Jtelss - 030619 - Reflection guidance workshop
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The document discusses technologies and approaches for data-driven reflective learning. It describes how prompts, diaries, journals, and visualizations can be used to encourage reflection on work activities, knowledge, mood, search behavior, and learning progress. Examples of intelligent mentoring systems and reflective learning apps are provided. Challenges with reflection timing, context, and motivation are also outlined. The goal is to use data and adaptive systems to support lifelong learning from experiences.
Jtelss - 030619 - Reflection guidance workshop
- 1. © Know-Center GmbH, www.know-center.at Reflection Guidance Angela Fessl STATE-OF-THE-ART AND CHALLENGES IN INTELLIGENT MENTORING SYSTEMS JTELSS 2019, Bari, Italy, 3rd June 2010 1
- 2. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics THINK ABOUT YESTERDAY‘S EXCURSION …. 2 • What was your highlight? And why? • What could be improved? Grotte di Castellana Alberobello Polignano a Mare
- 3. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics REFLECTION GUIDANCE 3
- 4. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics DATA-DRIVEN AND REFLECTIVE LEARNING • Problem setting • Design for lifelong learning from experience • Approach • Use data as basis for learning from experience via adaptive learning support • Expected results • Socio-technical concepts that combine working and learning to improve work performance on all levels
- 5. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics REFLECTIVE LEARNING … 5 … is the re-evaluation of past experiences with the goal to learn from them to drive future behaviour.
- 6. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: PROMPTS 6 Data-Driven and Reflective Learning • Reflection Interventions vs. Reflection amplifiers • Generic prompts vs. Directed prompts • Prompts in conversation (ChatBots) Prompts Prompts Misc. Diaries Visuals (Kocielniketal.,2018) (Davis, 2000)
- 7. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: PROMPTS 7 Data-Driven and Reflective Learning • Advantages: • Well investigated in learning environments, less investigated in work-place settings • If reflective learning is induced depends on the type of prompt • Disadvantages: • Timing: when should they be presented in order to be perceived as useful and not as disruptive? • How: How should they pre presented? Silent notification vs. Popup? Prompts Misc. Diaries Visuals
- 8. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: DIARIES/JOURNALS/E- PORTFOLIOS 8 Data-Driven and Reflective Learning • Diaries: personal notes not to be shared • Journals/ePortfolios: shared with trainer/teacher/colleagues Prompts Misc. Diaries Visuals From: http://ultranet.stdoms.ac.nz/WebSpace/4865/
- 9. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: DIARIES/JOURNALS/E- PORTFOLIOS 9 Characters Timeline Scribble Bluetooth devices Incoming/ Outcoming SMS Photos (Ståhl, et al. 2009)
- 10. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: DIARIES/JOURNALS/E- PORTFOLIOS 10 Data-Driven and Reflective Learning • Advantages • Works well and lead to reflective learning • Disadvantages • Difficulties in writing • Time consuming in keeping and maintaining • Well consideration necessary, where to introduce Prompts Misc. Diaries Visuals
- 11. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: VISUALS 11 Data-Driven and Reflective Learning • Smart Indicators, videos, images, charts, …Prompts Misc. Diaries Visuals (Glahn et al., 2009) (Malacria et al., 2013) (Fessl et al., 2019)
- 12. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: VISUALS 12 Data-Driven and Reflective Learning • Advantages • Easy to understand • Motivation through comparison via gamification • Fotos and videos, easy to interpret • Disadvantages • Photos, videos -> GDPR • It needs to be well considered what to present worth being reflected on Prompts Misc. Diaries Visuals
- 13. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: MISCELLANEOUS 13 Data-Driven and Reflective Learning Prompts Misc. Diaries Visuals (Prilla et al., 2013)
- 14. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TECHNOLOGIES: MISCELLANEOUS 14 Data-Driven and Reflective Learning • Advantages • Everything that might be worth being reflected on can be used and presented • Disadvantages • Decision of what is worth being reflected upon? Prompts Misc. Diaries Visuals
- 15. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics IN-APP REFLECTION GUIDANCE CONCEPT 15 Reflection-in-action Reflection-on-action How often?At what time? Which type? Pop-up automatically Self-regulated reflection Reflection Intervention Reflection Amplifier Application usage during work Usage Reminder Awareness of team usage Awareness of individ. data Awareness of team data Guidance with Context Reports and Feedback Reflection Journal/Diary Ask for context Statistical information Significant Patterns Insert outcomes or insights Reflect on entries Context information Intertwined Provide options for context
- 16. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics DATA-DRIVEN AND REFLECTIVE LEARNING 16 Motivation & Challenges „What is in for me“? • Timing for reflection: When? • Context of reflection: In which? • Topic/data as object for reflection: Which? • Motivation for reflection: Why?
