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Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
Experience Centered Design of Energy Interventions for Shared Student Accommodation
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Experience Centered Design of Energy Interventions for Shared Student Accommodation

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Full paper presentation given at the CHI Sparks HCI conference.

Full paper presentation given at the CHI Sparks HCI conference.

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  • Just so know what to expectWe worked with students so some of the quotes should not come as a shock to you!
  • A taster of the data we found
  • Now we are going to talk about the study and what we didFirst some contextSome background on the HCI litertuare around sustainability studiesOur study approach and reasoningMethods used in the studyResults
  • The challenge was designed to address the lack of intervention
  • What has HCI down around sustainability
  • Our domestic work (Wattsup and Power Ballads) allowed us to understand the use of social media to engage householders on the topic of energy usage with others.Both papers showed good engagement with the applications.Only Wattsup measured power consumption.Power Ballads measured engagement levels through Google Analytics data and server logs.
  • More feedback
  • Our domestic work (Wattsup and Power Ballads) allowed us to understand the use of social media to engage householders on the topic of energy usage with others.Both papers showed good engagement with the applications.Only Wattsup measured power consumption.Power Ballads measured engagement levels through Google Analytics data and server logs.
  • Our domestic work (Wattsup and Power Ballads) allowed us to understand the use of social media to engage householders on the topic of energy usage with others.Both papers showed good engagement with the applications.Only Wattsup measured power consumption.Power Ballads measured engagement levels through Google Analytics data and server logs.
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • The challenge was designed to address the lack of intervention
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • What has HCI down around sustainability
  • Transcript

