--- title: "Creating AI Vision Activities" slug: "creating-ai-vision-activities" updated: 2025-07-17T17:14:13Z published: 2025-07-17T17:14:13Z canonical: "docs.skillable.com/creating-ai-vision-activities" --- > ## Documentation Index > Fetch the complete documentation index at: https://docs.skillable.com/llms.txt > Use this file to discover all available pages before exploring further. # Creating AI Vision Activities ## What is AI Vision? AI Vision, a new activity type in Skillable Studio, helps lab builders create high-quality, performance-based activities. Lab builders can leverage AI-powered computer vision technology to create natural language prompts that verify, based on a learner’s screen, whether the learner successfully completed an activity or set of activities within the lab. ### Purpose - Reduces technical skills required to create a scored activity. (No need to write scripts.) - Enables builders to check for the outcomes that matter. (No more false negatives due to misspelled cell headers.) - Supports more environments and software types. (Measure what's on a learner's screen, without worrying about whether the software has an API to call.) ### Scenarios - Lab builders who want to evaluate activities in practice, learning, or validation labs with visual components - Lab builders who want to evaluate practice, learning, or validation labs on software products with limited API endpoints - Lab building teams who want to reduce the time required to build quality labs - Lab building teams without the technical skills required to write script-based activities ### Key Elements 1. **Prompt**: Allows the lab author to create a prompt using natural language. This prompt determines what the computer vision technology will check on the learner's screen. 2. **Test prompt**: Enables the lab author to test a prompt using a 1-5 star rating and AI-generated feedback to help improve prompt strength and clarity. 3. **(Optional) Reference image**: Adds a reference image of the correct answer to further guide the computer vision technology as it checks a learner's screen. **Remember:** A reference image, while helpful, is not a replacement for a clear, specific prompt. Including a reference image also adds time to the evaluation process. 1. **Evaluation/Scoring**: Uses computer vision to check a learner's screen when they click **Check/Score** in the lab, evaluating whether it matches the prompt and, if provided, the reference image. **Note:** AI Vision-based activities are only available in labs that contain a virtualized environment. ### Safeguards - Ensure the AI prompt is clear and precise to avoid any ambiguity in evaluation. - Validate the prompt's strength using the **Test Prompt** button. - Use the feedback provided to refine the prompt and improve its effectiveness. **Note:** Be cautious when relying on reference images for evaluation, as they may not always be optimal. Clear prompts are often better for accurate scoring. ## Create an AI Vision Activity 1. Navigate to your lab profile (which opens automatically after you create a lab) and click **Edit Instructions**. 2. Select the **Activities** tab and then click **+ New AI Vision Activity**. This option is only available if your lab profile contains a virtualized environment. 3. [Configure the prompt](/v1/docs/creating-ai-vision-activities#configure-the-prompt) and then click **Next**. 4. [Configure the activity settings](/v1/docs/creating-ai-vision-activities#configure-the-activity-settings). 5. Click **Save** or **Save and Insert** to finalize and create the activity. ### Configure the Prompt AI Vision activities work by comparing an image of a learner's screen (taken at the time of evaluation) to the contents of your prompt. 1. **Choose the environment**: Use the **Choose Environment** dropdown to select which VM the AI should evaluate. **Note:** When editing instructions: - **Without the lab running**: The dropdown defaults to the first available environment. - **With the lab running**: The dropdown selects the VM the lab author is viewing. 1. **(Optional) Provide a reference image**: Upload a reference image for the AI to use when evaluating a learner's screen. Providing a screenshot of the correct response further informs the AI model and its evaluation. 2. **Write the prompt**: In the **Write Prompt** text box, write a clear prompt using natural language that describes what the computer vision AI should look for on the learner's screen. Include specific outcomes that indicate success in the activity. 3. **Test the prompt**: Click **Test prompt** to verify the strength of your prompt. If the AI-generated feedback shows that your prompt strength is weak (three stars or below), update it based on the feedback, then test the prompt again. ### Configure the Activity Settings 1. **Name**: In the text field, specify the activity name. This is hidden from learners but visible to lab builders in the **Activities** tab and the **Activities** left pane. 2. **Replacement Token Alias**: In the text field, assign a recognizable name to the token for easier identification when reviewing a lab's Markdown code. A default alias is automatically generated. 3. **(Optional) Skills**: Tag the activity with relevant skills. This setting is hidden if your organization is not configured to use a Skills Framework. 4. **(Optional) Instructions**: Add instructions to display in the **Instructions** panel above **Check/Score**. 5. **Evaluation**: Use the checkboxes to set the activity's evaluation conditions: - **(Required) On-demand evaluation:** This option is checked by default because all AI Vision activities are currently *only* capable of on-demand evaluation. This allows learners to click a button in the lab instructions and receive feedback on their activity progress in real time. - **(Optional) Custom evaluation button text:** Specify the text of the evaluation button. If left unchecked, the buttons read **Check** for a non-scored activity and **Score** for a scored activity. - **(Optional) Allow retries:** Allow learners to retry and rescore the activity if they initially receive an **Incorrect** response. Use the corresponding **Maximum attempts** checkbox to limit the number of activity evaluation attempts. 6. **Scoring**: Use the **Scored** checkbox to determine whether the outcome of this activity will contribute to the learner's lab score. If checked, use the corresponding **Score Value** text field to set the point value the activity generates with a correct response. **Note:** Due to the dynamic nature of AI-based features, we recommend that you consult with your psychometrician before including AI Vision scored activities in high-stakes scenarios. 1. **Settings**: Use the checkboxes to configure additional activity settings: - **Show results in reports:** Check to include the results of this activity in the end-of-lab detailed report. - **Required for submission:** Check to require learners to evaluate the activity before they can end the lab. - **Blocks page navigation until answered:** Check to disable the **Next** button. 2. **Feedback for User**: Use this section to define the feedback learners see: - **Correct Answer Feedback:** In the text box, specify the text a learner sees when a correct response is generated. If left blank, the text simply reads **Correct**. - **Incorrect Answer Feedback:** In the text box, specify the text a learner sees when an incorrect response is generated. If left blank, the text simply reads **Incorrect**. - **Show AI Feedback for Incorrect Answers:** This checkbox is checked by default so incorrect responses display AI feedback to learners. Uncheck this option if you do not want to provide AI feedback. 3. **Outcomes:** Click **Add Outcome** to configure adaptive learning experiences based on the result of the activity. See more on outcomes in our [Activity Outcomes article](/v1/docs/activity-outcomes). ## AI Vision Activity Frequently Asked Questions ### How do I manage or edit AI Vision activities? Just as you'd do with all other activity types, navigate to the activity via **Lab Profile** > **Edit Instructions** > **Activities**. Find the activity you'd like to edit, and then click **Edit**. (Always remember to save!) Lab builders can also move, clone, or delete activities from this view. ### How do I use prompt feedback to improve my prompts? To improve your prompts using the system-provided feedback: - **Review feedback:** Carefully read the feedback and check for conciseness, specificity, clarity, and whether the prompt matches the image. This will give you a clear understanding of areas that need improvement. - **Analyze ratings:** Look at the prompt strength rating out of 5 and the summary of possible corrections. This will help you identify the specific aspects of your prompt that need enhancement. - **Implement corrections:** Make the necessary adjustments to your prompt based on the feedback. Focus on making your prompt more concise, specific, clear, and well-matched with the image. - **Mitigate errors:** Address any error messages related to primary failures such as timeouts and content errors. Ensure that your prompt is correctly parsed by the AI. - **Structure output:** If applicable, specify a structured output format, such as JSON schema, to ensure the response is returned in a consistent format. **Happy prompting!**