A new trend in apps to watch: e-learning


The pandemic has spurred new trends in many areas, and for those interested in building apps, an unmissable trend is online learning. Social distancing measures and school closures have forced “Zoom University” to become a norm, and although all students and faculty are eager to return to in-person learning, the trend towards online learning has grown. proven its effectiveness. Beyond the areas of a university program or other type of institutionalized learning, many people are motivated to take their learning into their own hands, whether they are studying a foreign language for the next vacation or hope to broaden their skills before entering the workforce. The scope of e-learning apps expands to include apps for math, languages, etc.

The technologies behind e-learning applications have developed to create teacher-student dynamics due to machine learning (ML), and this new frontier is just beginning. As an iOS developer with an ML background, I opened up my ML models in hopes that it would make it easier for other developers to take their apps to the next level with the benefits of ML in 10 minutes instead of weeks or of months. Large companies like Google have also made their sophisticated and well-trained ML models accessible to their developer community. Along with these exciting developments, here are a few more reasons why your attention should be on e-learning apps.

1. It offers students the opportunity to learn at their own pace.

Each student learns at their own pace, which can make a classroom environment where a group of students learn more frustrating. If a learning pace is too fast, students can fall behind and start to feel discouraged very quickly. On the other hand, if the learning pace is too slow, students can quickly become bored and disconnect from the program. Online learning apps that allow students to self-direct can help them take full autonomy for their education and retain more information. It also helps them get more out of their learning experience by focusing on the material they want to progress on.

This is one of the main reasons why some people turn to e-learning apps alongside in-person lessons, if they take them. I learned by creating my Japanese language learning app Nukon. A large number of Nukon users were actually students taking Japanese lessons in person. However, they used Nukon alongside a written program to supplement their learning to write and speak in Japanese.

One of the most popular features of Nukon voted by users was the real-time feedback which made their learning spontaneous. Whether they were commuting or having short breaks, they could easily practice Japanese on the fly with the app letting them know how precise their writing or pronunciation was. Under this popular feature, there are on-device ML models trained on large data sets with 98% accuracy to feed it. As you can see, apps with artificial intelligence can be powerful and easy to make sure a student understands concepts through personalized feedback. This allows students to study for a deeper level of understanding gained through hands-on learning. Thus, when they are in the classroom environment, they feel confident to participate and contribute.

2. Personalized learning can be achieved via a chatbot integrated into the application.

However, a downside to self-directed learning can be the lack of mentoring when a student is using the app alone. The ability to immediately ask an instructor and get help or a detailed explanation of a difficult problem is usually a vote for in-person learning and can greatly improve a student’s level of understanding and sense of self. support. To fill this gap in e-learning, applications have responded to this need thanks to machine learning algorithms that have given birth to chatbots created and implemented in many e-learning platforms. These chatbots are not only able to answer student questions with 24/7 real-time personal dialogues, but they are also able to observe, follow, and then adapt to the unique learning pace. of each student by suggesting new content or skills acquired to refresh.

These cutting-edge chatbot developments illuminate a bright future driven by artificial intelligence. The more applications integrate these ML algorithms, the more support students will feel in their e-learning efforts. Additionally, ML-powered applications unleash the potential to reach users of different needs and markets due to their adaptability.

3. Virtual classrooms have become the trend.

From a consumer perspective, there are a number of reasons why students prefer a virtual classroom. In addition to the possibility of being autonomous, online learning offers great flexibility, supporting students who wish to learn at a distance or at their own pace. This flexibility also allows non-traditional students – such as adults with full-time jobs or entrepreneurs – to add learning elements into their daily lives by taking a few quick lessons daily.

For these reasons, applications that make online learning easy and accessible will continue to be on the rise. As more and more language and math applications become available, consumers are likely to start looking for e-learning applications for a wide range of program types, creating a huge opportunity for developers of online learning. ‘apps and entrepreneurs looking for their next big idea. I hope the machine learning algorithms developed by other founders and engineers with machine learning expertise like myself will continue to be iterated, forging a powerful future of online learning capabilities for students of all ages and from all walks of life.

Author’s BIO:

Melody Yang is an iOS entrepreneur and engineer with a background in machine learning and mobile application development. IOS developer at Apple, his side projects include 5 applications published on the App Store.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.


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