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Instructions for Submitting Smart Learning Contents to the SPLICE Catalog

Follow the step-by-step guide below to prepare, format, and submit your Smart Learning Content (SLC) items, tools, or datasets for inclusion in the SPLICE catalog.

1

Prepare Your Data as one of the following

To contribute to the SPLICE Catalog, categorize your Smart Learning Content (SLC) into one of the following types:

  • SLC Items Catalog
  • SLC Tools Catalog
  • Dataset Catalog

Each type has a specific JSON format. Below are examples and field descriptions for each category:

SLC Items Catalog

A collection of Smart Learning Content (SLC) items should be described as a series of JSON records, each formatted as follows:

{
    "catalog": "SLCItemCatalog",
    "platform_name": "...",
    "url": "...",
    "lti_instructions_url (required if LTI URL)": "...",
    "exercise_type": "...",
    "license (optional)": "...",
    "description (optional)": "...",
    "author (optional)": "...",
    "institution": "...",
    "keywords": ["...", "..."],
    "exercise_name": "...",
    "language (optional)": "...",
    "iframe_url": "...",
    "lti_url": "..."
}

Field Descriptions:

  • catalog: The type of catalog, e.g., "SLCItemCatalog".
  • platform_name: Name of the platform offering the SLC item.
  • url: URL of the SLC item.
  • lti_instructions_url: Required if an LTI URL is provided.
  • exercise_type: Type of exercise, e.g., "KA" for Khan Academy.
  • license: Content license (optional).
  • description: Brief description of the SLC item (optional).
  • author: Author of the SLC item (optional).
  • institution: Institution associated with the SLC item.
  • keywords: Relevant keywords.
  • exercise_name: Name of the exercise.
  • language: Language of the content (optional).
  • iframe_url: URL for embedding the exercise.
  • lti_url: LTI launch URL.
SLC Tools Catalog

Describe tools that support Smart Learning Content using this format:

{
    "catalog": "SLCToolsCatalog",
    "platform_name": "...",
    "url": "...",
    "tool_description": "...",
    "license" (optional): "...",
    "standard_support": "...", 
    "keywords": "...",
    "contact_email": "..." 
}

Field Descriptions:

  • catalog: Type of catalog, e.g., "SLCToolsCatalog".
  • platform_name: Name of the platform offering the tool.
  • url: URL of the tool.
  • tool_description: Brief description of the tool.
  • license: Content license (optional).
  • standard_support: Standards supported by the tool.
  • keywords: Relevant keywords.
  • contact_email: Contact email for the tool provider.
Dataset Catalog

Describe datasets available for Smart Learning Content with the following JSON format:

{
    "catalog": "dataset",
    "title": "...",
    "publisher": "...",
    "dataset_name": "...",
    "url": "...",
    "description": "...",
    "data_format": "...",
    "data_type": "...",
    "keywords": "...",
    "population": "...",
    "affiliation": "...",
    "language": "...",
    "date": "..."
}

Field Descriptions:

  • catalog: The type of catalog, e.g., "dataset".
  • title: Title of the dataset.
  • publisher: Publisher of the dataset.
  • dataset_name: Name of the dataset.
  • url: URL where the dataset can be accessed.
  • description: Brief description of the dataset.
  • data_format: Format of the dataset.
  • data_type: Type of data in the dataset.
  • keywords: Relevant keywords.
  • population: Target population of the dataset.
  • affiliation: Affiliation associated with the dataset.
  • language: Language of the dataset.
  • date: Publication date of the dataset.
2

Submit Your JSON File to SPLICE

Once your JSON file is ready, you have two options to submit your Smart Learning Content (SLC) to the SPLICE Catalog:

  1. Upload Directly: You can upload your collection of any SLC type directly using our submission portal. here.
  2. Send Submissions: If you prefer, you can also send your JSON file to the SPLICE community here.

We look forward to your contribution to the SPLICE Catalog!

Examples

Here are JSON exports examples for OpenDSA, CodeWorkout SLC items submission, OpenDSA tool submission and a Dataset submission:

{
    "catalog": "SLCItemCatalog",
    "platform_name": "OpenDSA",
    "url": "https://opendsa-server.cs.vt.edu",
    "exercise_type": "KA",
    "license": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)",
    "description": "Introduction Summary Questions",
    "author": "Cliff Shaffer",
    "keywords": ["Introduction"],
    "exercise_name": "Introduction Summary Questions",
    "language": "N/A",
    "iframe_url": "https://opendsax.cs.vt.edu/embed/IntroSumm",
    "lti_url": "https://opendsax.cs.vt.edu/lti/launch?custom_ex_short_name=IntroSumm",
    "lti_instructions_url": "https://opendsa-server.cs.vt.edu/guides/opendsa-canvas"
}
{
    "catalog": "SLCItemCatalog",
    "platform_name": "CodeWorkout",
    "url": "https://codeworkout.cs.vt.edu",
    "exercise_type": "Coding Question",
    "license": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)",
    "description": "Introduction Summary Questions",
    "author": "Stephen Edwards",
    "keywords": ["programming", "coding"],
    "exercise_name": "Introduction Summary Questions",
    "language": "N/A",
    "iframe_url": "https://codeworkout.cs.vt.edu/gym/exercises/1/practice",
    "lti_url": "https://codeworkout.cs.vt.edu/lti/launch/gym/exercises/1/practice",
    "lti_instructions_url": "https://codeworkout.cs.vt.edu"
}

SLC tools catalog

{
    "catalog": "SLCToolsCatalog",
    "platform_name": "OpenDSA",
    "url": "https://opendsa.server.vt.edu/",
    "tool_description": "CS e-textbook platform.",
    "license": "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International",
    "standard_support": "LTI", 
    "keywords": ["Algorithm visualization", "practice", "auto-assessment"],
    "contact_email": "opendsa@cs.vt.edu" 
}

Dataset catalog

{
    "catalogType": "DatasetCatalog",
    "title": "iSnap - Introductory Programming",
    "platform": "DataShop",
    "datasetName": "iSnap - Introductory Programming",
    "url": "https://datashop.web.cmu.edu/DatasetInfo?datasetId=321",
    "description": "This project contains programming log data from iSnap, a visual, block-based programming environment based on Snap!. The data were collected from an introductory programming course for non-majors, starting in Fall 2015. Starting in Spring 2016, the environment provided students with on-demand hints for some assignments. The data includes not only detailed logs of all student actions within the environment, but also complete snapshots of student code as it was edited.",
    "dataFormats": ["txt"],
    "dataType": ["Programming"],
    "keywords": ["programming", "log data"],
    "population": "CS0 (non-majors)",
    "contributors": [
        {
            "Name": "Thomas Price",
            "affiliation": "North Carolina State University"
        }
    ],
    
    "yearPublished": 2015
}