Wizard of OZ

Oxford, Maurice Vereecken

Goal of implementing Woz

• Wp2– Quick insight in mapping events to Ontdeknet– Working towards what to do in WP3– Finding the possible obstacles on forehand.

• Wp4– Validating intervention model– Ad-hoc testing of new ideas

Implementation;Overview

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Intervention model

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Step 1; Gather Step 2; Wizard of Oz Step 3; Create modell Step 4

Gather measurable information out of the application and filter them on usability

Create the model out of the decision matrixCreate a decision list and do some Woz itterations to check the Intervention

responses

Implement the model in the atgentive interface, and repeat the WoZ itterations to

check the model

Repeat WoZ until modell refelcts WoZRepeat gathering unitl we have

enough to give the right intervention

Step 1; Gather information

Application

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Parameters

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Step 1; Gather

Gather measurable information out of the application and filter them on usability

Step 2; Ozzing

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Step 2; Wizard of Oz

Create a decision list and do some Woz itterations to check the Intervention

responses

Step 3; Create model

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InterventionDecision

Intervention model

Step 3; Create model

Create the model out of the decision matrix

Step 4; Implement model

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Intervention model

Step 4

Implement the model in the atgentive interface, and repeat the WoZ itterations to

check the model

What is woz

• The Wizard of Oz technique enables unimplemented technology to be evaluated by using a human to simulate the response of a system. Interacting with the ‘knowledge’ the agent would have.

• Actors– Wizard (Observer)– Dorothy (Logged in user)

What is woz

Using Woz

• The "wizard" sits in a back room, observes the user's actions, and simulates the system's responses in real-time. Often users are unaware (until after the experiment) that the system was not real.

• The "wizard" has to be able to quickly and accurately discern the user's input. The output must also be sufficiently simple that the "wizard" can simulate or create it in real time.

• The easy way:– The user logs in to the system– The observer receives all the application events the

system generates– The observer interpretes the data and gives a response

based on reasoning (ie; a reasoning tree)

Example 1; Introduction

• Outline– In the introduction fase, the user has to click

on “edit’, fill in his personal introduction and has to click on “save”

– The introduction is finished when he has filled in more than 5 words.

Example 1; Introduction

• Events– When clicking on “edit” a “start task” is fired– When clicking on “save” and more than 5

words are filled in a “complete task” is fired.

• Parameters– The context; Introduction– The text; The filled in introduction

Example 1; Introduction

• Fill in your introduction– The user provides a description/story about

himself.

Current problem:– Is the user done introducing himself; When is

the task finished?

Example 1; Introduction

Example 1; Introduction

Example 2; Assignment

• Outline– The user has to open an assignment– Make a decision if we want to use an expert

which he is already signed on or search for a new one.

– Select the expert for the project

Example 2; Assignment

• Events– Start_event on opening assignment– Start_event on selecting expert tab

• Parameters– The assignment context;

Example 2; Assignment

• Navigation; (three modalities)– Tell the user; Give a hint how to get to the

assignment– Guide the user; tell all the steps the user must

take (Buttons etc)– Redirect; Directly show the right screen

Example 2; Assignment

• Select expert for the assignment– The user can choose one of his own experts or (s)he can sign

up with a new one.

Current problem:– Signing up with a new expert can be an optional task. How do

we manage that?– The user can work parallel on multiple assignments, activities

like reading a diary are not linked with one single assignment– The user can click anywhere, the intention is not clear.– If the teacher decides the task isn’t finished, the completed task

has to be reopened

Example 2; Assignment

Example 2; Assignment

Next steps

• Wp2– Validate events mapping to model– Creating model on base of lessons learned

• Wp4– Check working of model– Fine tune model on base of pilots