Use AI to broaden career and scholarship exploration without fabricating options.
Keep student data out of unsafe prompts and tools.
Verify eligibility, deadlines, and recommendations using authoritative sources.
Course outline
01
Support exploration
Generate useful pathways and questions without making decisions for students.
02
Protect student privacy
Apply data-minimization and FERPA-aware practices to AI-assisted work.
03
Verify every opportunity
Confirm programs, scholarships, requirements, and deadlines at the source.
OPEN LESSON
Open lesson: Support exploration
Before automating a task, define the result you need and the evidence that would make it trustworthy. In this course, the goal is: Create a FERPA-conscious student-support workflow with verified resources and appropriate human review. AI can accelerate a draft, comparison, or exploration, but it does not know your policies, full context, or the cost of being wrong. Begin with a low-risk case and keep the earlier version so you can compare, explain, and reverse the decision.
Define the deliverable and an observable quality criterion: Use AI to broaden career and scholarship exploration without fabricating options.
Set context, allowed data, and human review before generating: Keep student data out of unsafe prompts and tools.
Check the output and document the final decision: Verify eligibility, deadlines, and recommendations using authoritative sources.
Responsible authorVidAcademia Editorial Team
ReviewVidAcademia Learning Quality
MethodOutcome-first design, primary-source review, guided practice, and a human-verified final decision.
SOURCES AND EVIDENCE
Learn with references you can verify.
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