Skip to main content

Workspaces

Navigate: Content > Workspaces

Workspaces support AI-assisted training authoring. A workspace lets an author synchronize training files to a local directory, edit or create the training with an AI tool, preview the training locally, and publish the result back to the LMS.

info

Workspaces are managed from the Content area, but they are not learner assignments by themselves. Use them to prepare structured training content that can be rendered by the training runtime.

In this section​

  • Authoring workflow – create or edit training with a local folder and an AI tool.
  • Training runtime – understand how the LMS displays workspace training to learners.
  • Workspaces list – find existing workspaces and create a new workspace.
  • Create a workspace – create the workspace record and define access.
  • Workspace page – maintain workspace details, files, preview, and synchronization.
  • Files – review, upload, download, rename, and delete workspace files.
  • Synchronization – compare and synchronize workspace files with a local directory.
  • Related pages – content pages connected to workspace use.

Authoring workflow​

The usual workspace workflow is:

  1. Create a workspace in the LMS.
  2. Create a directory on your computer for the workspace files.
  3. Synchronize from the server to the local directory. This can bring down AI tool instructions and existing training content when the workspace already has content.
  4. Use your preferred AI tool, such as Codex, Claude, or a company-approved AI tool, to edit or create the training in that local directory.
  5. Let the AI tool write the training assets and the training data file.
  6. Preview the training from your own computer while you edit it. You do not need to upload files to the server for local preview.
  7. Synchronize the local directory back to the server when the training should be published.
  8. Preview the server version and repeat the edit/synchronize cycle when more changes are needed.

The input material can be any information the chosen AI tool can read or access. This can include existing LMS content synchronized into the workspace, PDF or office documents, local files, public information from the Internet, or a completely new training created from scratch.

Workspaces are especially useful when a document should become training, not only a file to open. For example, a PDF can be turned into a structured training with pages and a few activities. This makes learners work through the material instead of jumping to the end of the PDF and confirming that they read it.

The AI tool does not publish the training directly to learners. It writes the files used by the workspace. The LMS receives those files through synchronization.

Synchronizing local changes to the server is the publishing step for the workspace training. Server uploads are versioned, so the LMS keeps track of uploaded workspace file versions.

Training runtime​

Workspace training is displayed by a training runtime. The runtime reads the workspace data file and uses the workspace assets to show the learner-facing training.

The data file defines the training structure and content, such as:

  • chapters;
  • pages;
  • text and media content;
  • activities;
  • checks or questions;
  • final quiz content.

The assets are the supporting files used by the training, such as images, videos, documents, or other files referenced by the data file.

Use local preview while editing on your computer. Use server-side Preview after synchronization to check how the runtime displays the published workspace files before the training is used by learners.

Workspaces list​

The Workspaces list shows the workspaces available to the administrator. The table includes columns such as Name, Type, Runtime, and Updated.

Available actions can include:

  • Add – create a new workspace.
  • Opening a workspace name – edit the selected workspace.

Create a workspace​

The Add workspace page creates the workspace record before files are uploaded, generated, or synchronized.

The form contains:

  • Name – the workspace name shown in lists and page headers.
  • Description – optional notes about the workspace purpose.
  • Scope – the permission labels that control who can manage the workspace.

After creation, the workspace page opens so files can be managed.

Workspace page​

The workspace page contains workspace settings and files.

Available actions can include:

  • Preview – open the current workspace training in a separate browser window.
  • Download – download the workspace files.
  • Copy – create a new workspace from the current one, with a new name and scope.
  • Delete – delete the workspace when deletion is allowed.

The page contains these tabs:

  • General – workspace name, description, and scope.
  • Files – uploaded and synchronized files.
  • Synchronize – local folder synchronization controls.

Files​

The Files tab contains a ZIP upload area and the workspace file table.

The table shows columns such as Path, MIME type, Size, and Version. File actions can include download, rename, and delete.

Workspace files normally include:

  • the training data file that defines the training structure;
  • assets used by the training, such as images, videos, documents, and other media;
  • AI tool instructions or other authoring files used while editing the training.

Use synchronization for the normal local editing and publishing workflow. Use the ZIP upload when workspace files need to be added or updated in bulk. Server uploads are versioned. Downloading an individual file uses its workspace path.

Synchronization​

The Synchronize tab compares workspace files with a selected local directory and then applies the selected changes.

The tab contains:

  • Local directory – selected directory and preview status. The preview can open the training files from the local directory.
  • Synchronization options – direction, mode, and delete behavior.
  • Preview changes – the files that would be written, deleted, unchanged, or skipped.
  • Synchronize – current state, pending writes, pending deletes, and the action to apply or continue synchronization.

Use Server → local when starting or continuing work from the server version. This can copy existing workspace files, training data, assets, and AI tool instructions into the local directory.

Use Local → server after editing with the AI tool and checking the local preview. This publishes the updated data file and assets to the LMS as a new server version.

Synchronization modes are Full mode, which includes all files, and Content mode, which synchronizes only root-level files and no directories.

The delete behavior can either delete missing files or preserve files that are missing from the selected source. Protected files are shown as skipped and are not overwritten.