Editing Ai Education (section)

== <span style="color: #FFFFFF;">Analyzing</span> ==
{| class="wikitable"
|+ AI in Education Application Maturity
! Application !! Evidence Base !! Deployment Maturity !! Equity Risk
|-
| Spaced repetition scheduling || Strong (cognitive science) || Wide (Anki, Duolingo) || Low
|-
| Intelligent tutoring (ITS) || Good (controlled studies) || Niche (Cognitive Tutor) || Medium
|-
| Essay auto-grading || Mixed (rubric-dependent) || Growing || High (bias in scoring)
|-
| LLM tutoring || Emerging || Early commercial || High (access inequality)
|-
| Dropout prediction || Good || Growing || High (self-fulfilling prophecy)
|-
| Question generation || Limited evaluation || Early deployment || Low
|}

'''Failure modes and equity concerns''': AI tutoring systems trained on data from high-resource schools may perform poorly for students from different backgrounds. AES systems can exhibit bias against non-native English speakers or non-standard dialects. Dropout prediction models may unfairly label students, leading to resource withdrawal. Over-reliance on AI tutoring may reduce development of student agency and metacognitive skills. AI-generated explanations can be wrong — students may accept confident incorrect explanations.
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