Rethinking Education: How Artificial Intelligence (OpenAI, ChatGPT, and other tools) can Revolutionize the Learning Experience

Quantilus has been a leader in the use of cutting-edge technology to enhance the learning experience in K-12 schools and universities. We believe AI has the potential to revolutionize the way we think about education and learning, and can help to create more efficient and effective learning experiences for students of all ages. AI can help educators provide personalized, adaptive and targeted instruction to address areas that need remediation. 

Explore how Quantilus is
incorporating AI in Education.

Our teams are working on numerous production systems, prototypes, and proof-of-concepts to harness the power of OpenAI, ChatGPT and other AI tools for EdTech companies and educational institutions. This page contains a sampling of the Use Cases we are solving.

Use Case 1: Automatically Generate Assessments from Content
Automatically create assessments for new content  
  • Extract relevant questions from scholarly articles.
  • Create multiple-choice questions with misleading “incorrect” answer choices.
  • Create questions of multiple types (multiple-choice, boolean, text answers, etc.)
AI Example: Multiple choice question with answer choices generated for the Rudyard Kipling poem “If”.

Question: What is the main theme of Rudyard Kipling’s poem If?

a. Love and relationships

b. War and patriotism

c. Honor and integrity

d. Nature and the outdoors

Use Case 2: Real-time Translation and Subtitling
Generate translations and subtitles in real time – make education more accessible to ESL students.
  • Multi-language audio translations for content spoken by the instructor
  • Simultaneous subtitle generation
  • Translations and subtitles use terminology and jargon of the subject material – go beyond Google Translate
  AI Example: Example of English to Spanish translation of text with technical terms.

English: “The system utilizes a multi-layer perceptron for image classification.”

Spanish: “El sistema utiliza un perceptrón multicapa para la clasificación de imágenes.”

Use Case 3: Measuring Anxiety Levels in Students
Measure anxiety levels in students and raise alarms for high-stress risk
  • Anxiety levels can be monitored through the measurement of pulse rate and body temperature fluctuations
  • Analyze facial expressions, body language, and other visual cues to detect stress
  • Automatically trigger mental health warnings for at-risk and highly stressed students
  • Give parents and teachers data to analyze content difficulty levels so they can manage student stress
AI Example: Description of monitoring high-stress levels in students through AI. “One way to monitor stress in students is through the use of computer vision and facial recognition, that could analyze facial expressions, body language, and other visual cues to detect stress. This can be done through cameras and microphones in the classroom or through videos recorded by students. These data can then be analyzed to provide insights into a student’s overall stress levels, and can be used to identify students who may be at risk for stress-related health issues or who may benefit from additional support and resources.”
Use Case 4: Keep Content Relevant and Fresh
Periodically update content with news and event references
  • Keep students interested in content with relevant references
  • Automatically update content with references to recent events and popular news items
AI Example: History passage about Modern Holistic Medicine, with a reference to the FIFA World Cup.

“Modern holistic medicine is an approach to healthcare that focuses on treating the whole person, rather than just their physical symptoms. This approach recognizes that an individual’s physical, mental, emotional, and spiritual well-being are all interconnected and must be addressed in order to achieve optimal health. One example of holistic medicine being incorporated into a mainstream event is the use of meditation and yoga to help athletes in the FIFA World Cup to manage stress, improve focus and performance, and prevent injury. These practices, which are rooted in Eastern traditions, have been adapted and implemented by sports teams and organizations to help athletes perform at their best, both physically and mentally.”

Use Case 5: Hyper-Localization of Content
Hyper-localize learning content to make it relevant for students
  • Update content for specific locations based on ethnic and geographical parameters
  • Update content based on local terminology and jargon in the location where it is being consumed
  • Update and serve content based on the specific perspective of the audience
AI Example: Paragraph describing the response to the Covid pandemic from an Australian and a Swedish perspective.

Australian Perspective: The government took early action to close the borders and implement strict quarantine measures, which helped to slow the spread of the virus. This, combined with widespread testing and contact tracing, has allowed Australia to keep case numbers relatively low and avoid widespread lockdowns.

Swedish Perspective: The Swedish government has chosen to rely mostly on herd immunity and has not imposed strict lockdowns or quarantine measures. Instead, the government has focused on providing information and recommendations to the population, and keeping schools and businesses open. This approach has resulted in a higher number of cases and deaths compared to other countries, but it has also allowed the country to maintain a relatively normal way of life and avoided the economic and social disruptions caused by lockdowns.”

Use Case 6: Sentiment Analysis of Student Writing
Analyze the sentiment in student generated content to identify mood and stress levels
  • Student writings can be analyzed for positive/negative, happy/sad and a spectrum of sentiments in the middle
  • Sentiment can be tracked individually and as a group (for a class, school, etc.) to monitor the emotional impact of the content and pedagogy
AI Example: Description of the levels of sentiment measured, and how this can be used to monitor stress levels.

