Bright AI core capabilities

Core capabilities for smart class management and personalized teaching

Bright AI connects class context, curriculum, assignments, and learning evidence to teacher planning, question generation, differentiated work, analytics, photo grading, explanations, targeted practice, and review.

Content reviewed: August 24, 2026

Eight connected teaching and learning capabilities

Each capability states the evidence it uses and the practical result it produces. These are product workflows available on aixue.app, not claims that AI replaces teacher judgment.

Teacher class management

Organize classes, members, curriculum settings, assignments, and submissions.

Evidence used: Grade, subject, curriculum, class membership, and real submissions.
Practical result: Reviewable class settings, assignment progress, and student records.

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AI teaching assistant

Draft lesson structures, questions, and differentiated assignments in a defined teaching context.

Evidence used: Class, grade, subject, curriculum, concept, and teacher instructions.
Practical result: Teacher-reviewed lesson drafts, questions, assignments, and teaching suggestions.

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Learning analytics

Turn assessments, assignments, mistakes, and practice into actionable learning evidence.

Evidence used: Real answers, grading, submission status, mistakes, and concept performance.
Practical result: Class and student gaps, mastery signals, and teaching focus areas.

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Family engagement

Create reviewable parent updates and progress feedback from learning evidence.

Evidence used: Assignments, assessments, progress, mistakes, and teacher-confirmed information.
Practical result: Parent updates, progress reports, and practical family support suggestions.

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AI homework grader

Recognize questions and student answers from a clear photo and assist with checking each item.

Evidence used: Source photo, recognized question, student answer, and verifiable expected answer.
Practical result: Item-level checks, feedback, and confirmed mistakes for later review.

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Photo question solver

Use the photographed source problem to explain conditions, method, and steps.

Evidence used: Complete source question, image, known conditions, and follow-up questions.
Practical result: A step-by-step explanation that can be checked against the original problem.

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Personalized learning

Organize concept learning, targeted practice, and review from learner context.

Evidence used: Grade, subject, curriculum, assessment answers, practice, and saved mistakes.
Practical result: Current priorities, targeted practice, mistake review, and progress records.

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Worksheet eraser

Remove handwriting from a worksheet image while preserving the question layout.

Evidence used: A clear, complete, and preferably flat worksheet photo.
Practical result: A clean worksheet image that can be compared, downloaded, and reused.

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How results remain reviewable

Source images remain available when image recognition is involved.
AI-generated questions, lesson drafts, grading, and teaching suggestions require review.
Learning conclusions use real evidence and state limitations when records are insufficient.
Regional pages distinguish curriculum contexts without claiming official certification.

Which capability should I use?

How can a teacher manage a class and assignments?

Start with class management, then connect learning analytics or the AI teaching assistant.

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How can I check answers from a homework photo?

Use the AI homework grader and verify recognized content before relying on item-level judgments.

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How can a student understand one difficult problem?

Use the photo question solver for an explanation grounded in the original problem.

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How can a student practice from saved mistakes?

Use personalized learning to connect confirmed mistakes with the current curriculum scope.

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