1. 2014 Empowering the People (ACM SigCHI) Margaret Burnett Oregon State University October 2014 #GHC14 2014

2. A Bit About Me  Great year for ACM SigCHI @ GHC −1 st year of HCI @ GHC. −Co-chaired by Jamika Burge & me.  Other hats: −Papers Co-Chair for CHI’08 −NCWIT AA Advisory Board −Research: HCI of Software Development Co-founded 2 HCI areas End-user software engineering & Gender HCI

3. 2014 What is End-User Software Engineering?  EUPing: EUDer “create” new programs.  EUSE: EUP + rest of software lifecycle  “enough” dependability.

4. 2014 End Users’ “IDEs” 4  CoScripter [Cypher et al.]

5. 2014 End Users’ “IDEs” 5  LabView [National Instruments]

6. 2014 First(?) EUSE example: WYSIWYT Cell turns more blue (more “tested”). At any time, user can check off correct value. Testing also flows upstream, Coloring other affected cells too. If this value is right, √ it; if it’s wrong, X it. This testing helps you find errors.

7. 2014 Where to take EUSE next? Beyond the Silos  Silo: “a system, process,... that operates in isolation from others”  Silo risk: −tunnel vision −lose potential for big, outside-the-box gains.  Challenges/benefits for de-siloing future EUSE: −“Who” challenges −“When” challenges −“Why/How” challenges 7 Design Testing Requirements

8. 2014 Who: Some Basics  2 Key Requirements of EUSE: −1. Cannot assume SE skills −2. EUSE tools/techniques must fit EUDs’: motivations & practices  But, what else do we know about them? 8

9. 2014 Empirical answer: Targeted studies  tools  Study target audience. eg: −Teachers [Wiedenbeck], designers [Rosson, Myers],...  Reveals important information! −resulting tools fit these folks’ motivations & practices.  But not enough... −Each population research separate. −Siloes knowledge by population. 9 Teachers Designers Children

10. 2014 Intent to De-silo “Who”  Difference Professional devs vs. EUDs: −Intent, not (necessarily) experience [Nardi, Ko]. −EUD becomes a situation/role not an identity [Ko].  Insight: intent nuances “who”: −Expands “who”: people with or without programming experience when little interest in SE. 10

11. 2014 Intent as a basis of de-siloing  Challenge: Make EUSE tools about an end-user developer’s actual intent.  E.g: medical scientist’s lab application to collect sensor data. −Intent ≅ : “fix my broken lab application”? −Not: “find new tool that might give me ways to guard the quality of my application”. 11

12. 2014 Intent & Attention Investment  Lab example (intent=fix my bug quickly): −Suppose her usual problem-solving method = edit & test. So, find/fix the bug that way. −Perceived benefit: fixes the problem! −Perceived costs, risk: No learning cost, no risk. −Use some fancy new tool instead? Only if scientist thinks: Risk!! problem too hard to fix without the tool 12

13. 2014 Intent & Attention Investment 13  Now... suppose scientist looks for a more powerful problem-solving tool −and spots a tool that might help.  Ventures to touch one. In 1 glance: −Perceives a cost (time to learn & then use). −Perceives risk that tool will be a waste of time. −If perceived costs/risks > benefits, unlikely to use the tool [Blackwell].

14. 2014 How we can use this: 3 intent-based strategies  1. Research-then-serve existing intent. E.g. “why” debugging [Ko, Myers] 14

15. 2014 How: 3 intent-based strategies  2. Infer-then-serve intent.  E.g.: IdeaGarden [Cao, Fleming, Scaffidi, Burnett,...] 15

16. 2014 How: 3 intent-based strategies  3. Try to generate intent.  E.g. Gidget [Lee, Ko, et al.] 16

17. 2014  These examples have in common: −(1) target EUD intent as of “right now” −(2) draw EUD into doing just a little when can benefit them directly make clear potential costs, benefits, risks −(3) give EUD supports just in time, in their own environment allows them to succeed at behaviors  These strategies work! (empirical) −seem to point ways forward. Intent-based strategies 17

18. 2014 Speaking of “who”… Gender HCI  Gender & software tools for problem-solving: −spreadsheets, −debugging tools, −... Q: Would females & males be more effective if tools took gender differences into account? Q: Would females & males be more effective if tools took gender differences into account?

19. 2014 A: Yes!  10+ yrs empirical research across populations: (~3000 people) −WHICH features −Tinkering −Motivations & attitudes −Strategies...  But NOT separate tools. −Rather, take down barriers, one at a time, to help everyone. pink blue pink

20. 2014 Where next with Gender HCI  Goal: To make a difference −to women and men who use today’s & tomorrow’s software.  Interested? −You can join in with this −with your software for problem-solving or reasoning −Here’s how.

21. 2014 Introducing … GenderMaP  A method to find usability issues through a gender lens.  “Kit” consisting of: −GenderMaP Cognitive Walkthrough & GenderMaP Persona.  Ready for early adopters to try this!  http://eusesconsortium.org/gender/ http://eusesconsortium.org/gender/

22. 2014 More Information  Gender HCI resources & GenderMaP kit: −http://eusesconsortium.org/gender/http://eusesconsortium.org/gender/  End-User Software Engineering resources −http://eusesconsortium.org/http://eusesconsortium.org/  My papers on these topics: −http://web.engr.oregonstate.edu/~burnett/reprints.htmlhttp://web.engr.oregonstate.edu/~burnett/reprints.html  Me: −http://web.engr.oregonstate.edu/~burnett/http://web.engr.oregonstate.edu/~burnett/

23. 2014 Conclusion: Empowering People  Requires hard thinking about the assumptions behind our software.  “Who” challenges: −1. EUD as an intent: Opens door to intent- oriented operations Manipulate & reward intent, infer intent, target intent... −2. From gender differences to tool design: A gender lens can help everyone  Not easy, but worth it! 23

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