How Artificial Intelligence is Changing the eLearning Environment

Artificial intelligence (AI) is everywhere these days, making inanimate objects increasingly smart. It’s designed by humans for humans, to enrich and facilitate our everyday lives. As a matter of fact, AI is now the brain behind your smartphone, car, music streaming service, banking app, freezer, and travel agency. It’s not only omnipresent, it’s omniscient as well.

If the main keyword for AI is “smart”, then how come we don’t talk more about this burgeoning technology in the context of knowledge, learning, and education? AI has everything we need to revolutionize the industry, enrich and facilitate the learning experience of students and adult learners, and boost the knowledge retention rates across the board.

It’s a whole new chapter in the history of the classroom. The change has already begun, with AI reshaping eLearning as we know it. Find out how.

AI Makes Personalized Learning a Child’s Play

Every student is different. Educators have known this for a long time, but it wasn’t until LMS software solutions that they were able to actually accommodate the various needs of different types of learners.

The introduction of technology to the traditional classroom established a framework for blended learning, which is now the dominant model for educating modern-day students. Essentially, blended learning allows students to choose how they access educational content, and how they acquire knowledge in terms of learning styles and speed. But AI brings personalization to a whole new level.

Unlike teachers, artificial intelligence can recognize students’ learning needs, interests, preferences, habits, and capacities automatically and in real-time, by analyzing their performance. This powerful insight helps create highly personalized learning environments and paths where every aspect – from content type to delivery method – is adjusted to the students’ individual needs.

The result? Optimum performance of every learner.

AI is at Learners’ Disposal Anytime, Anywhere

In combination with personalized learning paths, unlimited connectivity makes it possible for students to access educational content from anywhere and at any given moment.

Adaptive learning environments enable and encourage self-paced learning, thus allowing students to make the best out of their peak productivity hours. But what happens if one learner’s productivity peaks in the middle of the night, when there’s no one around to help solve a dilemma or address points of confusion?

Since blended learning is a combination of instructor-led training and online courses, tutors should remain available 24/7, whenever students may need their guidance. This may not be possible with human tutors, but it is with digital assistants.

Thanks to machine learning and natural language processing, AI assistants can learn to provide necessary guidance to students, answer their questions, and solve their problems. And since machines never sleep, this digital mentorship is available 24/7.

Digital Mentorship Can Encourage Engagement

Usually, AI assistants work with students individually. Extending the concept of student-centered education, smart technology caters not only to different learning styles but also to different personalities and temperaments. This is significant to introverted students, who usually don’t feel comfortable expressing themselves in front of their peers in the traditional classroom environment.

Faceless AI is a saving grace for such learners as it allows them to voice their dilemmas without the fear of being judged, while the eLearning environment itself encourages them to participate in social learning. Of course, AI has the potential to motivate and engage all students, be they introverts or extroverts, visual learners or auditory learners.

Higher engagement is a natural consequence of personalization – by facilitating the learning path, AI makes knowledge acquisition easier, thus eliminating all frustration from the process. All students thrive in such a learning and development (L&D) environment when they are motivated by their own achievements.

AI Allows Continual Real-Time Improvement

Thanks to cutting-edge software technology and authoring tools, everyone can learn to create an online course that encourages engagement and equips students for success.

It’s maintaining this eLearning environment that’s hard, especially in today’s fast-paced world. Technology is a powerful knowledge acquisition tool – the more potent it becomes, the more we understand about the world we live in. The human race is learning on a daily basis.

The road from tacit to explicit knowledge was a long one in the pre-digital age. At times, students had to wait years before new findings were added to their old textbooks. Today, we have the Internet – the biggest and fastest knowledge base in history.

With AI, we can now comb through this knowledge base in matters of minutes, update our online courses with cutting-edge information in real time, and keep educational content relevant. Having said that, up-to-date content is not enough to ensure a rich learning experience. Educators and online course creators must learn from their students as there are always challenges that need to be addressed. Because of this, student feedback is precious.

Real-Life Examples of AI in Learning

Let’s now see a few companies who are working behind the scenes to bring the benefits of AI-powered technologies to people.

Nuance

Massachusetts-based software technology company, Nuance builds speech recognition software. The technology can transcribe a maximum of 160 words per minute. It is useful especially to learners with mobility challenges, including writing. Instructors too can rely on it to dictate classroom lectures and expedite repetitive tasks such as emails.

Carnegie Learning

As a provider of quality math education, Carnegie Learning brings together artificial intelligence and machine learning to its platform. It puts emphasis on personalized learning experiences to turn learners into critical thinkers, creative problem solvers, and lifelong learners. By combining cognitive and learning science with research and practical instructions, CL helps students gain a deeper understanding of what they are learning.

Century

Century is a provider of an AI-based teaching and learning platform located in London. It provides adaptive learning solutions for learners according to their strengths and weaknesses, while helping instructors simplify their routine tasks such as grading. For this, it combines AI, neuroscience, and data analytics.

Artificial intelligence is already making waves in the eLearning industry by unlocking exciting new opportunities for educators and students alike. But deep personalization, 24/7 availability, increased engagement, and real-time improvement are only a fragment of what AI may mean for the future of education. Experts predict that the use of this smart technology will grow by 47.5% in the next two years. We can only imagine the possibilities.

Published at Tue, 20 Oct 2020 12:00:00 +0000

How Retailers Use Artificial Intelligence to Know What You Want to Buy Before You Do

MIAMI, FLORIDA - AUGUST 19: A sign is seen outside of a Target store on... — MIAMI, FLORIDA – AUGUST 19: A sign is seen outside of a Target store on August 19, 2020 in Miami, Florida.

