01. Scenario Structure

What the scenario structure looks like and what it consists of.

After generation, you'll see the completed scenario structure. It consists of several elements: the game title, a brief description, the intern's role, the bot's role and appearance, and evaluation criteria with scores.

Game Title and Brief Description

This is what the roleplaying will be called and what it is about. This section describes the situation in which the interaction between the participant and the bot takes place.

Trainee

The trainee is the one who will play through the game. This section describes their role, goals, objectives, and what they need to do.

AI Assistant

The AI assistant is the bot that acts as the conversational partner. It has a defined role, backstory, responses, and tasks it needs to perform.

Bot Appearance and Character Description

Based on your prompt, the system generates the bot's appearance and background, which the participant will see during the conversation. The bot is automatically assigned a first and last name, along with a brief description of its character.

Evaluation Criteria

At the end of the scenario, the system generates evaluation criteria, which the bot will use to analyze the participant's responses.

Each criterion consists of three elements: a competency, its indicators, and the levels of indicator manifestation.

The system works as follows:

  • If you described your criteria in the prompt, the neural network will use those.

  • If not, criteria will be generated automatically based on the scenario topic.

A competency is a group of skills that are demonstrated in the dialogue and help achieve the goal: reaching an agreement, defusing tension, clarifying a situation.

Indicators are specific behavioral manifestations of that competency. To view them, select a competency and click on it.

An indicator level describes different variants of how the indicator may manifest—from undesirable to target behavior. To view them, click on the indicator you're interested in.

AI does not currently evaluate pace, pauses, voice volume, or emotional tone of the conversation.

Competency scoring is standardized: each competency contributes equally to the overall score; it is not possible to adjust the weighting of competencies.

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