Posted by: Memory Staff
Published: Nov 14, 2018 Approx. 6 minutes reading time

Algorithmic ELearning

Algorithmic ELearning

Benefits of Algorithmic Learning Applications

The rapid proliferation of information technology makes eLearning an invaluable learning tool in modern-day learning systems. It broadens a learners scope of knowledge and experience whether they are using it during personal study or in a classroom setting. ELearning is not only important for students, but also for teachers given the increased communication and collaboration of multimedia tools.

At first, this mode of education served as a way to provide electronic texts for students to read. This changed over time as developers integrated other technologies that increase engagement and interaction. For example, new technologies enable tutors to enhance their teaching skills when explaining complex procedures. Developers also integrated tools that allow just-in-time learning, allowing learners to learn-on-demand.

In addition, eLearning developers have taken to applying algorithms and artificial intelligence in the education sector to improve learning. Also referred to as a biased algorithm, this form of eLearning is designed to develop individual capabilities. Today we look at other benefits of adopting algorithmic eLearning in schools.

Personalisation

Modern-day learning is about creating a student-centric environment where the learners can choose the pace, learning objectives and tools used based on their interests. Algorithm-based eLearning platforms help tutors personalise learning by promoting a learning pace designed for the learner, the ability to learn at any time and use student voice and choice. This form of learning was only available to a few due to cost concerns. As a result, students are empowered to develop their skills, and their learning needs are met. Keep in mind that a good learning system is evaluated based on its ability to adjust to the learner’s time, strengths and weaknesses, referred to as machine learning.

Enhances Spaced Repetition

ELearning enhances this learning technique as learners have to use readily accessible devices to access information. Spaced repetition is also known as spaced rehearsal; a learning technique that increases the intervals of time the student revises learnt material. Usually, learners are required to read large texts then retain them in their memory for future use.

The concept is based on the fact that the forgetting process begins between the time a learner reads content for the first time and the moment he repeats it. Attempts to retrieve that information after a long time causes the brain to work harder compared to when the learner repeats reading or learning the material regularly.

Algorithmic eLearning helps you engage with the content regularly especially during revision thus, improving retention and your ability to remember and retrieve that information. Spaced repetition also comes in handy when a student intends to learn a second language. For example, when learning Spanish, students use eLearning platforms to enhance vocabulary acquisition. A good eLearning system uses an algorithm that repeats questions to increase the time interval between each repetition. It also helps the learner practice the vocabulary or answers to specific questions.

Recognises Patterns in the User’s Past Learning Behaviour

Algorithm-based eLearning monitors the student’s performance registered in the learning management platform, tailors future sessions, topics and other learning material to respond to the needs of the learner. It is beneficial where a large number of students with different abilities and experiences enrol for a course.

The algorithm actively adopts the course to these fluctuations to provide customised content. The feature benefits students in two ways. First, knowledgeable students advance faster using content tailored to their abilities. Secondly, less versed students have an opportunity to work on challenging tasks and improve performance before they move ahead in the course.

Increased Interactivity

The main obstacle of effective learning is passiveness. Content that is meant for consumption via a frontal instruction or video is less likely to engage a student’s long-term memory because he has not experienced such knowledge. Algorithmic eLearning offers numerous ways of engaging students actively, e.g., through real-life scenarios that require the learner to acquire knowledge; not the passive consumption of content. This way, tutors no longer need to give a list of activities for students to perform. Virtual space technologies are also used to initiate more interaction with students. As a result, the students ask more questions and come to class prepared for the lessons. Other benefits of active engagement of students include:

  • Enhanced student collaboration, which helps develop their interpersonal skills. As a result, the learners engage in more positive peer interactions in the classroom thus, developing useful social and emotional learning skills outside a class setting.
  • The learners are more accountable to projects and assignments given by the tutor
  • The learners also develop confidence in talking in class because they have a chance to interact with their peers in the online space

Increased Motivation

Algorithmic eLearning allows learners to obtain knowledge using a personalised approach, which focuses on their knowledge gaps instead of using a passive, redundant curriculum. Naturally, students loathe going through unnecessary parts of a course; it is the most common demotivating feature of an eLearning program.

With algorithmic eLearning, such demotivating aspects are eliminated because they monitor the progress of the student and actively refine the curriculum to his needs. As such, the learner spends less time training to acquire the desired skills, and the course is tailored to fit the user’s knowledge gaps without going through irrelevant lectures.

Fast Delivery of Lessons

Traditional classroom teaching methods are slow compared to eLearning platforms. The time required to learn using eLearning methods is reduced by up to 60%. Factors that lead to the reduced learning time include:

  • Lessons begin quickly and are included in one single learning session. It enables tutors to roll out training programs within a few days or weeks.
  • Learners define the pace at which they learn unlike in traditional classroom settings where they are forced to follow the speed of the whole group.
  • Students are allowed to choose the specific study and use relevant learning material focusing on areas of their choosing.
  • Learners also don’t have to attend training venues as they can learn at the comfort of their homes.

Improved Productivity

The reduced time in training and teaching students provides ample time for tutors to schedule online courses for students who need to improve performance in certain areas. They achieve this by analysing the data generated by eLearning courses to identify students who are struggling and adjusting the course material to help those learners focus on identified weaknesses.

A Large Pool of Learning Resources

Today, there are numerous online sources of information that students can use to get material for their assignments, projects and other uses. For example, there are online libraries where they can collect data and save it on their eLearning portals for use when revising for an examination. This way, the tutor can evaluate their reading techniques and recommend ways of improving learning or additional study material. Algorithmic eLearning makes this task easier by helping students tailor the sources to the learning objectives and techniques. Once the student downloads the material, he doesn’t need to look for the sources every time he needs to access it.

Saving Resources

ELearning courses that are customised to the user help school administrators save on additional payroll hours used in training tutors as the algorithm has already done the legwork. Also, the use of algorithmic courses means the learning and development department will not spend long hours analysing graphs and the students’ results. They will devote this time to creating valuable, up-to-date content for eLearning courses.

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