A Primer on Machine Learning and Deep Learning for Educators

Exploring how Artificial Intelligence and Machine Learning Enable Deep Learning, and Considering Implications for Education

The field of learning has evolved drastically over the years. With the advent of e-learning and learning management systems, the process of learning has gone beyond the traditional model of classroom training. Now it is possible for instructors and teachers to reach a wider, international audience through online courses hosted on cloud based LMS platforms. Students can access these courses from any place in the world at any time, by simply logging into their account using their login credentials.

Although e-learning is a complete and self-sustainable medium for imparting knowledge, it also works well in conjunction with traditional classroom training. Teachers all over the world have adopted digital tools to augment their classroom lectures with supplementary material, quizzes and online discussions.

While many digital technologies have played a role in advancing education, a set of emerging technologies is positioned to bring new advances thanks to the breakthroughs achieved in artificial intelligence (AI), machine learning (ML) and deep learning (DL).

Artificial Intelligence has already made its way into several everyday applications and will continue to change the landscape of technology as we know today. A variety of major fields and industries have developed applications based on AI and the learning industry is about to experience a major revolution as well.

If you are a teacher or an instructor keen in staying aware and informed about the latest breakthroughs and advances in the field of education, understanding AI, ML and DL is a must.

Although this article aims at explaining deep learning, it is important for you to know about artificial intelligence and machine learning beforehand so that you have a clear mindset when it comes to understanding deep learning. The article also discusses the positive changes that these technologies can bring to the field of learning and education.

Artificial Intelligence, Machine Learning and Deep Learning

People often use the terms AI, ML and DL interchangeably. However, these are very different (but closely related) things.

Artificial Intelligence

Artificial Intelligence refers to the capability of machines to solve problems, think, and make decisions on their own without being provided with a hard-coded algorithm. Intelligent machines solve problems similar to how humans do, and in some cases their results are even better than humans.

It is called ‘artificial’ as opposed to the ‘natural’ intelligence that humans and other living beings possess.

Facebook, Twitter and Google take the services of their respective AI to identify and sort pictures of your friends in your photos, filter spam and classify emails based on importance. Virtual assistants like Alexa, Google Assistant and Cortana are popular AI applications too that are rapidly growing.

Machine Learning

Machine learning refers to the collective field of all the algorithms and processes that are deployed to develop artificial intelligence in machines. These algorithms enable the machine or program to ‘learn’ from a set of data and use this learning to solve other tasks and problems.

Machine learning trains a machine to learn from a wide set of input data and come up with an indigenous algorithm of its own to identify patterns and trends.

Deep Learning

Deep learning is one of the approaches of machine learning. It is achieved by approximately mimicking the anatomy and functioning of biological brains by creating a similar neurological network. The ‘deep’ in deep learning comes from the plethora of such neurological layers that make up a deep learning system.

Current deep learning algorithms are quite far from biological brains, but it is a huge step in that direction.

Deep learning networks are characterized by several layers, nodal joints and interconnections that act as paths with directions in which data can travel. These are powered by modern GPUs that enable deep learning systems to learn from massive amount of data and make sense of it without any explicit algorithm. As the capabilities of GPUs increase, deep learning networks become smarter.

Google’s Andrew NG created a deep learning based car-finding algorithm in 2012 that became popular among the masses. It was Google again that created an AI AlphaGo player which trained itself in the massive number of strategies and moves of the challenging strategy game “Go” (much harder than chess). AlphaGo became such an expert that it was able to defeat a human Go champion from South Korea.

The relationship between these three fields can be summarized with this simple Venn diagram:

How Can Deep Learning Systems Impact Teaching and Learning?

Now that we have a fair understanding of deep learning, machine learning and artificial intelligence, let’s have a look at the impact it can have on learning management systems and education in general.

As discussed above, deep learning enables software applications to develop intelligence so that they are able to adapt and improve on its own as per the situation. This opens a wide range of possibilities in the e-learning landscape, especially in customization of course content for each student.

Automatically Optimize Course Content

Every teacher knows that developing course material is not a one-time activity. Instead, materials need to be improved and optimized based on the latest information as well as students’ feedback.

Learning management systems have made it easier to collect the feedback from students in the form of quiz results, course ratings and other such course metrics. Cloud based LMS's provide this quantitative data in the form of reports and data that the teacher can refer to for analyzing and improving the course content and delivery. You can also collect qualitative feedback in the form of surveys and discussions through the LMS and use it as well.

However, the instructor has to manually process the data and use statistical and qualitative models to identify patterns and improve the course material. It is a time-intensive activity and hence, challenging to carry out frequently.

Deep learning algorithms specialize in identifying patterns and trends from large sets of data. Integrating deep learning with learning management system can result in an intelligent course material that frequently updates itself based on student feedback, without any manual intervention required, and with a very high accuracy.

Create Unique Customized Course Content for Every Student

Different students have different thinking abilities and learning requirements. This is because our minds are shaped by several factors including educational and family background.

Hence, the same course content may not be suitable for all the students that are part of the course. No wonder some students perform great in a class, while others can’t catch up. There is a need for adapting the content, language, and pace of a course as per the student’s aptitude.

Such a high-degree of customization can be made possible with the help of deep learning LMS. An intelligent LMS would be able to understand the profile of every student based on their past performance data and then mould the course according to them.

Discover The Need For New Courses and/or Modules

Deep learning systems intelligently make sense of humongous data sets and identifies patterns and trends within it. Utilizing this ability, such an LMS would be able to analyze the complete statistics and data sets of the students in order to discover the gaps within the learning that need to filled.

It can even suggest the ways in which such gaps can be fulfilled, hence leading to the development of new course modules or entire courses.

Reach Wider Range of Students With Improved Marketing Message

Learning management systems have already enabled course instructors to reach a global audience that can learn any topic by simply logging into the LMS platform and access the course content.

But there is a need for both students and instructors to identify the most suited course and learner respectively. Deep learning powered Intelligent LMS's can help with the same.

By creating a detailed profile of the typical students that might reap the maximum benefits out of a particular course, such a detailed persona can then be utilized to refine the marketing message so that the right students can be targeted.

Of course, this is a new science, so it is important to proceed cautiously and learn as we go. While some courses may not be best suited for some students, they will still be necessary based on the requirements of a larger degree program. Considerations such as these need to be incorporated.

Enable 24X7 Doubt Solving For Students

Teachers are often over-burdened with creating, delivering, and improving course material as well as evaluating student performances. Not to forget the managerial tasks that every teacher must undertake. Entreprenurial online trainers may also need to look after the business aspects of their courses.

This means that they are often left with a tiny amount of time left in which they can interact with their students and clarify their questions and doubts regarding the course.

But establishing a two-way communication with the students is one of the most critical things that a teacher needs to do for increasing the effectiveness of their courses.

Cloud-based deep learning LMS connected to a learning knowledge base can act as a 24X7 doubt solving assistant for the teachers. It can be a highly-valuable virtual assistant for all teachers and would enable the students to resolve their doubts timely and accurately.

Highly Interactive and Immersive Learning Experience

At this point of time, the zenith of deep-learning LMS seems to be AI-powered robot assistants that are present with students in their homes. There are already virtual assistants in the market, like Zenbo, Cloi and Temi, which assist home-owners in their routine home-management activities.

It is not that distant into the future when educational robot assistants would be present in students’ homes to help them in their learning endeavors.

Conclusion

Deep learning is not a mere fad that would wane with time. Instead, it is a revolutionary technology that has the power to modify the canvas of human civilization. Learning and education can massively benefit from this ground-breaking technology which can drastically modify the way we learn new things.