The new world of Al-Based adaptive Education

What is the Al-Based Adaptive education system?

Adaptive education refers to imparting education through computer-based technology. Adaptive learning systems adapt the direction and speed of learning based on data, and allows delivery of personalized learning. Al-Based Adaptive education systems introduce animated changes in faculty roles, enable innovative teaching practices, and incorporate a variety of content formats.

The basic concept of Al-Based Adaptive education is to alter teaching models as per the needs of learners and enhance education and training by providing students with individualized learning plans on the basis of the record of data collected both before and during the learning process to help students meet their individual learning needs.

Adaptive Learning Strategy

In order to specifically choose a suitable learning approach, the literature suggests a broad variety of teaching methodologies that fulfills learner’s needs. The learning strategy is primarily focused on the learner’s style, which is defined by FSLS and established by the WAKA kit. The evaluation and English level are also important factors in determining the LO form that is used with a specific learner style.

Before the learner begins learning the certificate content, an assessment is performed to ascertain the student’s background experience and expertise in computer skills. Two key attributes ‘ICDL Learning Strategy Type’ and ‘ICDL Learning Strategy Order’ construct the Adaptive E-learning strategy applied for ICDL programs.

A Proposed Adoptive Model

The proposed adaptive learning system is based on purely learning style. Learner repository shows learner model and domain model. The learner model holds all of the information about the learner that is gathered from questionnaires. The domain model also includes metadata about learner data including language, title, definition, size, format, resource type, copyrights, and more.

Artificial Intelligence

Education these days is taking large springs in the principle of adopting Artificial Intelligence. Artificial Intelligence (AI) plays varying roles supporting both existing and emerging technologies. In the area of learning and studying, it plays a key role in Intelligent Tutoring Systems (ITS).

In 1950, Carnegie Mellon University’s Allen Newell and Herbert Simon invented artificial intelligence (AI) to solve probabilistic and numerical problems. Later, this led to incorporating mathematics, economics engineering etc.

Artificial intelligence has primarily been applied to education in the form of tools that aid in the development of skills and the testing of systems.

AI-based schooling in the future will propel intensive era application, including innovation, and provider optimization. Artificial intelligence training is continuously evolving showing new ways in every sector including education. 

Smart Pedagogy for Digital Transformation

Education based programs and content technologies presently are working on smart pedagogy designs digital platforms that use AI for teaching, evaluation, and provide feedback to learners about their study progress.

Innovative digital systems under Smart Pedagogy prepared for educational institutes or academies can read the expressions on students’ faces, indicating that they are having difficulty understanding the subject, so the curriculum can be modified to respond to the subject.

Furthermore, the implementation of synthetic intelligence technology in education necessitates collaboration among diverse fields such as neuroscience, cognitive technology, psychology, mathematics, and training. The advancement of AI-based education would be supported by interdisciplinary applications. AI has the following characteristics:

  • Excellent ability to reproduce benevolent traits.
  • Best judgment
  • Beneficial issue understanding
  • Understanding terminology
  • Finding difficult situations
  • Perceptual analysis

Discussing the intelligence level, then AI can be categorized into three levels:

  • Narrow artificial intelligence
  • General artificial intelligence
  • Super artificial intelligence

Advantages of Adaptive Learning

Adaptive learning is reviving the classroom and truly revolutionizing the way education is delivered. Students learn in a variety of ways, despite the fact that they are categorized into wide categories such as visual, spatial, logical, social, and so on. This modern learning style is data-driven and teaches in a non-linear manner.

It can monitor student progress as it teaches, adapting its instruction as needed and providing teachers with useful data to help them become more successful educators. Following are some big advantages of Al-Based adaptive education:

  1. Faster and high quality student progress
  2. Adapts to different abilities
  3. Improves the level of understanding
  4. Engages students
  5. Maximizes student learning efficiency
  6. Educates students using various methods and media
  7. Improves certification and licensure exam outcomes.
  8. Provides focused remediation based on each student’s performance

Facilitating Self-Led Learning through an Adaptive Learning System

During and after the pandemic, self-led learning, or the opportunity for students to take care of their own learning at their own speed or stage, can be a game-changer.

However, EdTech approaches are particularly appealing, and allow students to learn at their own speed with minimal outside assistance.

Adaptive Learning has also brought such teachers training which introduces a mixed both traditional and digital education system. Students may not unnecessarily insist on getting visuals, tutorials, pictorial notes etc. Teachers will address it by following the rules taught to them in teachers training.

Predictive Analytics

Combining adaptive learning with predictive analytics has optimized student-learning and produced positive results. Algorithms are much better than humans at analyzing data. As a result, students receive material, prompts, and strategies that adapt in real time to meet their needs and abilities. Following points are easily processed by AI-based learning systems:

  • The amount of time spent on each task
  • Response latency
  • Evaluation performance

COVID-19 Experience and Technology Based Learning

We can no longer depend on conventional forms of education, as the COVID-19 pandemic has already taught a lot. So, technology is increasingly likely to diversify the means of supporting students in the future of learning.

Adaptive systems have the potential to promote self-directed learning and other types of learning, making it easier, more accessible and engaging. For using adaptive learning strategies, firstly you target particular courses, fetch best suit research softwares, and identify larger strategic goals.

Make sure your class incorporates active learning techniques like research, critical thinking, and information construction. Include different methods to handle learner variation related to academic and social-emotional support.

The World Changed

Thankfully, Al-Based adaptive education system has changed the world and yet to bring wonders. Digitization through AI in education has been a broadly preferred move. Furthermore, expecting digital tutors aiding human teachers and students is no longer a dream.

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