A critical part of 2BeLive learning ecosystem involves assessments, quizzed and surveys, which used by educators to evaluate students' performance, and collect feedback to improve courses.
However, with thousands of students submitting assessments every week, educators spent enormous time analyzing responses one-by-one.
Manually reviewing student responses was:
- Time-consuming: each course assessment took hours to analyze.
- Inconsistent and subjective: human analysis lacked data-driven accuracy
- Unscalable: the only way to increase speed of assessment analysis was increasing manpower.
To solve this challenge, 2BeLive partnered with Outter to integrate an AI Insights Module that could automatically summarize assessments data, generate reports, summaries and insights in real time.
Tasks
- Transform raw student responses into structured summaries and visual dashboards
- Analyze assessments, Identify knowledge gaps, trends, and learning progressions at high scale
- Provide meaningful summaries and actionable insights for educators
The Challenge: Too Much Data for Manual Processing
Educators Were Drowning in tons of submitted forms:
- Thousands quizzes, open-ended responses, and survey forms were submitted weekly.
- Extracting common patterns, personal weaknesses, and individual performance trends manually was impossible.
Manual Assessment Review Required Too Much Time:
- Educators had to read, analyze, summarize, and extract key points from student responses one by one, form by form.
- In this routine they often missed important trends and spent hours robotically reviewing assessments.
- No Easy Way to Identify Knowledge Gaps & Trends
Educators needed real-time insights on:
- Common mistakes across students
- Trends and common topics in feedbacks and surveys
- Course improvement opportunitiesManual 'by-hand' processing made it barely feasible.
2BeLive platform needed an automatic solution to:
- Analyze assessments & feedback data at scale
- Catch, summarize and present key trends and insights instantly
- Provide actionable feedback and advice to help educators improve their courses
"Before, our educators could only analyze a fraction of student responses manually. Now, AI uncovers insights we never even thought to look for—in seconds.",
Naomi, Head of Partnerships, 2BeLive
The Solution: AI-Powered Assessment Insights
To solve this challenge, 2BeLive integrated Outter Insights Module, an LLM-powered analytics engine that automatically processes, summarizes, and extracts key insights from student assessments.
The system leverages:
- LLM-Based Summarization – Extracts key insights from open-ended answers & surveys
- Trend Analysis & Knowledge Gap Detection – Identifies patterns across student responses
- AI-Generated Reports – Provides actionable recommendations to educators
AI-Powered Assessment Processing & Summarization
Supports Multiple Assessment Types:
- Multiple-choice quizzes (MCQs) – Analyzes student performance trends Open-ended questions & essays – Extracts key themes & student sentiment
- Surveys & course feedback forms – Summarizes educator-relevant insights
Processing Pipeline:
- Step 1: Data Aggregation & Injection – Collects and enriches student response data in real time
- Step 2: NLP-Based Text Processing – Extracts structured data from students' responses
- Step 3: LLM-Powered Summarization – Generates concise takeaways from student-written answers
- Step 4: Insights Extraction – Identifies patterns, trends, and learning gaps
- Step 5: AI-Generated Summary: with key insights and recommendations
- Step 6: Full Assessment Dashboard: allows deep-dive exploration for educators
Trend Analysis & Knowledge Gap Identification
Student Performance Insights
- Identifies trends in correct vs. incorrect answers across assessments
- Detects concepts where students struggle the most
- Flags recurring errors to help improve course material
Sentiment Analysis for Open-Ended Responses
- AI categorizes student feedback into positive, neutral, or negative themes
- Highlights common student concerns (e.g., “Lesson 4 theoretical part was unclear”)
Course Adaptation Recommendations
- AI suggests lesson modifications based on student performance
- Generates personalized learning adjustments for struggling students
TechStack:
- FastAPI, PostgreSQL, Apache Kafka - for high performing backend processing
- LangChain, Mistral-8B, NLTK - for text processing, sentiment analysis and trend extraction
- FastAPI + Webhooks - for lighting fast results retrieval
- Next.js, ShadCN, Plotly - for user friendly educators dashboard
The Results: AI-Driven Assessment Intelligence
4x Reduction in Manual Assessment Analysis Time with AI instantly summarizing responses
99% Accuracy in Trend Identification - with automatic detection of patterns and knowledge gaps
10,000 Responses Processed Weekly - real-time, scalable assessment analytics
Higher Course Completion Rates - personalized feedback improves students retention.
"Previously, I’d spend hours reading through every student's assessment, making notes and checking answers manually. Now, AI instantly check everything for me - correct and wrong answers, topics each student didn't understand fully and even gives me advice how to structure my lessons better."
Hayley, K12-teacher and 2BeLive Partner
