In the era of AI and Machine Learning a revolution is expected to occur  in education. New technologies can make a significant impact on the students’ educational journey. And while some AI-powered solutions have been around for some time the educational industry has been slow to adopt them. AI has the power to optimize both learning and teaching, helping the education sector evolve to better benefit students and teachers alike:

Differentiated learning: Personalization is one of the biggest trends in education. With the use of AI, students now have a personalized approach to learning programs based on their own unique experiences and preferences. AI can adapt to each student’s level of knowledge, speed of learning and desired goals so they’re getting the most out of their education. Plus, AI-powered solutions can analyze students’ previous learning histories, identify weaknesses and offer courses best suited for improvement, providing many opportunities for a personalized learning experience. But while the term personalization is used for a (static) one-time adaptation of an educational aspect to the needs or preferences of a user, whereas adaptation refers to the continuous adjustment of the educational procedure based on the actions and performance of a user and the current state of the educational procedure towards a desired state. 

It has been suggested that the adaptation process should involve two distinct challenges: User Identification and Content Adaptation.

User Identification is the process of identifying and inferring the characteristics of the student. There are two sub topics that are extremely relevant for identifying a user and keeping him actively involved in the interactive learning process: User Models for Interactive Learning and Detection of User Engagement. 

Content Adaptation can be used to provide an effective system response to the student, by presenting a personalized view of the educational content and learning materials.

Task Automation: AI has already been used in different industries to automate tasks, and it will come in handy the same way in the education sector. Professors and teachers usually spend a lot of time on non-teaching tasks, and it overwhelms them. Artificial Intelligence will automate these tasks to have more time to do their primary work of teaching without being bothered with administrative tasks.

Ubiquitous learning: AI-powered tools make learning accessible for all students, anytime and anywhere. Each student learns at their own pace, and 24/7 access makes it easier for students to explore what works for them without waiting on an educator. More than that, AI-powered chatbots are specifically built for education as a sector. They work as students’ assistants round the clock to provide answers to their queries at any time. So, they don’t have to wait to see the teacher in their office or the classroom.

Education Analytics: AI-based systems can analyze an enormous amount of information. Using ML and AI tools student work can be assessed through data mining techniques, analyzable either as individual progress, or comparisons across cohorts. The increasing use of the produced data can help us to improve, understand, and personalise the learning process, and more generally, various aspects of the educational operation.

Multimodal Meaning. AI can help teachers create smart content that makes teaching and learning more comfortable for them and the students, respectively. Today’s learners need to be able to use digital media to juxtapose and link text, diagram, table, dataset, video documentation, audio recording and other media. Across all subject areas, meaning making and knowledge representations are supported and enhanced today by digital production skills and technologies. AI can help generate bite-sized learning, study guides, digital textbooks, all within the framework of digital learning. Learning content, such as simulation, visualization, and web-based study environments, can be generated and updated regularly with AI. This ensures that information is up-to-date.

Metacognition and Metamemory. Metacognition provides an Artificial Intelligence system with a sense of Self-Analysis, or Introspection, allowing the system to “think about what it thinks.” Metamemory is a concept of an Artificial Intelligence system’s memory capabilities and strategies that can aid in memory representation, retention, mining, retrieval, as well as the processes involved in memory Self-Monitoring.  Providing  Metacognitive  and  Metamemory structures  and  processes  within  an  autonomous  AI educational system, can help us finetune the AI system and also can provide Safeguards against confusion and errors from lower cognitive processes.