AI-Driven Enhancements in HelioCampus Assessment & Credentialing

As part of our AI strategy, we’re expanding automation and data analysis capabilities in our Assessment & Credentialing products. These updates will simplify how institutions access and interpret data, helping faculty and administrators more easily explore their data and make informed decisions.

AI for Analyzing and Summarizing Data

Our first forays focus on what AI does best – analyze language.  Institutions collect a large volume of feedback and assessment data, but extracting useful insights takes time. We’re using AI to:

• Identify trends in student and faculty feedback – AI will analyze course survey responses to surface common themes and potential concerns. This feature is scheduled for release in March 2025* (v3.108).
• Enable natural language queries – Faculty and administrators will be able to ask direct questions of the data collected as part of their Outcomes Assessment data collections efforts (e.g., “Show writing proficiency results over the past three years”), as well as the data collected in Evidence Banks as part of their Accreditation and Planning efforts thus reducing the need to manually sift through reports. This capability is in pilot now and expected to become generally available in July 2025.*

These tools align with our broader data strategy, ensuring institutions can quickly access relevant insights.

AI for Reducing Manual Work

Next up for us is research on how AI might be used to enhance and simplify workflows by automating some tasks, and assisting with others.  We’ll be looking into AI applicability several different areas: 

• Curriculum Mapping – AI could suggest alignments between course content and institutional learning outcomes.
• Assignment Linking – AI could recommend connections between assignments and required competencies.
• Automated Accreditation Tagging – AI could classify and index evidence, making it easier to organize documentation for accreditation reviews.
• Pre-Structured Self-Study Reports – AI could compile assessment data into structured reports, mapping evidence to accreditation requirements.

Expanding AI’s Role in Institutional Workflows

Beyond data analysis and workflow assists, we’re exploring AI’s potential to streamline institutional processes:

• Accreditation Readiness Assistant – AI could monitor compliance with accreditation standards, flag missing evidence, and assist with report preparation.
• Smart Workflow Optimization – AI could recommend process improvements, including approval flows, task automation, and deadline tracking.
• Faculty and Administrator Assistance – AI-powered assistants could help users navigate dashboards, retrieve reports, and suggest next steps based on assessment results.
• Pattern Recognition in Student Work – AI could identify gaps in skill development across student submissions and suggest curriculum adjustments.

These AI-driven updates are designed to integrate with existing workflows, helping institutions reduce administrative burden and improve decision-making. 

Stay tuned as we’ll be reaching out for input and feedback on our research in these areas. If you’d like to be involved in an upcoming pilot program, send me a note: brad.koch@heliocampus.com. 

*Feature launch dates are shared in the spirit of transparency. They may change as pilot programs and development evolve.