    • 1. “Experience Centered Design of Energy Interventions for Shared Student Accommodation” Conor Linehan, Derek Foster, Shaun Lawson Maureen Schoonheyt, Katrin Heintze Email: defoster@Lincoln.ac.uk @derekfoster
    • 2. “One participant told me that instead of getting his window fixed he just turned his heating on more often” “participant one has no interest in the consequences of their actions” “I save energy to save money, not the planet” “meh” ?
    • 3. Sustainable?
    • 4. Overview • Context • Background • Study Approach • Method • Results
    • 5. University of Lincoln • UK University in Lincoln, England • 1037 students across 17 ‘official’ accommodation blocks 1,734,020 kg 6,007,972 kWh 1,202,693 kWh £300,508 p.a
    • 6. Why? • Promote more sustainable energy-use practices in official student accommodation • Lower UoL CO2 footprint and support UoL strategic plan for improved sustainability engagement • Embed sustainability in the curriculum at UoL • Contribute to corpus of HCI sustainability literature
    • 7. Background • HCI sustainability research suggests people have a poor understanding of their consumption habits* • Evolution of energy monitors has rebooted digital monitoring for the home focussing on feedback • Environmental psychology studies indicate that feedback can motivate reductions • So HCI + Psychology == behaviour change interventions for sustainable practices? • Sounds great in principle, but what about the practical application of such interventions? • Bates, O., Clear, A. K., Friday, A., Hazas, M., & Morley, J. Accounting for energy-reliant services within everyday life at home. In Proc Pervasive Computing (2012), 107-124. • Darby, S. (2006). The effectiveness of feedback on energy consumption. A Review for DEFRA,486, 2006. • Toth, N., Little, L., Read, J. C., Fitton, D., & Horton, M. (2012). Understanding teen attitudes towards energy consumption. Journal of Environmental
    • 8. Anton Gustafsson and Magnus Gyllenswärd. 2005. The power-aware cord: energy awareness through ambient information display. In CHI '05 extended abstracts on Human factors in computing systems (CHI EA '05). ACM, New York, NY, USA, 1423-1426. Petkov, Petromil, Köbler, Felix, Foth, Marcus, & Krcmar, Helmut (2011) Motivating domestic energy conservation through comparative, community-based feedback in mobile and social media. In Proceedings of the 5th International Conference on Communities & Technologies (C&T 2011), ACM, Brisbane, pp. 21-30. Background • Mobile and ambient monitoring systems
    • 9. • Domestic energy studies delivering socially-mediated live energy feedback on social platforms* Background Derek Foster, Shaun Lawson, Mark Blythe, and Paul Cairns. 2010. Wattsup?: motivating reductions in domestic energy consumption using social networks. In Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries (NordiCHI '10). ACM, New York, NY, USA, 178-187. Derek Foster, Conor Linehan, Shaun Lawson, and Ben Kirman. 2011. Power ballads: deploying aversive energy feedback in social media. In
    • 10. Background Injunctive Norm (Is your consumption good or bad?) Descriptive Norm (How much energy are you using compared to others?)
    • 11. Jon Froehlich, Leah Findlater, Marilyn Ostergren, Solai Ramanathan, Josh Peterson, Inness Wragg, Eric Larson, Fabia Fu, Mazhengmin Bai, Shwetak Patel, and James A. Landay. 2012. The design and evaluation of prototype eco-feedback displays for fixture-level water usage data. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '12). ACM, New York, NY, USA, 2367-2376. Matthias Laschke, Marc Hassenzahl, Sarah Diefenbach, and Marius Tippkämper. 2011. With a little help from a friend: a shower calendar to save water. In CHI '11 Extended Abstracts on Human Factors in Computing Systems (CHI EA '11). ACM, New York, NY, USA, 633-646. Background • Domestic water monitoring visualisation
    • 12. Eric B. Hekler, Predrag Klasnja, Jon E. Froehlich, and Matthew P. Buman. 2013. Mind the theoretical gap: interpreting, using, and developing behavioral theory in HCI research. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). ACM, New York, NY, USA, 3307- 3316. Jon Froehlich, Leah Findlater, and James Landay. 2010. The design of eco-feedback technology. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 1999-2008. Carl DiSalvo, Phoebe Sengers, and Hrönn Brynjarsdóttir. 2010. Mapping the landscape of sustainable HCI. In Proceedings of the SIGCHI Conference on Background • HCI sustainability review papers
    • 13. Background • Froehlich et al review paper revealed a number of issues with HCI sustainability studies: • Short study length • - no longitudinal return to baseline • - novelty effect • Difficult to validate behaviour change • Lack of evidenced-based behaviour change methods • Highlighted importance of working with psychologies to help bridge the theory-design gap • It’s very hard to do!
    • 14. Background • Some limited HCI research has been undertook that looks at student energy consumption habits* • Mainly feedback interventions • Findings indicated environmental concerns were not a priority Oliver Bates, Adrian K. Clear, Adrian Friday, Mike Hazas, and Janine Morley. 2012. Accounting for energy-reliant services within everyday life at home. In Proceedings of the 10th international conference on Pervasive Computing (Pervasive'12), Judy Kay, Paul Lukowicz, Hideyuki Tokuda, Patrick Olivier, and Antonio Krüger (Eds.). Springer-Verlag, Berlin, Heidelberg, 107-124. Odom, W., Pierce, J., & Roedl, D. Social Incentive & Eco-Visualization Displays: Toward Persuading Greater Change in Dormitory Communities. In Workshop Proc. OZCHI (2008).