Sentiment analysis is a technique used to determine the emotional tone of written or spoken language, which can be used to track stress levels in students. By analyzing student writings, such as journal entries, essays, or other written assignments, sentiment analysis algorithms can identify words, phrases, or patterns that indicate stress, such as negative words or phrases like “anxiety” or “frustrated”.

The analysis can also identify changes in writing style, such as a shift in sentence structure or tone, that may indicate an increase in stress levels. This data can then be used to provide insights into a student’s overall stress levels, and can be used to identify students who may be at risk for stress-related health issues or who may benefit from additional support and resources.”

Use Case 7: Personalized Tutoring with Adaptive Content

Automated tutoring systems based on personalized assessments

  • Serve tutoring content based on individual student weaknesses 
  • Adapt content based on student performance over time
  • Adjust the level of difficulty and pace of instruction based on a student’s progress, providing more challenging or easier content as needed

AI Example: Description of how AI systems adapt content based on student progress.

“If a student is struggling with fractions, the system might provide additional practice problems and interactive tutorials that focus on fractions. The system also uses machine learning algorithms to adjust the level of difficulty of the problems based on the student’s progress. As the student becomes more proficient with fractions, the system will provide more challenging problems.”

Use Case 8: Automated Learning Content Generator
Create content, problems and assessments customized for individuals and groups
  • Automatically generate new content based on specific needs of the individual.
  • Scale math assessments by generating randomized problems of varying difficulty levels.
  • AI can automatically generate math problems by understanding the structure of the problem and using machine learning or computational creativity techniques to generate new and unique problems
AI Example: An AI generated Physics (Mechanics) problem.

“A car of mass 1000 kg is moving at a speed of 30 m/s and it’s brakes are applied to stop. What is the force of friction if the car stops in 5 seconds?”

In this case, the AI system has generated a problem that requires the student to use the equations of motion and the friction force concept to find the force needed to stop the car.

Use Case 9: Chatbot to Answer Questions and Recommend Content
AI-Powered Learning Chatbots as a Master Reference
  • AI models can be trained with the data for specific subjects
  • Automated systems can respond to student questions
  • AI can be used to recommend educational resources, such as videos, articles, and interactive activities, that are most likely to be engaging and effective for a particular student.
AI Example: Legal question posed by a student and answered by a Chatbot .

Legal Question: “What are the legal consequences for breaking a non-disclosure agreement?”

AI-powered Chatbot Answer: “Breaking a non-disclosure agreement (NDA) can have a range of legal consequences, depending on the specific circumstances. If a party to an NDA breaches the agreement by disclosing confidential information, the other party may be able to sue for damages. In some cases, the court may also issue an injunction to stop further disclosures. Additionally, if the NDA is a part of an employment contract, the employee who breaches it may be subject to termination of employment.”

Use Case 10: Predict Optimal Learning Paths for Individuals
Create personalized learning plans for each student
  • AI algorithms can analyze a student’s performance data, learning style, and interests to create a personalized learning plan that is tailored to the student’s unique needs

  • Use computer vision to analyze student’s body language and facial expressions, which can help to identify engagement level and adjust instruction accordingly

AI Example: Structure of a Personalized Learning Plan developed by AI.

A student is struggling in his math class. He has taken a diagnostic test and an AI-powered system has identified that he has difficulty understanding basic concepts of algebra, such as solving equations and working with variables. Based on this analysis, the system has created a personalized learning plan that includes the following elements:

  1. Additional practice problems on solving equations and working with variables.
  2. Interactive tutorials that explain the concepts in a step-by-step fashion with visual aids.
  3. Quizzes that test John’s understanding of the concepts and provide immediate feedback.
  4. Video lectures that cover the concepts in more depth.
  5. Additional resources such as worksheets and games to provide additional practice opportunities for John.

Contact us to discuss how AI can be implemented in your organization.

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Creating The Future of Education

The next decade for education will be dominated by the adoption of AI-enabled technologies. 


Create content and assessments automatically based on adaptive curricula. Refresh and localize content on an ongoing basis to keep it relevant for students.


Provide teachers and students a library of vetted content, accessible through AI-powered chatbots. Proactively recommend content and resources based on individual needs.


Analyze real-time data for personalized learning plans. Track student engagement, sentiment and stress levels, and undertake preemptive remediation when required.

Case STudies
Solving Real-World Challenges

With over 200 experts in data and AI, Quantilus can help make your vision a reality. Our custom engineering services take open source models and adapt them to fit any business scenario without sacrificing scalability or performance. Explore how we’ve leveraged AI to solve our client’s business challenges. 



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