1. Universal Access to Programming Mary Beth Rosson Department of Computer Science Virginia Tech

2. March 20012 Computer literacy has changed a basic skill of being a citizen  ATMs, grocery self-check, EFT, email pervasive impacts of the Internet  just-the-right, just-in-time information has become the norm  anyone can author a Web page tremendous hype but also potential

3. March 20013 Is end user programming next? i.e., beyond accessing or exchanging information—> creating and connecting computational entities opportunities for end user programming are diverse and growing:  hords of data ready for analysis  building and customizing workflows  project-based inquiry learning  sophisticated & demanding gaming world

4. March 20014 EUP is not a new problem promising approaches, some success  spreadsheets, special-purpose languages, construction kits, constraints and PBD largely technique-centered  visual or text-based? natural language or not? how much domain-specificity? need a broader, more inclusive view  who will be the EUP-ers, what will they be doing, and why?

5. March 20015 Extending the scope of EUP taking an activity-centered view  what you can get done, rather than what programming concepts you know reaching out to non-obvious populations  people at work, but also doing tasks at home or in the community assuming, leveraging, personal initiative  intrinsic motivation, self-paced learning sharing, co-development, and reuse

6. March 20016 1: EUP as a learning activity Learn about a topic by programming and debugging a personal model. Papert’s classic microworld approach  contains problem objects and relations  should be engaging, fun, provoking configure, run, refine to investigate ideas  learn flexible, open-ended analysis and design along with specific content

7. March 20017 Example: Agentsheets white cloud dark cloud water vapor rain drops sun sun rays lake puddle grass desert water evaporates, is absorbed, rains, etc.

8. March 20018 Sample rules - left-hand specifies a “before” state - right-hand specifies one or more actions to take if state is confirmed - multiple rules are tested in order, first match fires

9. March 20019 But what about the activity? Technology must first be learned and appropriated by classroom teachers teachers define and guide projects, but...  they learn technology only if value is clear  even then, little time to learn new tools  little time to use new skills that are learned supporting the activity has to start with the teachers’ learning and use needs

10. March 200110 A minimalist approach generalizing earlier work w/Smalltalk  emphasis is on quick start-up & success example-based, realistic simulations  water cycle as primary learning example

11. March 200111 Reprise: water cycle model - cloud absorbs vapor, turns into dark cloud; rains and turns back to white cloud. - ground cycles from desert to grass, to a puddle and finally to a lake as it absorbs water - lake produces water vapor, eventually transforming to puddle, grass, desert as water content decreases

12. March 200112 A minimalist approach generalizing earlier work w/Smalltalk  emphasis is on quick start-up & success example-based, realistic simulations  water cycle as primary learning example sparse instructions, learn by doing  forces inference, making-sense  empirical test-iteration to optimize

13. March 200113 maybe show a page of tutorial make sure it has the model in it? Exploring a Water Cycle Double click on the Agentsheets WaterCycle icon.  A water cycle gallery and worksheet open. What do you think are the “agents” in this worksheet? Now, this model for a few minutes, and then it.  Watch the simulation. What actions are taking place? The water cycle demonstrates ecological interactions. There are lake agents that release moisture (water vapor) that the cloud absorbs. As the cloud absorbs more water vapor it turns into a dark cloud. Once a cloud is dark it produces raindrops. The sun emits sunrays that will evaporate water from the lake. When the sunrays have evaporated some moisture this will change the lake into a pond. All of the agents in this simulation are interdependent, and portray a simplified version of a water cycle in the real world. Be sure you have stopped the simulation before you continue. Add more agents to the simulation (e.g., more clouds, another sun).  To add an agent, first select it in the gallery. Then select the worksheet, and after making sure the pencil tool is selected, click to show where you want the agent. Try out your changes. AgentSheets Tutorial © Virginia Tech Visual Languages Group-Draft

14. March 200114 Learning outcomes 60-90 minutes, explored and extended water cycle, built new volcano models but much variability, problems due to both visual language and design

15. March 200115 Visual language issues attaching semantics to side-effects how to model non-visual elements specifying visual constraints  spatially-distributed relations; cases where spatial relation is simply not important managing screen space  palettes of actions and conditions, view of individual agents, the “program”,... e.g., careful positioning and build-up of “result”

16. March 200116 General design issues converting an episode into an ensemble of interacting agents  from a scenario to a general solution decomposing and distributing individual responsibilities  character creation and destruction  passing on the thread of control  ordering competing rules within an agent

17. March 200117 Can we promote reuse? A second minimalist tutorial  walked through reuse of cloud agent  then given concrete versus abstract model: to reuse in creating new (ocean) world

18. March 200118 Reuse outcomes Reuse tried but not always successful  trouble parsing, translating reusable agents  abstract example seemed to work better P4 (Ozone) P5 (Starter) - carefully studies Ozone agents - but developed ocean agents from scratch, “I found it easier to create new ones—a bit less confusing” - infers Starter behavior from names, testing - “an ocean that makes waves would be similar... an ocean might be the emitter.” - proceeded to model ocean on emitter, wave on mover, and sand on transformer Teacher Summary of reuse efforts

19. March 200119 Implications, ongoing work exploring new tools and techniques  combining objects and procedures: objects hold state, scenarios puts them in play  invisible forces, multiple visual layers  design representations for end users  reusable examples at a “basic” level  embedded minimalist learning support back to the activity: what is really learned? can it be taught to others?

20. March 200120 2: EUP as a community activity engage diverse people in collaborative community modeling and reflection  initially older adults and children EUP “challenges” embody current issues  finding energy in community, leveraging what will be the impact on participants?  programming skill (or even just efficacy)  community involvement and concern

21. March 200121 For example: a fight happens at the middle school kids argue, heckle, or just watch; tension rises; a fight breaks out, unless a teacher comes out to stop it

22. March 200122 Attracting diverse participants minimalist instruction, customized for different users with different needs  iterative design with kids, the elderly, other adults (teachers, parents) promoting intrinsic motivation, reward  finding the right level of fun, challenge  community construction kits as scaffolding  participants extend, refine, share the kits

23. March 200123 A community starter kit an ensemble of roads, lights, moving car

24. March 200124 As starting point for a project: add a video camera that catches cars that speed; show effects relative to a police car discuss the implications of each approach...

25. March 200125 Summing up studying EUP in an activity context  teachers who rule a busy classroom  community members with diverse goals, backgrounds, skills not individual cognition, but social  groups of learners working together  complementary motivations, understandings, roles, reward mechanisms

26. March 200126 Acknowledgements NSF support: REC-9554206, ITR-0091102 Partnerships: Agentsheets, Stagecast, Cambridge University, schools, community groups Virginia Tech research team: John Carroll, Cheryl Seals, Lenese Colson, Shanda Harper, Tracy Lewis, Sriram Sridharan Publications: Proceedings of IEEE Visual Languages 2001; CHI 2001