-efficacy, and I investigate apprentices as a com-munity of practice, focussing on their learner identities. My main area of inter-est is to develop Rebo, the reflection guidance chatbot that guides them to re-flect on practical learning tasks, working through defined, subsequent levels of reflection. This active guidance from one level of reflection to the next is new, thus a major contribution to existing research on reflection guidance in the field of technology-enhanced learning. The dialogue structure based on de-fined reflection levels, Rebo Junior, is evaluated in multiple field studies, where the reflective conversations between apprentices and Rebo Junior are analysed for coherence, reflection level and engagement. Furthermore, I inves-tigate which adaption mechanisms are relevant for successful reflection guid-ance with a conversational agent, continuously improving and enhancing chat-bot Rebo.

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Designing Rebo, the Reflection
Guidance Chatbot
IN THE CONTEXT OF DIGITALISING APPRENTICESHIP TRAINING
Mag. Irmtraud Wolfbauer
ECTEL 2020, online

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Reflection works on different levels
0. Revisiting: Returning to learning experience
1. Description: Describing learning experience
2. Judgement: Did it go well? Why/Why not?
3. Emotions: What did it feel like? Did you enjoy it?
4. Learning: Evaluate experience - What did you learn?
5. Contextualisation: What was the situation like?
6. Planning: Behaviour change – And next time?
Inspired by e.g.
Boud, D. et. al.: Reflection. Turning experience into learning, London, New York (1985)
Renner, B. et. al.: Effects of Prompting in Reflective Learning Tools: Findings from Experimental
Field, Lab, and Online Studies. Frontiers in psychology (2016).
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Research Questions
RQ1: How do apprentices use computers and how self-efficacious
are they with regard to ICT?
RQ2: What characterises apprentices as a community of practice
with special re-gard to their learner identities?
Understanding the target group
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Research Questions
RQ3: How apt is Rebo’s dialogue structure to successfully lead
apprentices in reflection? - Focusing on: acceptance of the
conversational agent, reflectiveness of interactions, engagement
of apprentices over time.
RQ4: Which adaption mechanisms does a conversational agent
for reflection on practical learning tasks need?
Designing the learning intervention with guided reflection &
continuous evaluation
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Research Questions
RQ5: What characterises discourse between humans and
chatbots?
Interesting emerging discursive features of resulting reflective
dialogues
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RQ1 Apprentices & Computers: An investigation of usage and self-efficacy
in a sample of Austrian apprentices in metal and electrical engineering
Mixed-method approach:
• Quantitative method: questionnaire, 72 apprentices
• Qualitative method: in-depth interviews, 6 apprentices
Questionnaire based on:
• Computer Usage: Glušac, D. et. al.: Adolescents' informal computer usage and
their expectations of ICT in teaching – Case study: Serbia. Computers & Education
(2015).
• Computer Self-Efficacy: Wang, Y., Haggerty, N.: Individual Virtual Competence and
Its Influence on Work Out-comes. Journal of Management Information Systems
(2011).
Paper in preparation
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RQ2 Apprentices as Community of Practise: An Investigation of
Learner Identities
Method:
• Semi structured in-depth interviews
• 8 apprentices, 3 apprenticeship supervisors, 3 trainers
Literature:
• Lave, J., & Wenger, E. (1991). Situated Learning - Legitimate peripheral
participation.
• Boud, D., & Solomon, N. (2003). “I don’t think I am a learner”: acts of
naming learners at work. Journal of Workplace Learning.
Data available, analysis upcoming
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RQ3 Rebo Junior: Analysis of Dialogue Structure Quality for a
Reflection Guidance Chatbot
You are cordially invited to my paper presentation here at ECTEL!
Parallel session 22: Impact III
Thursday, September 17, 1:30 pm
Track: Track 4 (Z4)
Track Location: Zoom room 4
published
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2. Judgement
3. Emotions
4. Learning
5. Planning
0. Revisiting
1. Description
 Upload of task
Field study 1
Reflective dialogue with Rebo Junior

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RQ4 & RQ5
• Designing Rebo, the Reflection Guidance Chatbot
 Method: Experimental field studies
• Chatting with Bots– a New Discourse
 Method: (Critical) Discourse Analysis
Analysis ongoing
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Thank you!
Well, what do you think?
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Business and Big Data Analytics
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gefördert durch das Programm COMET (Competence Centers for Excellent Technologies), wir danken unseren Fördergebern:
Researcher
iwolfbauer@know-center.at
Irmtraud Wolfbauer