AI-Powered Learning Management System
Powered by Large Language Models, Natural Language Processing, and Predictive Analytics. Multi-model AI architecture (Claude, Gemini, GPT-4) with real-time NLP-based question generation, rubric-aware automated grading, stylometric AI plagiarism detection, and predictive early warning systems. Compliant with DigCompEdu, GDPR, and EU AI Act.
ATLAS LMS leverages multiple AI/ML disciplines — from transformer-based LLMs to statistical pattern recognition — delivering intelligent automation across the entire learning lifecycle.
Transformer-based large language models (Claude, Gemini, GPT-4) for semantic text analysis, question generation from documents, and context-aware answer evaluation with multi-criteria rubrics.
Multi-provider LLM fallback chain ensures 99.9% uptime. Document chunking with token-aware splitting. Bloom taxonomy auto-classification via prompt engineering.
Statistical models for dropout prediction, success forecasting, attention pattern analysis, and engagement scoring across video content and assessments.
Risk scoring algorithm analyzes 15+ behavioral signals. Weekly trend detection with moving averages. Attention heatmaps reveal content engagement patterns.
Multi-layered detection combining structural analysis, linguistic fingerprinting, and behavioral indicators to identify AI-generated content (ChatGPT, Gemini, Claude) with confidence scoring.
7-layer detection pipeline: sentence structure analysis, markdown pattern detection, politeness markers, academic register analysis, error-free writing detection, depth-to-topic ratio, and conversational AI signatures.
Personalized learning paths with dynamic difficulty adjustment based on real-time performance metrics, learning style profiling, and competency gap analysis.
Individual learner profiles built from assessment data. Automatic remedial question generation for weak competencies. EQF-aligned competency mapping across curriculum standards.
ATLAS LMS integrates 9+ AI/ML technologies spanning NLP, predictive analytics, stylometric analysis, and adaptive learning.
From raw content to personalized learning outcomes — every step powered by AI. Click any stage to explore the technology behind it.
6
Processing Stages
3
LLM Providers
15+
Behavioral Signals
7
Detection Layers
Eight AI/ML-powered modules working together for a complete learning ecosystem.
Transformer-based LLMs analyze document semantics and generate curriculum-aligned questions. Multi-provider architecture (Claude, Gemini, GPT-4) with automatic fallback chain. Token-aware document chunking for long texts.
NLP-powered rubric evaluation with 4-criteria scoring matrix. Multi-dimensional analysis: accuracy, consistency, scientific validity, and originality. Includes 7-layer stylometric AI plagiarism detection.
Engagement analytics powered by attention pattern recognition. Video heatmaps reveal drop-off points, re-watch zones, and quiz impact on retention. AI-generated instructor suggestions.
WebRTC low-latency streaming with real-time quiz delivery. Live engagement scoring, instant result aggregation with bar chart visualization, and automatic VOD archiving.
Auto-generate PDF certificates and Open Badge 2.0. QR-verifiable digital competency credentials.
Statistical pattern recognition for early warning system. 15+ behavioral signal analysis, moving average trend detection, dropout probability prediction, and engagement scoring.
Adaptive learning engine with dynamic difficulty adjustment. Individual learner profiles built from multi-dimensional assessment data. Competency gap analysis with automatic remediation.
AI-powered progress tracking and reporting capabilities integrated into the platform.
The demos below use real AI APIs. Results are generated in real-time.
Enter lesson text, AI generates questions automatically
Örnek: 9. Sınıf Tarih - Osmanlı Devleti konusu yüklenmiş durumda
Questions generated by AI aligned with curriculum standards
Click Generate Questions
AI will automatically create questions from the text
Automatically detects answers copied from AI chatbots like ChatGPT and Gemini.
If these patterns are detected, a <strong>maximum of 1 point</strong> is given:
If these indicators are detected, a <strong>maximum of 3 points</strong> is given:
These situations generate a <strong>warning</strong> but do not reduce the score:
Analyze which parts of each video see attention drops, how quizzes affect engagement, and which sections are re-watched.
