Data collection helps Institutions gather structured information from selected participants in a consistent, trackable workflow. Institutions commonly use them to request updates, narrative responses, evidence, or form-based inputs from departments, programs, committees, faculty, or other designated contributors. Unlike one-time spreadsheets or email-based requests, the Data Collections feature centralizes participation, due dates, response status, notifications, and reporting in one place. This makes it easier to manage recurring institutional processes and improve completion rates. Some key benefits of using data collections include:
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Standardizes institutional data gathering
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Improves visibility into participation and completion
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Reduces manual follow-up and version control issues
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Supports recurring cycles and repeatable processes
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Provides cleaner data for reporting and downstream analysis
Data collections are most useful when an Institution needs a structured, repeatable way to gather information from multiple contributors. They are best suited for information that requires narrative input, confirmation, reflection, or locally maintained details rather than data that should be automatically sourced from an existing feed.
Use Cases
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Collecting Annual or Periodic Program Updates |
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An Institution needs a reliable way to collect annual or periodic program updates without relying on scattered emails, spreadsheets, or one-off documents. This is especially relevant when many programs must report on similar information on a recurring cycle, such as curriculum changes, enrollment context, faculty updates, assessment activity, or progress toward prior goals. |
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Gathering Assessment Reflections or Action Plans |
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An Institution needs a structured way for programs, departments, or instructors to reflect on assessment results and document planned improvements. This practice often follows the close of an assessment cycle, rubric scoring period, or annual outcomes review. |
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Capturing Accreditation-Related Narrative Responses |
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An Institution requires narrative responses that support accreditation, program review, or external accountability requirements. This can be triggered by self-study preparation, interim monitoring reports, specialized accreditation cycles, or requests for evidence tied to standards and criteria. |
First Time Implementation Process
For Institutions using the Data Collection feature for the first time, implementation can take a minimum of three months. This ensures adequate time for form configuration and validation, as well as related training for the Institution.
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The Institution submits a Support ticket requesting data collection. Learn more.
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HelioCampus will meet with the Institution to provide an overview of the Data Collection feature and discuss collection specifications. In this part of the process, HelioCampus and the Institution will discuss goals, scope, data needs, and required documentation.
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HelioCampus will configure and build a draft form in the Institution’s Training Site.
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HelioCampus provides training to the Institution:
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Logging in as a user
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Form features
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Testing draft forms in the Institution’s Training Site
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The collection is validated and tested in the Institution’s Training Site to ensure the form meets the Institution's needs.
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As part of testing, a soft-launch can be configured to review how the data collection functionality works in real time. Each soft-launch configuration adds one week to the timeline.
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HelioCampus provides training to the Institution:
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Preparing the form for the Production Site
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Managing a collection before launching to the Production Site.
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The Institution will validate the configurations, schedule, workflow, and template details in preparation for the Production Site
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After successfully validating the collection in the Training Site, HelioCampus will load the finalized data collection into the Production Site.
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After the collection changes to In Progress status, the data collection is live, and the Support ticket will be closed.
*Timelines can vary based on project scope
Repeat Data Collections Process
For Institutions administering repeat data collections, implementation can take up to one month. This ensures adequate time for form configuration and validation per the Institution requirements.
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The Institution submits a Support ticket requesting data collection. Learn more.
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HelioCampus will meet with the Institution to discuss collection specifications
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HelioCampus will configure and build a draft form in the Institution’s Training Site and provide a link for Institutional review.
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Internal testing of the form, workflow, and schedule elements ensures successful collection of the intended data.
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The Institution will then submit feedback on the form so HelioCampus can iterate on the data collection until it meets the Institution's requirements.
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Once all revisions are complete, the Institution will approve the form, then migrate the template and workflow to the Institution’s Production Site.
*Timelines can vary based on project scope
Considerations
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Collection Scope and Scale: Before using a data collection, Institutions should determine whether they need to collect a small set of responses from a limited group or a large volume of submissions across many areas of the organizational hierarchy.
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Recurring Collection Needs: Institutions should consider whether the information is needed one time or on a recurring cycle, such as annually, each term, or during a scheduled assessment period.
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Source of Truth: Institutions should identify whether users should enter the requested information manually or whether it already exists in another system, such as an SIS, LMS, or governed institutional dataset.
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Timing and Deadlines: Institutions should consider whether the collection is tied to a fixed deadline, mid-cycle update, accreditation submission, annual report, or term-based review. Data collections require enough lead time for contributors to respond, reviewers to follow up, and administrators to prepare results for reporting.
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Contributor Readiness: Institutions should confirm that contributors understand what information is being requested, why it is needed, and how their responses will be used. Clear prompts, instructions, and due dates can reduce incomplete responses and help ensure responses are consistent enough for review.
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Governance and Review Process: Institutions should decide who is responsible for monitoring the collection, monitoring submissions, reviewing responses, and determining whether follow-up is needed. This is especially important when responses affect institutional reporting, accreditation evidence, or official program records.
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Data Consistency: Institutions should consider how much structure the response format needs. Open-ended narrative prompts may be appropriate for reflection or accreditation context, while more standardized prompts may be needed when responses must be compared, aggregated, or reported across multiple units.
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Access and Visibility: Institutions should determine who can view, submit, edit, or review responses. Access decisions should align with the sensitivity of the information being collected and whether responses are intended for program-level use, institutional oversight, or external reporting.
Data Collection Participants
Keep the participant experience as simple as possible. Data collections with clear instructions, focused questions, and realistic due dates tend to achieve stronger completion rates.
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Participant |
What They Usually Do |
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Administrator |
This responsibility is usually limited to institutional administrators. These participants assign participants, manage settings, and monitor progress. *Initial configuration and form building is completed by HelioCampus Administrators |
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Contributor |
These participants may be faculty, staff, department leads, committee representatives, etc. They are responsible for completing assigned forms and tasks and will have access to past results from the forms they have submitted. |
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Reviewer |
While not every data collection includes this role, a reviewer reviews submitted information when the collection includes a review step. |
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Institutional Stakeholder |
These participants may not directly participate in the workflow, although they consume results, exports, or summaries. |