Application overlapping user profiles to foster reflective learning at work.
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Reflective learning is an important activity of knowledgeworkers in order to improve future working-behaviours. The insights gained by reflective learning are based on re-experiencing and re-evaluating past working situations. One time- and cost-e ective way to support reflective learning is the employment of applications that collect data about working processes, store the data in user proles, and visualise it in order to provide timely feedback to the employees. However, a single application can only capture part of the data that might be relevant for reflection and the parallel use of several applications leads to high demands on the user regarding the interpretation of relationships between several single visualizations. A combined visualisation of data captured by di erent apps should enhance the support for reflection about the working behaviour and experiences. This paper introduces an overlapping user prole application, which combines and aggregates data captured by various applications. The goal of this overlapping application is to provide higher-level reflection possibilities by combining visualisations of di erent application data in order to better induce and support reflective learning at work. A rst proof-of-concept of such an approach indicates that a combined user prole application and especially it's visualisations can be benecial with regard to reflective learning and can enhance the awareness about the multiple aspects of a user's work life.
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Application overlapping user profiles to foster reflective learning at work.
- 1. Application overlapping user profiles to foster reflective learning at work Angela Fessl, Gudrun Wesiak, and Granit Luzhnica 16. September 2014 ARTEL Workshop, EC-TEL 2014, Graz, Austria © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 2. Agenda ▪ The MIRROR Project ▪ Motivation ▪ MIRROR Applications: 2 Examples ▪ MIRROR User Profile Application (MUP) ▪ Proof of Concept ▪ Future Work © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 3. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 4. MIRROR – Reflective Learning at Work Informales Lernen am Arbeitsplatz durch Reflektion über Arbeitser-erfahrungen Scientific partners EU IST FP7 Integrated Project © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu Test-bed partners Informal learning in the workplace through reflection on work experience.
- 5. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 6. Motivation ▪ Thus, reflective learning has become an important activity of knowledge-workers to … ▪ re-experience past situations ▪ reflect upon their activities and ▪ improve future working behaviour ▪ Work-integrated reflection tools and applications can … ▪ gather and present work-related data ▪ raise awareness and trigger reflection during work ▪ motivate and remind employees to reflect © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 7. Motivation ▪ MIRROR Apps support reflective learning at work … ▪ for individuals, teams, and organisations ▪ at different phases of the reflection process ▪ in different organizational settings ▪ General set-up of app-support in MIRROR ▪ single apps collect and visualize data regarding certain aspects of work ▪ MUP-App intends to … ▪ increase benefit by combining different data sources ▪ presents a broader view of work/life © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 8. Research Questions ▪ RQ1: Are participants interested and willing to use more than one application in parallel with regard to reflective learning? ▪ RQ2: Does the MUP App as overlapping application facilitate reflection about users' working experiences and contribute to raising awareness of multiple aspects of their work life? ▪ RQ3: Do participants perceive any individual insights or benefits for themselves? © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 9. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 10. MoodMap App (http://moodmapapp.com) © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu ▪ UP: mood data ▪ Valence: positiv - negative feelings ▪ Arousal: low - high energy ▪ Notes + Context ▪ Timestamp ▪ Development with
- 11. KnowSelf (http://www.know-center.at/knowself/) © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu ▪ UP: KnowSelf data: ▪ Used applications ▪ Used resources ▪ Duration of usage ▪ Timestamp
- 12. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 13. Goal: Application Overlapping User Profiles App Aggregated data App App App App App App App data App MSF © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu MUP App
- 14. Prerequisites and assumptions for MUP ▪ Data: ▪ About the user, private data and shared data; ▪ User: full control about own data ▪ Reusability: ▪ Predefined data format; ▪ Apps: reuse own data and data from other apps ▪ Sharing: ▪ Relevant for comparison ▪ Different levels of sharing (e.g. colleagues or team) ▪ Privacy & Security ▪ Defined by & in full control of the user through settings UI ▪ Aggeragtions and visualisations conform user‘s settings © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 15. High level tasks of MUP ▪ Task 1: Data retrieval ▪ Access and fetch data captured in the underlying data storage system (MIRROR Spaces Framework) ▪ Task 2: Aggregation and visualisation of data ▪ Data aggregation service: ▪ Multi-user, cross-application ▪ Visualisation of data ▪ Present data to trigger reflection ▪ Individual and/or collaborative level © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 16. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 17. Goal: Application Overlapping User Profiles KS & MMA data MSF © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu MUP App MAA KnowSelf
