Below are resources related to the data submission process in general that apply to most data collections. Resources specific to particular collections can be found on the respective data collection page. Links to each data collection are provided under the Data Submissions Library For questions or support, please email Submissions_CSI@csi.state.co.us.
Key Resources
- Data Submissions Onboarding [docx]: This resource for new school submissions contacts outlines how to prepare for the data collection process and highlights important resources to review before meeting with a Data Team member for onboarding.
- Data Submissions Handbook: This handbook outlines the data submissions process as well as helpful tools and resources for school-level data submissions contacts. This is the primary resource school submissions contacts will need for comprehensive background on all aspects of working with CSI on data submissions.
- Data Submissions Calendar [docx]: This printable, annual calendar provides deadlines for main data collections along with information on other submission-related deadlines. These deadlines can also be accessed on the CSI Website Calendar.
- Troubleshooting Errors: This resource provides guidance to schools in how to resolve errors. There are tabs for Level 1 and Level 2 errors for each collection.
23-24 Resources
- 23-24 Gender Category Update: This CDE resource provides background on the updated gender field, implementation timeline, and a list of impacted data collections.
- 23-24 New This Year: This short webinar highlights some of the bigger changes to expect in state reporting for the upcoming 2023-24 school year. School contacts can use this resource to support planning for the coming year, particularly as changes may impact school-level forms or processes.
Optional Resources
- Data Submissions Plan Template: This optional resource can support schools in developing internal processes related to collecting and validating data for each data collection.
- Data Submissions Feedback Form: The Data Submissions Team welcomes school feedback! School contacts can email feedback directly to Data Team members or can use this online form to submit feedback anonymously.
Training Modules
All school-level data submissions contacts should review the following training modules prior to participating in a data collection for the first time. Schools should also plan to review the collection-specific training modules posted on the applicable collection webpage.
Data Submissions Process
The following training modules walk through the five steps of CSI’s data collection process.
- Step 1: Preparing for the Collection [slides] [recording]
- Step 2: Collecting and Entering the Data [slides] [recording]
- Step 3: Extracting the Files and Submitting to CSI [slides] [recording]
- Step 4: Reviewing and Resolving Errors [slides] [recording] [exercise] [answers]
- Step 5: Review Data for Accuracy [slides] [recording] [exercise] [answers]
Requesting SASIDs and EDIDs
Most data collections require the use of unique student IDs (known as SASIDs) and/or unique staff IDs (known as EDIDs). Provided training modules walk through how to identify whether a SASID/EDID is needed as well as how to request new SASIDs/EDIDs or updates to existing SASIDs/EDIDs. Visit the SASID/EDID Request webpage for these trainings and more information.
Additional Trainings
- File Layout Resource Overview [slides] [recording]: This provides an overview of the File Layout and Definition resource, what you can find within the resource, and how to use it to support data entry and error resolution.
- Data Security [slides] [recording] [G-Drive Instructions]: This outlines what personally identifiable information is and how to securely share it using G-Drive. A separate G-Drive instructions document is also posted here.
- Excel: This training provides an overview of the following features in Excel: importing a csv to Excel, freezing the top row of a spreadsheet, sorting, filtering, and wrapping text. Many of these skills come in handy as schools review files and error reports.