Artificial intelligence and automation have invaded every aspect of human life today. Companies now rely on AI-powered solutions to optimize operations and increase productivity.
And the situation is no different in academia. Automated solutions dictate the future of academic services, especially in e-learning ecosystems. This change in ideology (and technology) is apparent in student behavior and learning culture.
At the moment, students can reach out to bots with the write an essay requests and obtain instant results. Teachers can also monitor class performance to detect underperforming students.
This article analyzes the impacts of automation on online learning. Read on to discover the areas of application in academia.
8 Ways Automation Is Used in e-Learning
The power of automation lies in its versatility across the board. Modern tools even offer a more comprehensive array of possibilities for customization. So, let’s take a look at the areas of implementation of automation in e-learning.
Contemporary e-learning platforms provide advanced content editing options for students and professors alike. You can complete a project and use EssayEditor services to fine-tune it.
How does it work?
The AI identifies common writing errors and suggests edits. With the information, you can adjust the paper to deliver your thoughts with clarity.
Teachers can assess student performance with automated services. These AI-powered solutions can evaluate tests instantly without human supervision. Other advanced e-learning management systems can generate tests based on the available academic material.
Machine learning systems can arrange and moderate online classrooms. For instance, an automated service can monitor students’ dashboard activity to fine-tune reading recommendations. In essence, built-in modules can curate the academic workflow even in the teacher’s absence.
Better Success Tracking
Tools like Learndash can assign, grade, and generate pre-programmed rewards for completed tasks. E-learning solutions like this can eliminate the monotonous nature of teaching.
Besides, these digital learning platforms have built-in data management systems. With machine learning and AI, teachers can collect the students’ progress reports on a centralized dashboard. This information will help to monitor real-time academic performance and highlight students’ strong and weak points.
Flexible and Fast-Paced Learning
Automation eliminates the rigors and repetitiveness of manual tasks. For instance, teachers can obtain data on any student instantly. Students can also access their courses 24/7 from any location. As a result, they can cover their curriculum in time for exams and tests.
Online learning with AI-powered tools helps educators and scholars to safeguard data and sensitive information. Automated platforms are protected by advanced encryption protocols and other security features, making them almost impregnable by third parties.
Besides, you no longer need to take hand-written notes and worry about losing them. With advanced digital learning platforms, students can store information and files for easy access. And most importantly, online learning tools provide access to comprehensive academic databases.
Nowadays, every academic platform has a messaging feature for communication between students and teachers. These services also allow instant feedback on projects. Without this feature, all interactions would have to go through email chains.
Besides, AI learning promotes a community-based ecosystem, which fosters debates, discussions, and collaborations among peers. As a result, students can assist one another, even without a teacher’s supervision.
Great for Motivation
Automated learning modules encourage students to work harder. And how is that? The flexible nature of the ecosystem allows them to choose courses targeted toward acquiring specific skills. And since students get instant feedback from their teachers and peers alike, this motivates them to participate in the learning process.
Most importantly, AI-generated suggestions increase students’ enthusiasm to learn. Since these academic resources are customized by personal preference, they can retain more information from lectures.
Disadvantages of Automation in Online Learning
Despite the extensive integration of automation in online learning, some of its downsides remain unaddressed.
Let’s discuss some glaring examples.
Automation Rewards Laziness
The better the machine learning algorithm, the lesser the amount of work needed to complete a task. Let’s assume that a student wants to research a topic; they can use AI-generated solutions to filter suggestions. Although this feature is a net positive, it removes the fact-finding aspect of research, limiting the student’s ability to solve problems from scratch.
Automation Prioritizes Data Over Human Connection
All artificial intelligence and machine learning solutions are data-driven. The algorithm collects numbers and generates performance reports on specific students or the entire classroom.
Consequently, teachers only focus on numbers while ignoring the human interaction with students.
Most importantly, the importance of face-to-face interactions cannot be ignored. Students now feel detached from their peers and educators due to a lack of physical interactions. As a result, they don’t get the necessary guidance to perform at a high level.
E-Learning Automation Is Not Always the Best Solution
Courses that require only visual and aural cues thrive in the automated digital space. However, subjects like chemistry that require all sense organs need on-site solutions. At the moment, AI systems are still unable to relay smells and other sensory impulses. Although this may change in the future, it is still a current hindrance to all-round digital learning.
Automation is a blossoming trend in e-learning, so institutions are adopting online academic solutions to improve student performance. Nowadays, AI systems can curate and edit texts. They can also process stored data for faster communication. Besides, automated programs keep students motivated by establishing a conducive e-learning environment.
Nevertheless, existing systems still need improvement to address the human factor deficit. Ultimately, teachers need to develop creative ways to maintain a stable work rate among the student body.
Automation is the future of e-learning. Let’s embrace it and usher in a renaissance in academia.