More feedback capacity without giving up professional judgment.
The more legitimate learner and educator context available, the more useful the next action becomes.
TEACHER WORKFLOW
Let AI handle repetition. Keep judgment human.
HAOLLA turns assignment feedback into a human-in-the-loop workflow: AI drafts analysis, exceptions rise to the teacher, and revisions become longitudinal learner signals.
HAOLLA METHODDraft → exception → teacher judgment
AI supports repeatable analysis while important judgment and learning ownership remain human.
HAOLLA is not positioned as a substitute teacher.
HAOLLA avoids unverified claims of official status, guaranteed outcomes, affiliation or scoring authority.
HOW IT WORKS
Start small. Use the result to decide what comes next.
A single analysis matters only if revision and re-performance become useful learning signals.
출발 맥락을 명확히 하여 불필요하고 방향 없는 학습을 줄입니다.
목표를 관찰 가능한 행동으로 전환하여 유용한 학습 신호를 만듭니다.
학습량을 늘리기 전에 가장 영향력이 큰 변화부터 분리해 피드백합니다.
수정된 수행 결과를 다음 학습 설계와 판단을 위한 근거로 연결합니다.
HUMAN-CENTERED BY DESIGN
Learning ownership matters more than automation volume.
Learners revise and explain, educators retain important judgment, and AI helps with repeatable analysis and pattern detection.
✓Human override
✓Revision-first workflow
✓Context + longitudinal signals
FAQ
What to know before you start
Do I need to change my curriculum?
No. The pilot is designed around one assignment you already use.
Can a teacher override AI feedback?
That is a core design principle. Important decisions should remain reviewable and editable by educators.
How should I evaluate the pilot?
Measure turnaround time, teacher minutes saved, revision quality, exception rate and whether the feedback is actually usable.