AI Decision Support for Faculty.

Learning Cortex provides clear, data-driven insights into where students are struggling, helping instructors design personalized interventions, generate assignments, and optimize the cirriculum.

Class Insights

Organic Chemistry II · Spring 2026 · 142 students

Live

Class Average

81.4%

↑ 2.3 last 7 days

Predicted Exam Avg

78.6%

high confidence

Below Threshold

12 / 142

threshold @ 70%

Engagement

86%

active in last 48h

Data-driven collaboration

Everything faculty need to create personalized assessments, predict outcomes, improve the curriculum, and support struggling students before exam day.

Individualized AI Assessments

Build individualized quizzes, exams, and assignments for each student that help them address their specific strengths, weaknesses, and knowledge gaps.

  • Assignments can be completed directly on Cortex
  • Alignment with specific content and learning objectives
  • Personalized question pools based on each insights profile

Predictive Gradebook

Log grades and other scores that provide context for the AI models enabling continuous learning and improvement of Cortex predictions.

  • Predicted grades for every student
  • Automatic risk triage with thresholds set per course
  • Longitudinal optimization of AI models using real outcomes

Customizable Insights

Visualize data insights from the entire class, specific performance subgroups, or individual students, and identify the content causing the most difficulty.

  • Per-student score trajectories with a risk threshold
  • Weak pages, chapters, modules, and topics ranked by mastery %
  • AI recommendations for next best action

Integrations & Activity Tracking

Cortex helps unify study activity across the tools students already use, encouraging adoption and daily engagement.

  • Connections with platforms like Google Drive
  • LTI Integrations for use within existing LMS tools
  • Pipeline for importing open-source web content

Faculty Decision Support

Gradebook

142 students · Predicted Final 79.2%

Grade Distribution

3
<60
9
60–69
29
70–79
58
80–89
43
90–100
Maya Kapoor
94.7% 1.8
Jordan Torres
62.3% 4.1
Alex Brooks
86.2% 0.7
Predictive Gradebook

Help students improve before the final exam

Cortex forecasts student trajectories so personalized interventions can happen before the test.

Class Insights

Module Breakdown · Past 14 days

Unit 5 — Aromatic Substitutionchallenge topic 2.1
61.2%

18 students at risk

Unit 4 — Alkene Additions 1.4
73.8%

9 students at risk

Unit 3 — SN1/SN2 Reactions 3.6
79.4%

5 students at risk

Move the threshold to change which students are flagged at-risk across the gradebook.

Classroom Insights

Find weak topics

Cortex AI identifies difficult topics early, and maps student challenges to specific parts of the cirriculum. With these insights, faculty can make targeted changes and improve outcomes.

Jordan Torres

Current 62.3% · Predicted Final 58.9%

High Risk

Weak Topics

Aromatic substitution
34%
Alkene addition mechanisms
48%
Resonance structures
55%
SN1 vs SN2 reactions
68%

AI Recommendations

Office hours referral

Declining trajectory & low engagement.

Assign remedial quiz set

8-question quiz targeting Aromatic substitution.

Pair with peer mentor

Pair with Maya Kapoor or Ravi Chen.

Next Best Actions

Office Hours optimized by AI

Cortex insights come with recommendations for best next steps, allowing faculty to spend more time with students and less time reviewing data manually.

Bring Learning Cortex to your courses

See a walkthrough on your own courses and explore pilot options for your department.