OverviewClass ManagerPracticum ManagerAI DetectionAI Teaching AssistantUniversal ReaderOER Library
Integrity Hub

Evidence-Based Integrity Analysis

Schologic uses a multi-model approach to detect AI-generated content with unparalleled accuracy. We provide transparent, granular reporting so you can make informed decisions.

Forensic Evidence

The "Glass Box" Approach to
Academic Integrity.

Stop guessing. "Black Box" detectors give you a score without an explanation. Schologic uses Linguistic Forensic Analysis to identify patterns of deterministic structure.

Visual Evidence Heatmaps

Research shows teachers trust AI scores 3.5x more when they can see specifically why a paragraph was flagged.

Sovereign Data Privacy

Student data remains in your institutional tenant. We match against Open-Weights Models, ensuring full FERPA compliance without 3rd-party API leaks.

Submission Analysis

Alpha DujaIntroduction to AI1/30/2026
AI Probability
55%

Document shows strong patterns consistent
with AI generation.

Distribution Analysis

HumanMixedAI
Segment Analysis
#01 Flagged

Supervised learning uses labeled data to predict outcomes, unsupervised learning finds hidden patterns in unlabeled data, and reinforcement learning (RL) trains agents via rewards through trial-and-error interaction. Supervised learning is for mapping inputs to known outputs, while unsupervised learning focuses on structure discovery, and RL focuses on maximizing future rewards.

Confidence
100.0%

The Detection Engine

1

Segment Analysis

Submissions are split into semantic units (sentences or paragraphs) based on your Class Manager settings to isolate specific AI-generated claims.

2

Multi-Model Scan

Each segment is run against 3 specialized models (RoBERTa, AI Content Detector, OpenAI Base) to detect different generation patterns.

3

Triangulation

Scores are weighed and aggregated to filter false positives, producing a final "Authenticity Score" visible in your Gradebook.

Data Sovereignty

Why Open Source Models?

Most detectors are "Black Boxes"—proprietary APIs that send your student data to 3rd-party servers where it may be stored or used for training.

Schologic takes a different approach. We deploy Open-Weights Models (like RoBERTa) directly within your institutional tenant.

  • Zero Data Leaks: Student essays never leave our secure infrastructure.
  • Full Transparency: You can inspect exactly how the models are trained and what data they use.
  • FERPA & GDPR Compliant: No murky 3rd-party data processing agreements.
Why It Matters

Protecting the Value of a Degree.

Academic integrity isn't just about catching cheaters—it's about preserving the value of education, especially in online classes. In an era of instant answers, ensuring that students engage with the material, think critically, and produce original work is more crucial than ever.

AI detection helps maintain a level playing field, validates genuine student effort, and upholds the standards that give Schologic degrees their meaning.

Instructor-Controlled Intelligence

One size does not fit all. Different assignments require different eyes. We give you the power to choose the right model for the job.

RoBERTa Large

HC3 Corpus Trained

The academic standard. Best for formal essays and research papers. Trained to spot standard GPT-3/4 patterns.

AI Content Detector

Mixed/Humanized Data

A more aggressive model. Best for creative writing or when you suspect "humanizing" tools were used.

OpenAI RoBERTa

Apollo Dataset

Specializes in short-form content and reviews. Use as a "Second Opinion" to validate other flags.

Flexible Scoring Logic

Why Weighted?

Best for most classrooms. It mimics human intuition by looking at the "density" of AI signals rather than just one-off flags.

Why Strict?

Ideal for high-stakes exams. It significantly reduces false positives by ignoring low-confidence signals entirely.

Why Binary?

For zero-tolerance policies. Flags a document if any single paragraph is detected as AI. Use with caution.

Weighted
Takes the average probability of all highlighted segments. Best for nuanced evaluation.
Recommended
Strict
Only counts segments with >90% AI probability. Minimizes false accusations.
Conservative
Binary
Flags submission if ANY segment exceeds 50% probability. Maximum scrutiny.
Aggressive
Testing Sandbox

The AI Lab: A Sandbox for Integrity

We don't believe in "set it and forget it." The AI Lab allows you to paste sample text and test different models and granularity configurations in real-time.

Use the Lab to "Calibrate before you Grade." Test known AI text and known human text to understand how different sensitivity settings affect the final Score.

AI LAB PREVIEWSANDBOX MODE
Model:RoBERTa Large
Granularity:Sentence Level
Status:Calibrating...

Our Stance on Academic Integrity

AI detection is probabilistic, not deterministic. We provide these scores as evidence to support instructor judgment, not as absolute proof of misconduct. We recommend using our "Weighted" scoring method for the most fair assessment.

Limitation: No detector is 100% accurate. False positives can occur. Schologic is designed to be one tool in a holistic grading process.

Frequently Asked Questions

Common questions about accuracy, models, and privacy.