- 17. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics DATA 17 Data-Driven and Reflective Learning • Can be anything and is not limited to • … mood data • … work activities • … search activities • … sports/fitness data • … knowledge • … • … your data?
- 18. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics Reflect about your… Work Activities Knowledge Mood Search Behaviour Learning Progress … working activities to become an expert in time management and self-organisation … knowledge to become an expert in your domain. … mood and your team‘s mood to become aware of how emotions affect our work. … search behaviour to become an effective and efficient search expert. … learning progress to become expert in information literacy and digital competences. Demo Demo Demo
- 19. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics DEMOS …. 19 • Medical Quiz • https://www.know-center.tugraz.at/en/showcase/medical-quiz-2/ • MOVING • https://moving.mz.tu-dresden.de/
- 20. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics INDIVIDUAL ASSIGNMENT 20 • How does this relate to your PhD? • Reflective Learning Technologies … • Data-driven reflection… • Adaptive/context aware systems… • Intelligent mentoring/tutoring… • User models/learner models … • Note down your ideas • Present and discuss it afterwards with the groups
- 21. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics TIME MANAGEMENT …. 21 • Participate in the Study on „TimeManagement“ • http://tiny.cc/timeTool What‘s in it for you? Reflect on your time management – and if you have no need for that, do share your secret with everyone this week.
- 22. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics References • (Brusilovsky & Peylo, 2003) Brusilovsky, P. & Peylo, C. (2003) Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education (IJAIED), 2003, 13, pp.159-172. hal-00197315. • (Brusilovsky & Millán, 2007) Brusilovsky, P., and Millán, E. User models for adaptive hypermedia and adaptive educational systems. In The Adaptive Web, P. Brusilovsky, A. Kobsa, and W. Nejdl, Eds. Springer-Verlag, Berlin, Heidelberg, 2007, ch. User Models for Adaptive Hypermedia and Adaptive Educational Systems, 3–5. • (Brusilovsky, 2012) Brusilovsky, P. Adaptive hypermedia for education and training. In Adaptive Technologies for Training and Education, P. J. Durlach and A. M. Lesgold, Eds. Cambridge University Press, 2012, 46–66. Cambridge Books Online.(Dimitrova et al., 2016) Dimitrova, V., Poulovassilis, A., Van Labeke, N., Treasure-Jones, T., Zukas, M., & Brna, P. (2016). Intelligent Mentoring Systems for Making Meaning from Work Experience. In Proceedings of First International Workshop on Intelligent Mentoring Systems (IMS 2016). Leeds. • (Dimitrova et al., 2016) Dimitrova, V., Poulovassilis, A., Van Labeke, N., Treasure-Jones, T., Zukas, M., & Brna, P. (2016). Intelligent Mentoring Systems for Making Meaning from Work Experience. In Proceedings of First International Workshop on Intelligent Mentoring Systems (IMS 2016). Leeds. • (Dimitrova & Brna, 2016) Dimitrova, V., & Brna, P. (2016). From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond. International Journal of Artificial Intelligence in Education, 26(1), 332-349. • (Fessl et al., 2017a) Fessl, A., Blunk, O., Prilla, M., & Pammer, V. (2017). The known universe of reflection guidance: a literature review. International journal of technology enhanced learning, 9(2-3), 103-125. • (Fessl et al., 2017b) Fessl, A., Wesiak, G., Rivera-Pelayo, V., Feyertag, S., & Pammer, V. (2017). In-app reflection guidance: lessons learned across four field trials at the workplace. IEEE Transactions on Learning Technologies, 10(4), 488-501. • (Kocielnik et al., 2018) Kocielnik, R., Xiao, L., Avrahami, D., & Hsieh, G. (2018). Reflection Companion: A Conversational System for Engaging Users in Reflection on Physical Activity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(2), 70. • (Davis, 2000) Davis, E. A. (2000). Scaffolding students' knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22(8), 819-837. • (Lindström et al., 2006) Lindström, M., Ståhl, A., Höök, K., Sundström, P., Laaksolathi, J., Combetto, M., ... & Bresin, R. (2006, April). Affective diary: designing for bodily expressiveness and self-reflection. In CHI'06 extended abstracts on Human factors in computing systems (pp. 1037-1042). ACM. • (Ståhl, et al. 2009) Ståhl, A., Höök, K., Svensson, M., Taylor, A. S., & Combetto, M. (2009). Experiencing the affective diary. Personal and Ubiquitous Computing, 13(5), 365-378. • (Glahn et al., 2009) Glahn, C., Specht, M., & Koper, R. (2009). Visualisation of interaction footprints for engagement in online communities. Educational Technology & Society, 12 (3), 44–57. • (Malacria et al., 2013) Malacria, S., Scarr, J., Cockburn, A., Gutwin, C., & Grossman, T. (2013, October). Skillometers: reflective widgets that motivate and help users to improve performance. In Proceedings of the 26th annual ACM symposium on User interface software and technology (pp. 321-330). ACM. • (Prilla et al., 2013) Prilla, M., Nolte, A., Blunk, O., Liedtke, D., & Renner, B. (2015). Analyzing collaborative reflection support: a content analysis approach. In ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway (pp. 123-142). Springer, Cham. 22
- 23. © Know-Center GmbH • Research Center for Data-Driven Business and Big Data Analytics References • (Fessl et al., 2017a) Fessl, A., Blunk, O., Prilla, M., & Pammer, V. (2017). The known universe of reflection guidance: a literature review. International journal of technology enhanced learning, 9(2-3), 103-125. • (Fessl et al., 2017b) Fessl, A., Wesiak, G., Rivera-Pelayo, V., Feyertag, S., & Pammer, V. (2017). In-app reflection guidance: lessons learned across four field trials at the workplace. IEEE Transactions on Learning Technologies, 10(4), 488-501. • (Rivera-Pelayo et al., 2017) Rivera-Pelayo, V., Fessl, A., Müller, L., & Pammer, V. (2017). Introducing mood self-tracking at work: Empirical insights from call centers. ACM Transactions on Computer-Human Interaction (TOCHI), 24(1), 3. • (Kocielnik et al., 2018) Kocielnik, R., Xiao, L., Avrahami, D., & Hsieh, G. (2018). Reflection Companion: A Conversational System for Engaging Users in Reflection on Physical Activity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2(2), 70. • (Davis, 2000) Davis, E. A. (2000). Scaffolding students' knowledge integration: Prompts for reflection in KIE. International Journal of Science Education, 22(8), 819-837. • (Lindström et al., 2006) Lindström, M., Ståhl, A., Höök, K., Sundström, P., Laaksolathi, J., Combetto, M., ... & Bresin, R. (2006, April). Affective diary: designing for bodily expressiveness and self-reflection. In CHI'06 extended abstracts on Human factors in computing systems (pp. 1037-1042). ACM. • (Ståhl, et al. 2009) Ståhl, A., Höök, K., Svensson, M., Taylor, A. S., & Combetto, M. (2009). Experiencing the affective diary. Personal and Ubiquitous Computing, 13(5), 365-378. • (Glahn et al., 2009) Glahn, C., Specht, M., & Koper, R. (2009). Visualisation of interaction footprints for engagement in online communities. Educational Technology & Society, 12 (3), 44–57. • (Malacria et al., 2013) Malacria, S., Scarr, J., Cockburn, A., Gutwin, C., & Grossman, T. (2013, October). Skillometers: reflective widgets that motivate and help users to improve performance. In Proceedings of the 26th annual ACM symposium on User interface software and technology (pp. 321-330). ACM. • (Prilla et al., 2013) Prilla, M., Nolte, A., Blunk, O., Liedtke, D., & Renner, B. (2015). Analyzing collaborative reflection support: a content analysis approach. In ECSCW 2015: Proceedings of the 14th European Conference on Computer Supported Cooperative Work, 19-23 September 2015, Oslo, Norway (pp. 123-142). Springer, Cham. 23
- 24. © 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: Researcher afessl@know-center.at Angela Fessl Head of Data-Driven Busniess vpammer@know-center.at Viktoria Pammer-Schindler 24