❌  Without CuraAI

• Every student sees the same lesson content

• Failed formative checks go unaddressed

• No personalization to interests or career goals; motivation wanes

• Gaps persist and compound across lessons

✓  With CuraAI

• Gaps detected automatically from in-lesson formatives

• Personalized reteach generated instantly, inline

• Anchored to each learner's field, interests, and background

• Mastery-triggered — only when and where needed

① PROFILE

Learner Profile Build

The student's interests, field of study, career goals, and topic background are compiled into a structured learner profile.

② DETECT

Gap Detection

CuraAI generates an internal learning graph of concepts in the course to detect gaps in student learning (mastery assessment).

③ RETEACH

Personalized Content Generation

CuraAI inserts inline targeted reteach material,  anchored to the student's own interests and goals, for each gap concept.

RQ1  ·  Learning

Does personalized reteach improve learning?

Within each learner, do gap concepts that receive CuraAI's reteach gain more on a neutral cumulative assessment than a matched held-out control concept?

RQ2  ·  Generation Quality

Can CuraAI reliably generate high-quality content?

Is the generated reteach instructionally accurate, genuinely personalized to the individual, and effective?

RQ3  ·  Acceptability

Do learners find it useful?

Do students rate the personalized reteach as more relevant, engaging, and helpful than standard presentation,  and prefer it?

Participants
N = 14 students in CSC 101 (AI Foundations) at URI. Diverse fields of study, CS experience levels, and first-generation status.

Materials
CuraCourse Chapter 2 (AI Foundations); concept knowledge graph; parallel cumulative Forms A/B; learner perception & preference survey.

Control Condition
One gap concept per participant is held out: standard lesson only, no personalized reteach added. Eliminates between-subject confounds.

Safety & Quality Gate
All generated reteach blocks are reviewed for correctness by the research team before any learner sees them. Post-study, all blocks rated by the full 5-member expert panel.

3.9 / 4

Expert Accuracy Rating

Mean instructional accuracy score across all generated reteach blocks, rated independently by a 5-member expert panel

88%

Genuine Personalization

Percentage of generated blocks rated ≥ 3/4 on personalization fidelity — anchored to the individual learner's field, interests, and goals

r ≈ 0.45

Medium Learning Effect

Within-participant matched-pairs effect size — gap concepts receiving CuraAI reteach vs. held-out no-reteach control

Expert Panel Agreement

ICC(2,k) = 0.81   ·   Krippendorff's α = 0.62

Reliable inter-rater agreement across the five-member heterogeneous reviewer panel (content author, college AI instructor, K-12 educator, CS-ed researcher, recent CS graduate). All reviewers rated all generated blocks — a census, not a sample.

Learner Preference

13 of 14 students preferred the personalized version

Learners also rated the CuraAI reteach as significantly more relevant, engaging, and helpful than the standard lesson presentation on the learner acceptability survey.