When AI Meets Education

Nadine Kahaleh , Aug 07 2017

As children, we all hated school. It’s the unspoken secret. We murmured it in the halls and the classrooms, and shared it in whispers with other schoolmates. Even the geekiest ones hid a bit of that despise in the bottom of their hearts, but were too proud to admit it. Getting pulled out of our beds early in the morning, five days a week, just to listen to some adult throw a bulk of nonsense at us – no wonder all the grim faces! 


Contemporary learning methods are still cursed with being terribly static; they stand very far from engaging learners and crafting interactive educational methods. Today, with technology advancements sprouting here and there, and with the heroic march of Artificial Intelligence (AI) through the doors of many sectors, the way we process and interact with information is truly transformed, from Conversational User Interfaces (CUI) in smartphones or home devices, to chatbots, to humanoids. So, why not education? AI-Ed can help decipher the micro-steps that students go through while being taught a certain subject, and process this data to better the educational experience. 

According to Pearson’s released report, named “Intelligence Unleashed”, AI operates according to two defined components – first the knowledge about the world they interact with, and second, smart algorithms to help them process this knowledge. When it comes to AI-Ed, there are three main models that represent this knowledge about the world, they are:

  • The Pedagogical Model which refers to the different approaches to teaching.
  • The Domain Model which represents the subject that’s being taught to the learner.
  • The Learner Model in reference to the student.

So how does AI deliver personalized learning – technically? The mechanism, in the grand scheme of things, is simple to understand; AI algorithms process the knowledge transmitted by the three aforementioned models to select the most suitable content to be delivered to the learner, based on the latter’s capabilities and needs. In the meantime, AI will be analyzing the student’s performance and interactions. By aggregating and analyzing these interactions, AI will estimate the student’s current state and ensure that the learning experience is in harmony with the student’s cognitive and affective status. 

Learning Jetsons

Other than automating menial tasks and saving teachers’ time, AI leverages softwares to adapt to students’ needs and cater to their learning pace; these softwares are divided to three categories: Intelligent Tutoring Systems, Intelligent Support for Collaborative Learning, and Intelligent Virtual Reality.

With the use of these smart softwares, many teaching methods will be radically transformed to serve for the development of teacher, student, and the relationship between both. Furthermore, AI technologies will positively affect: personalized learning methodologies that focus on equipping the learner with long-term memories stored in the mind for future need, mastery-based learning which is focused on moving forward with cumulative subjects once the student has mastered all the concepts that precede it, and finally experiential learning which represents the process of learning through hands-on experience. 

Intelligent Tutoring Systems (ITS) 
Simulating a one-to-one human tutoring experience, ITS leverage AI to deliver learning activities that cater to students’ cognitive needs; it provides targeted and timely feedback.

Many ITS use machine learning techniques, self-learning algorithms that aggregate and analyze large data sets, along with neural networks; this combination allows the systems to decide on the type of content that should be delivered to the learner.

A valid example in this context is the iTalk2Learn System platform, it teaches fractions; it uses the learner model that stores data about the student’s mathematical knowledge, their cognitive needs, their affective or emotional state, the feedback they had received and their responses to that feedback.

On another note, the tutoring systems that are model based utilize a number of AI-Ed tools that tailor the learning experience to the student’s cognitive and affective states, allows them to discuss and question the subject being taught, include open learner models that motivate the students by keeping them aware of their own progress, along with social simulation models that help the student understand the subject by understanding the culture and the social norms behind it.


Intelligent Virtual Reality 
Virtual Reality (VR) is all about simulated immersive experiences. It creates an environment where learners get the chance to explore, interact, and manipulate certain elements. They are therefore capable of using these virtual experiences in the real world. Today, students can explore a nuclear power plant, wander through the streets of Ancient Rome, or orbit around the outer planets. 

University SandBox

Coupled with AI, VR becomes intelligent and delivers an optimized virtual experience. It offers an environment that can interact or respond to the student’s reactions. Intelligent synthetic characters are incorporated to the virtual world; they can play roles in setting that can be dangerous or unpleasant to the student.

In this context, we mention FearNot, a school-based intelligent virtual environment. This system presents the student with bullying incidents showcased as a virtual drama. Students who suffered from bullying can immerse themselves as characters in the drama, all the while, exploring bullying issues and effective coping strategies.

In the MENA, Cherpa is one of the few startups that utilize AI in the field education; it’s an online platform that teaches robotics and coding. Ibrahim Ezzedine, co-founder of Cherpa, explained to ArabNet how the platform operates. Accompanied by an intelligent chatbot that acts as a virtual instructor and guides the learner throughout his/her entire journey, the student begins by selecting one of the many available projects (Astronomy, medicine, agriculture, industrial, etc.) Further to the selection, the student is given an overview of the lesson with its learning objectives. The learning subject will then build and code the physical circuit. Once the intelligent chatbot validates that the circuit is error free, the student enters a virtual world with which the actual circuit interacts. For instance, if a student built a joystick, this production will be incorporated into a virtual space mission to Mars for NASA. Each completed mission unlocks a new lesson. 


This immersion has the capacity to unburden the students from what learning scientist, Chris Dede, calls “trapped intelligence”; it allows them to change the way they look at themselves. 

Intelligent Collaborative Learning
Collaborative learning has proven itself to be a rather effective method of learning, as it engages learners in constructive dialogues around the subject being taught and triggers a sense of awareness and curiosity in the student’s mind. It also motivates the learner, and equips him/her with the skills of being proactive in a group.

However, creating the sense of collaboration between group members can be quite the challenge. Enter AI-Ed - the technology supports several approaches in that context:

  • Adaptive group formation – Coupled with data about each learner in the classroom, AI’s goal is to design a grouping of students that share the similar cognitive level and interests.
  • Expert facilitation – AI techniques provide collaboration patterns that are used as an interactive support to the collaborating students. For example, Markov modeling, an approach using the probability theory to represent randomly changing systems, identifies collaborative problem-solving strategies.
  • Virtual agents – They can act as an expert a coach or a tutor, a virtual peer (fellow innovative student), or someone the students have to teach themselves.
  • Intelligent moderation – Using machine learning and shallow text processing techniques, they help the teacher in analyzing discussions all the way to reaching a productive collaboration. 

Putting Theory to Practice

As a Conclusion
AI is a disruptive force that just reached the Education sector; it is the only force that will free the student from accumulate knowledge gaps, understand the student morale and cognitive capacities, and provide him/her with the educational path that’s mostly suitable to them. AI-Ed will pave the way to personalized education.

Many have questioned whether or not integrating AI to the education sector would force teachers to step aside; the truth is, AI won’t replace teachers in the classroom, it will only urge them to develop new research and management skills. Brought together, teachers and AI techniques, will revolutionize educational systems.






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