Universal Access to Programming

Mary Beth Rosson

Department of Computer Science

Virginia Tech

March 2001 2

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

March 2001 3

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

March 2001 4

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?

March 2001 5

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

March 2001 6

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

March 2001 7

Example: Agentsheets• white cloud• dark cloud• water vapor• rain drops• sun• sun rays• lake• puddle• grass• desert

water evaporates, isabsorbed, rains, etc.

March 2001 8

Sample rules- left-handspecifies a“before” state

- right-handspecifies oneor moreactions to take if stateis confirmed

- multiple rulesare tested inorder, firstmatch fires

March 2001 9

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

March 2001 10

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

March 2001 11

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 apuddle and finally to alake as it absorbs water

- lake produces water vapor, eventually transforming topuddle, grass, desert as water content decreases

March 2001 12

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

March 2001 13

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

March 2001 14

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

March 2001 15

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 positioningand build-up of “result”

March 2001 16

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

March 2001 17

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

March 2001 18

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

March 2001 19

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?

March 2001 20

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

March 2001 21

For example: a fight happens at the middle school

kids argue,heckle, orjust watch;tensionrises; afight breaksout, unlessa teachercomes outto stop it

March 2001 22

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

March 2001 23

A community starter kit

an ensemble of roads, lights, moving car

March 2001 24

As starting point for a project:add a videocamera thatcatches carsthat speed;show effectsrelative to apolice car

discuss theimplicationsof eachapproach...

March 2001 25

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

March 2001 26

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