AI Content Recommendations
AI Content Recommendations is one of 91 AI tools built into OpenEduCat. It drafts topic-matched resource suggestions from a faculty-curated pool, and instructors review those drafts before anything reaches a student. AI advises, faculty decides — every suggestion traces back to material your team approved.
What Content Recommendations Does
Four capabilities that connect the right resources to the right students at the right time.
Topic-Matched Suggestions
When a student struggles with a specific quiz topic, the AI drafts a suggested resource list matched to that topic — a practice set, a video explanation, a worked-problem PDF — all drawn from the materials the instructor uploaded. The suggestions target the specific skills the quiz covered, not the entire unit, and the instructor reviews the draft list before deciding what to assign.
Suggestions That Stay Current
Suggestion lists refresh as students practice. When a student completes recommended practice sets and improves on a follow-up practice quiz, the AI drafts an updated list covering the next topic instead of repeating material the student has already worked through. Instructors see the refreshed suggestions and stay in control of what is actually assigned.
Faculty-Curated Resource Pool
The AI does not recommend random internet content. Faculty members build and curate the resource pool: approved textbook chapters, vetted videos, practice worksheets, lab simulations, and reference articles, each tagged by topic. The AI only ever suggests resources from this pre-approved collection — so every suggestion a student sees traces back to something faculty chose to include.
Multi-Format Content
Not every student learns the same way. The suggestion engine draws on resources across formats: reading materials, video explanations, practice problems, and discussion prompts. When faculty tag resources by format, suggested lists can offer the same topic in more than one form, and students choose the format that works for them.
How It Works
Three steps from faculty resource upload to personalized student recommendations.
Faculty loads the resource pool
Instructors upload or link supplementary materials to each course topic in OpenEduCat: textbook sections, videos, practice sets, articles, simulations. Tag each resource with the topic it covers and the skill level it targets. This is a one-time setup per course, resources carry over across semesters.
AI drafts suggestion lists
As students complete practice quizzes and course activities, the AI drafts topic-matched suggestion lists from the tagged resource pool. A student working on calculus integration gets a different draft list than one working on limits. The lists are advisory — instructors review them and decide what appears on each student's dashboard.
Students engage, instructors refine
When students open and complete assigned resources, the suggestion lists refresh to cover the next topic instead of repeating completed material. Faculty sees aggregate engagement data — which resources students actually use and which ones they skip — and uses it to prune the pool and refine what gets assigned.
Example: A Student's Dashboard
An illustrative example of what a statistics student sees after the instructor approves the AI's drafted suggestion list for the probability unit.
Suggested for You
STAT 201, Introduction to Statistics · Approved by your instructor
Conditional Probability Practice Set A
15 problems with worked solutions covering Bayes' theorem applications
Suggested because this week's practice quiz covered conditional probability
Bayes' Theorem Explained with Medical Testing Examples
12-minute video walkthrough with 3 step-by-step examples
Same topic in video form — choose the format that works best for you
Conditional Probability Practice Set B
10 problems without solutions, check your understanding after Set A
Suggested next step after Practice Set A — practice only, never graded
Note from your instructor: These resources cover the conditional probability topics from this week's practice quiz. Work through them at your own pace, then try the practice quiz again to see how you're doing.
Bring Your Own Model
The suggestion engine runs on the AI endpoint your institution already governs — Azure OpenAI, Google Vertex AI, AWS Bedrock, or another compatible provider. All requests go from your OpenEduCat instance to that endpoint under your own agreement, region, and data terms. OpenEduCat never accesses student grades or engagement data. Your IT team picks the endpoint and sets per-department spending budgets.
For institutions with strict data governance policies, the data relationship stays the one you already negotiated with your cloud provider — and every AI suggestion is captured in your instance's audit log for review.
Frequently Asked Questions
Common questions about AI Content Recommendations.
Related AI Tools
Content Recommendations works alongside other AI tools in OpenEduCat.
AI Course Generator
AI drafts complete course outlines — instructors review, edit, and publish.
Learn more →Quiz & Assessment Builder
Draft practice quiz questions from course materials — formative, instructor-controlled.
Learn more →AI Grading Assistant
AI drafts rubric-aligned feedback; teachers review and assign every grade.
Learn more →Student Support & Tutoring
Answers student questions from institution-uploaded course documents, with citations.
Learn more →