12:00 min | 247 views | Avg. 72% completion
4:30
Attention Drop Point
52% of viewers dropped off here
+26%
Post-Quiz Revival
Engagement increase after Quiz 1
3:00-5:30
Re-watched Section
35 students re-watched this section
78% / 62%
Quiz Accuracy Rates
Quiz 2 was found more challenging
AI Instructor Suggestion
Attention drops significantly in the 3:00-5:30 section. Shortening this section and adding a quiz or visual material could increase completion rates by an estimated 15-20%. Quiz points increase engagement by an average of 26% — adding an additional quiz around 4:30 is recommended.
Zoom-like live streaming infrastructure with instant quiz delivery, chat, and leaderboard.
Live streaming directly from browser. Camera, microphone, and screen sharing. Sub-second latency.
Teacher sends quiz to all viewers with one click. Multiple choice, true/false, open-ended. Real-time results.
Moderated live chat, emoji reactions, pinned messages, slow mode, and subscriber-only mode.
Top-scoring students are ranked on the leaderboard. Detailed reports are generated after the broadcast.
Live lessons are automatically recorded and available for on-demand viewing. Quiz results are preserved.
Live Lesson Preview
İstanbul hangi yılda fethedildi?
At-risk students are instantly identified by the early warning system. Click any tile to view details.
30
Total
17
Low Risk
7
Medium Risk
6
High/Critical
73
Class Avg.
Click a student to view details
Each question is mapped to curriculum learning objectives. Weak objectives are identified and remedial questions are automatically generated.
3
Mastered
3
Good
2
Needs Work
2
Weak
Analyzes causes and consequences of migrations
%45 mastery — Remedial questions recommended
Discusses the effects of tolerance policy
%38 mastery — Remedial questions recommended
AI Remediation Suggestion
Automatic remedial questions can be generated for objectives 9.3.3 (38%) and 9.2.3 (45%). The "AI Question Generator" can create easy-medium level questions targeting these specific competencies.
Separate panels for administrators, teachers, and parents with 12+ modules.
Upload, edit, analytics
Auto question generation & management
Create, schedule, record
Individual performance analysis
Dedicated tools for teachers
Performance reports for parents
At-risk student detection
Exam-focused study tools
Standards-based analysis
PDF/Excel report generation
Content & comment review
API keys & usage
All modules accessible from a single admin panel. School, district, and regional authorization supported.
Integrate with your existing education infrastructure in minutes using REST API, SDK, LTI 1.3, and xAPI support.
Access from any platform
npm install atlas-lms
Shortcode & Gutenberg block
Moodle, Canvas, Blackboard
Learning Locker compatible
Embed on any site via iframe
Full compliance with GDPR, EU AI Act, and DigCompEdu framework standards
All data is encrypted end-to-end
Data can be kept within your own infrastructure
Rate limiting, daily quotas, and access control
Bulk deployment to schools, centralized admin panel, district-level performance reporting
Direct connection to existing Moodle/Canvas systems via LTI 1.3 integration
Standards-based question generation, per-student weak objective detection, and remediation
Video-based distance learning, certificate programs, and participant tracking
Timeline: 0-1 year
Timeline: 0-1 year
Timeline: 1-3 years
Timeline: 1-3 years
Timeline: 3-5 years
Machine learning-powered attention analysis, success prediction with multi-factor regression, dropout risk assessment via behavioral signal processing, and personalized intervention planning. Explore the system with 3 different student profiles below.
78
Attention Score
85
Predicted Success
82%
Success Probability
12
Risk Score
Last 5 weeks performance trend
Achievement success rates
Video Tamamlama
Son 30 günde %92 tamamlama oranı
Quiz Performansı
Ortalama 8.2/10 puan
Oturum Süresi
Ortalama 12 dk (beklenen: 25 dk)
Strengths
Areas for Improvement
Personalized intervention plan
Açık uçlu soru pratiği artırılmalı — yazma becerisi geliştirme etkinlikleri önerilir
Çalışma saatlerini 20:00-22:00 aralığına çekmesi önerilir
Grup tartışma etkinliklerine katılımı teşvik edilmeli
Haftada 2 saat açık uçlu soru pratiği
Başarılı öğrencilerle eşleştirilmiş çalışma grubu
AI-generated teacher notes
Bu öğrenci görsel materyallerden daha iyi öğreniyor — video içerikler ağırlıklandırılmalı
Kısa quizler motivasyonu artırıyor, uzun sınavlarda performans düşüyor