    • 15. Study Approach • Builds upon previous HCI research in area • Study adopted both a participatory design and practitioner-led inquiry approach • 100 students were recruited as ‘practitioner researchers’ who recruited a further 300 participants • Experiential data elicited to inform design process • Large body of data collected • Thematic analysis carried out on data by authors of this work to identify clusters of experiences, perceptions and attitudes
    • 16. Study Approach “Design a technology-led and socially-enabled energy intervention; that is both engaging and cool, for students in official accommodation blocks, that encourages more sustainable energy-use practices.“ • A design challenge was presented, the focus of all research carried out by the student practitioners:
    • 17. Study Approach • Researchers were presented with the design challenge • User experience-centred practices were used to understand and address the challenge • Focus groups were initially conducted in order to elicit user requirements for the design challenge • A variety of techniques were used within the focus groups
    • 18. Study Approach • 100 focus groups carried out semi-structured interviews, 53 questionnaires, 40 card sorting, 26 particapatory design tasks, 15 diary studies, 13 cultural probes, 4 cool walls, 4 0 10 20 30 40 50 60 Instances of technique used in focus groups
    • 19. Study Approach • Each researcher produce a thematic analysis of their focus group data and paper prototype • Each thematic analysis carried out produce 3 themes, typically with one paragraph describing each theme • The authors then carried out an inductive thematic analysis on all of the researchers themes as one corpus of data • The data presented next represents both the subjective, experiential information from participants, plus our interpretation of the data
    • 20. Better connected?
    • 21. Better connected?
    • 22. Study Approach • Unit of analysis at sentence level • 1,760 units analysed • First pass created 87 conceptual labels • These were grouped on similarity to create 34 categories • A further pass created 5 distinct categories • All labels grouped under one of the main categories
    • 23. Results • 146 labelsStudent Experience • 232 labelsEnergy Consumption • 291 labelsBarriers to Saving • 209 labelsBehavioural Solutions • 450 labelsDesign Suggestions
    • 24. Results • From a purely descriptive perspective we can see that discussion around the design aspects of the challenge were the most common • Can also see there was a lot of discussion around barriers to saving energy – more on this later! • Can look upon these 5 distinct categories as the design implications for student energy interventions • Example quotes from each category are now discussed
    • 25. Results Student Experience socialisin g drinking alcohol computer games using social media cool YOL
    • 26. Results Energy Consumption “With each student spending the majority of time in their rooms…. each room will have electrical appliances/devices turned on, on standby or charging up” “most of the time the students are at home…. some kind of technology is always being used” “One participant told me that instead of getting his window fixed he just turned his heating on more often”
    • 27. Results Barriers to Saving “students may not be too familiar with existing terminology or whether their current energy consumption level is particularly high or low” ” “there is not a defined scale of how much I should and shouldn‟t be using” “the fact that we don‟t have to pay just makes us like „meh, we might as well make the most of it‟”
    • 28. Results Behavioural Solutions “A reward system whereby at the end of each month, the person who saved the most is rewarded” “the best way of making people change their behaviour is to turn it into a competition” “£50 to everyone in the flat that saves the most energy…”
    • 29. Results Design Suggestions “Although this is a good idea one of the disadvantages could be that there may be rebellious students who want to boast how much energy they can use” “With each student spending the majority of time in their rooms…. each room will have electrical appliances/devices turned on, on standby or charging up” “a method of turning a light bulb off without them interacting with it”
    • 30. Results • Breadth and scope of experiences and reflections is powerful – sometimes at odds with itself • Thematic analysis supports ‘making sense’ of chaotic qualitative data • Realistic and grounded findings of the barriers to successful intervention uptake and adherence • One size does not fit all* • A novel approach that promotes openness in the complex area of energy use practices Helen Ai He, Saul Greenberg, and Elaine M. Huang. 2010. One size does not fit all: applying the transtheoretical model to energy feedback technology design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 927-936.
    • 31. Results • Each theme produces a cluster of related user- requirements or design implications • Requirements can be used to design energy interventions across pilot studies • Currently working on implementing a range of pilot interventions from findings • Developed an opendata platform to publish Lincoln accommodation energy data to open standards, every 30 minutes Helen Ai He, Saul Greenberg, and Elaine M. Huang. 2010. One size does not fit all: applying the transtheoretical model to energy feedback technology design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 927-936.
    • 32. Thanks! Derek Foster Lecturer in Computer Science Lincoln Social Computing (LiSC) Research Centre School of Computer Science University of Lincoln Email: defoster@Lincoln.ac.uk @derekfoster Questions?

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