Joe Raedle/Getty Images

The Terminator, a symbol of artificial intelligence run amok, famously declared that he would be back. Three and a half decades later, it turns out repeat business is at the heart of AI.

AI and machine learning have long been a part of retail—nearly a decade ago,

Target

(TGT) could infamously predict when a woman was pregnant. In the years since, consumers have grown more comfortable sharing their data, especially as they crave more personalization. Now, with Covid-19 propelling shopping online—replete with tracking cookies and apps—we’ve reached a key moment. There’s more information, and more computing power than ever before to parse it for patterns that keep customers loyal.

“An AI system needs data in order to become smart. And the more data it has, the smarter it gets,” says Gaylene Meyer, Vice President Global Marketing & Communications at RFID company

Impinj

(PI), whose products allow retailers to track trillions of items of inventory in real time and respond quickly to changes in demand. “When you can see everything moving through a system, you gain a new view of the system as a whole. So you can find the pain points and eliminate them.”

That’s crucial, as inconvenience is the enemy of sales; the easier the transaction, the more likely people are to complete it. The pandemic played havoc with supply chains throughout the industry, causing products to be out of stock or delayed in delivery. That, coupled with consumers’ reluctance to buy nondiscretionary items, actually drove data down earlier this year.

Yet the strongest retailers, who have seen revenues climb in 2020 and have the money to invest in technology, may be able to sidestep this problem—especially as they use data not directly tied to sales.

“Mobile is the new mall,” says Cowen & Co. analyst Oliver Chen, who notes that machine learning allows brands to build one-on-one relationships with consumers at scale. “It’s how you interact with a retailer online; that’s the secret sauce behind a lot of social media data. It comes back to [retailers] knowing what you want before you know you want it, to keeping you interested, buying, and satisfied.”

That’s part of the rationale behind

Walmart’s

(WMT) bid for TikTok: The app provides valuable information about how shoppers are engaging with brands via social media, while also reaching a younger demographic. And just like Target years ago, “Walmart knows that the most valuable customer is in the early stages of household formation,” says Chen. From drapes to diapers, they’re on the cusp of prime spending years, making their loyalty still more prized.

Walmart and Target shares have been on a tear in 2020—Target stock has gained 28%, while Walmart has risen 20.3%—but Barron’s has argued before that both can keep winning, as they gobble up market share amid consumers’ tendency to do all their shopping in one place.

At roughly 26 and 21 times forward earnings, respectively, Walmart and Target’s valuations are above five-year averages of 19 and 15 times, but have forward price-to-earnings growth ratios below historical levels, at 3.1 and 2.1 times, compared with 4.1 and 3.4. That suggests the stocks’ now-brighter outlooks leave them more room to run. Returns on equity of 25% and 29% put Walmart and Target ahead of many peers, with that metric expanding for both in recent years.

It’s not just the giants benefiting from these tools. At a time when in-person makeovers aren’t appealing, beauty brands are using them to attract and retain consumers for items that have traditionally been difficult to sell online.

Estee Lauder’s

(EL) Virtual Try-On (VTO) gives consumers the ability to see how makeup and hair care products “look on them in real time, virtually,” says Marki Zabar, Director of Global Communications at the firm. “We leverage AI and machine learning to provide personalized skin care and foundation recommendations.” She says that VTO users’ average time spent on site is 2.6 times higher compared with total site visits, and the tool has a 67% rate of converting users to buyers.

Barron’s recommend Estee Lauder in August, with the shares outperforming the market since. While the stock’s valuation, at 43 times forward earnings, doesn’t look cheap, analysts expect earnings per share to grow nearly 17% in the fiscal year ending in June, to $4.84, and jump to a record $6.09 the year after.

Far beyond makeup, personalization has been a buzzword across retail in recent years, as tailored suggestions and offers help increase loyalty. AI enhances this effort in everything from redirecting ad dollars to more receptive audiences to providing better product recommendations and even bespoke promotions.

“This is not just innovation for innovation’s sake, it really does drive a better consumer experience and generate sales,” says Stephane Wyper, senior vice president of Retail Innovation at

Mastercard

(MA), which provides AI Powered Drive Through solutions at restaurants like Sonic and

Dunkin’ Brands Group

(DNKN).

Machine learning allows menus to change based on diners’ past preferences, or, for new customers, hone them for weather or historical purchasing patterns. “We’re leveraging AI as a way to drive a more personalized experience [with] frictionless retail solutions,” says Wyper.

McDonald’s

(MCD), the Walmart of fast food, is another behemoth that’s been investing in technology for several years, while also seeing growing sales after an initial Covid crash. At 29 times forward earnings, it is a bit pricier than average, but trades more cheaply than peers like

Wendy’s

(WEN),

Starbucks

(SBUX), and

Domino’s Pizza

(DPZ). Analysts expect record 2021 EPS of $8.31, easily eclipsing 2019 levels, and McDonald’s just increased its dividend, and yields 2.2%.

Looking ahead, holiday sales are still expected to grow between 1% and 1.5% this year, but e-commerce sales could increase as much as 35%, as shoppers look to minimize exposure risks.

That could be an opportunity for consumer companies of all stripes to capture more data at a time when shopping habits are rapidly shifting. It’s also a chance for the biggest players to use this technology to drive sales, either via a well-timed ad or a spot on product suggestion.

“Despite a weak labor market, consumers afford themselves small luxuries in every crisis,” notes Aaron Terrazas, director of research at truck brokerage and technology start-up Convoy, which uses machine learning to cheaply and efficiently match trucks with cargo. “With fewer Americans able to travel to see family this holiday season, I expect they will seek psychological solace in retail therapy.”

Shopping may provide comfort, but our psychology remains a hotly contested commodity.

Write to Teresa Rivas at teresa.rivas@barrons.com