- 18. First Approach ▪ Combine different application data ▪ Find out relationship between data e.g. mood and working patterns © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 19. Proof of concept: Setting ▪ 6 knowledge workers (3 women, 3 men) ▪ MoodMap App & KnowSelf ▪ Usage for 2 weeks in parallel ▪ Tasks (daily reminder): ▪ Re-evaluate and reflect about data ▪ Write down insights ▪ Evaluation Tools ▪ Online-Questionnaire ▪ About features, functionality, usage, and reflective learning ▪ Interviews: ▪ Presentation of combined statistics ▪ Questions about insights and benefits © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 20. Proof of Concept: Results ▪ Relationship between mood (valence and energy), app usage, and working activities © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 21. Proof of Concept: Results ▪ RQ1: Are participants interested and willing to use more than one application in parallel with regard to reflective learning? ▪ Interest in getting support for time management (Md=4.0) ▪ Interest in capturing working activities, own mood and team mood (Md = 3.5) ▪ Participants (all Md = 4.0) ▪ found the applications easy to use ▪ liked the visualisations ▪ rated the presentation of information as comprehensible ▪ Source: Questionnaires, 5 pt. agreement scale © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 22. Proof of Concept: Results ▪ RQ2: Does the overlapping MUP App facilitate reflection and raise awareness of how different aspects of their work life could be related? ▪ Combination of data can foster reflection by, e.g. : ▪ Compare number of applications used and arousal development ▪ Reveal working patterns ▪ Reveal relationship between activities and mood ▪ Trigger to reflect on own and teams ▪ Arousal level is low in the morning but increases during the day © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 23. Proof of Concept: Results ▪ RQ3: Do participants perceive any individual insights or benefits for themselves? ▪ Fluctuation of the arousal and valence level ▪ Falling arousal -> small breaks to recover ▪ Self-estimation about working day ▪ Confirmation of some aspects of users‘ self-estimation, but also … ▪ Surprise: six – seven hours in the office, only four hours in front of the computer © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 24. General Discussion ▪ MUP has potential to ▪ facilitate individual reflective learning ▪ raise overall awareness of users‘ work life ▪ give insights about the relationship between working activities and mood ▪ All participants gained individual insights ▪ Automatic data capturing (KS) vs. manual mood capturing (MMA) ▪ Time for reflection © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 25. © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 26. Future Work ▪ Comprehensive evaluation ▪ Add more applications ▪ Add more combined sophisticated visualisations ▪ Derive more triggers for reflection ▪ Implement privacy and security features © MIRROR Project - Co-Funded by EU IST FP7 – www.mirror-project.eu
- 27. More about MIRROR ... http://www.mirror-project.eu Try out MUP at ... Angela Fessl, Gudrun Wesiak, Granit Luhznica https://mirror-demo.eu/mup {afessl, gwesiak, gluhznica} @ know-center.at © MIRROR Project - Co-funded by EU IST FP7 - www.mirror-project.eu Know-Center GmbH Inffeldgasse 13 8010 Graz
Notes de l'éditeur
- Today‘s working environments … are complex, globally integrated and knowledge-centric require employees to repeatedly adjust to new demands
- at different phases of the reflection process (collect data, initiate and conduct reflection session, apply outcome) in different organizational settings (business, health, emergency sectore)
- MSF – Open Source available
- For the development of a common user prole based on the MIRROR spaces the following prerequi- sites have to be considered: assumptions regarding (i) data, (ii) reusability, (iii) sharing, (iv) privacy and security, and (v) accessibility by the user interfaces.
- The aggregated data can be used to raise awareness on relationships between data captured from different applications, make comparisons along a timeline or among different users, and finally detect patterns that are relevant for individual or collaborative reflection. Reasons for reflection can encompass the need for problem solving, decision-making, emotion regulation, or detection of significant deviations between the individual user and a team.
- As an example, the left of Fig. 2 shows the hourly application usage history of a single user for both KnowSelf and the MoodMap App. The picture on the right of Fig. 2 visualises combined application specic data, namely the number of hourly switches between tasks or resources captured by KnowSelf and the corresponding mood of a user, depicted as separate lines for arousal (mood.energy) and valence (mood.feel) by the MoodMap App. For this visualization, mood values from the MoodMap App depicted in Fig. 1 are expressed as numbers between 0 and 100.
- We used descriptive statistics due to the low participants number Only data points from 5 participants! Thus to be interpreted with much caution!!! App usage: positive relationship between MMA use and mood (higher valence / higher energy related to higher number of moods entered per day); No trend found for Knowself use and mood; Working activities: Higher valence (blue line) connected to longer times between switches (lower switching frequencies) Higher energy connected to more used resources
- * Start day with reading emails Subsequent increase of application switches and arousal level indicates actual start of work *Switches and valence (few switches, higher valence)
- Although she was six to seven hours in the office she spent only four hours in front of her computer. Only after comparing this awareness with her dates in her calendar, she could reproduce her day and explain why this happened.
- While KnowSelf captures automatically the resources and applications used on the PC, the moods need to be inserted manually. Having to repeatedly insert a mood in a web based application can distract from the normal working process. One recommendation to alleviate this distraction was to add five different smileys in the system tray to facilitate the mood capturing. All of the participants perceived the combination of the data captured by the MoodMap App and KnowSelf as useful, because they could check at all times what they were doing during work and how they felt. However, one participant stated that it was not very useful to reflect on how she felt three days ago, but that it was more interesting to become aware of her mood in relation to her work directly while working. For other participants especially the knowledge of how they felt for example three days ago was very important. Especially when the mood could be directly related to the mood note, used applications or used resources. A rather interesting statement from one of the participants was that her working tasks did not influence her mood at all.