Artificial intelligence (AI) is a subfield of computer science that focuses on developing intelligent computers capable of doing activities that would normally need human intelligence. These machines are programmed to analyze data, learn from it, and make decisions based on their analysis.

The role of AI in education is to augment traditional teaching methods by incorporating technology, data analysis, and machine learning algorithms into the learning process. This integration can potentially transform education for students, teachers, and administrators alike.

And don’t get this wrong! Students aren’t cheating on their homework when using AI-powered tools; they are just taking control of their learning experience. There are already numerous detection tools that can detect plagiarism, one of the best AI content detector tools available is GPTZero which checks grammar, sentence structure, and originality.

The Pros of AI in Education

Personalized Learning

AI can adapt to the learning style and pace of individual students. Educational platforms powered by AI can adjust the difficulty level, suggest resources, or modify the content based on the student’s performance. This personalized approach ensures that students are not left behind and that they grasp the concepts effectively.

Real-time Feedback

The real-time feedback provided by AI aids in immediate correction and learning. Instead of waiting for a teacher to grade their work, students can get instant feedback on their understanding of a subject. It allows them to identify and work on their weak areas promptly.

Immersive Learning Experiences

AI can create immersive and interactive learning experiences that go beyond the conventional classroom setting. With the integration of Augmented Reality (AR) and Virtual Reality (VR), AI can create real-life scenarios for students to interact with. It not only enhances their understanding but also makes learning a more engaging and fun experience.

The Cons of AI in Education

Data Privacy Concerns

One of the primary concerns surrounding the use of AI in education is related to data privacy. AI systems require a vast amount of data to operate effectively. It could potentially put sensitive information about students at risk if it falls into the wrong hands. Strict regulations need to be in place to ensure student data is protected.

Dependence on Technology

While technology can enhance learning, over-reliance on it can lead to issues. Should the systems fail or if there are technical glitches, the learning process could be halted. Moreover, constant interaction with AI might lead students to lack the social skills that are developed through human interaction in a traditional classroom setting.

Lack of Human Touch

While AI can mimic human responses, it cannot understand and react to the emotional needs of students. Teachers play a crucial role in motivating and inspiring students, offering a human touch that cannot be replicated by AI. Emotional intelligence is as important as academic intelligence in a holistic education. Balancing the use of AI with the irreplaceable human touch of teachers is paramount for effective learning.

The Future of AI in Education

The use of AI in education is still in its early stages, but it has already shown significant potential to transform the learning experience. With advancements in technology and AI, we can expect to see even more innovative ways of incorporating it into education.

In the future, AI could potentially take over mundane tasks such as grading and administrative work, freeing up time for teachers to focus on personalized instruction and connecting with students. It could also enable the creation of adaptive learning platforms that cater to each student’s needs.

However, as we continue to explore the benefits of AI in education, it’s crucial to address any ethical concerns and ensure responsible use. With proper regulations and a balanced approach, AI has the potential to enhance education for generations to come. So, it’s up to us to navigate the integration of AI in education carefully and harness its benefits while mitigating any potential drawbacks.

If you found this article interesting, take a look at Higher Education: Using AI to Meet Student Needs. 

Featured image credit: Poca Wander Stock, iStock. 

The post AI in Education: the Pros and Cons appeared first on eLearningInside News.

This article was written by Shantanu Bose, Ph.D., Chief Academic Officer and Provost at DeVry University. 

Higher education is on the cusp of an AI revolution. Artificial intelligence has the potential to fundamentally transform higher education for the better, including how we teach, what we learn, and the skills needed to be successful in a world shaped by AI.

By infusing AI into learning platforms and courses, colleges and universities can make the educational experience more adaptive, personalized, engaging, and impactful for students.

Universities are not moving fast enough.

Yet, many colleges and universities are moving cautiously and slowly towards the promises of AI. A report released this year by Ellucian, a leading higher education technology solutions provider, reveals that despite the recognized benefits of artificial intelligence, its use in higher education is not as widespread as perceived.

The comprehensive survey gathered responses from 1,140 higher education administrators across 768 institutions. Its findings bring to light the unrealized potential of AI in higher education. Despite the gap between the perceived and actual use of AI, over 70% of respondents view AI favorably and about half of them expect the positive effects of AI will span the student experience, from better supporting the student journey to improving student outcomes at their institution.

How is AI changing the employment landscape?

Both students and employers are grappling with their own uncertainties and realizations about AI’s capabilities and its impact on jobs. College graduates are worried about their work readiness and potential to secure jobs due to the rapid emergence of generative AI, while employers acknowledge how the hiring landscape is being changed quickly by the new technology, according to Cengage Group’s 2023 Employability Report. Educators and employers need to do more to prepare today’s workers, the report added.

Higher education has a profound duty to keep up with technological advancements that impact the learning needs and employability of students. DeVry is an institution that has a legacy of combining education and technological innovation, along with a mission to close the opportunity gap in tech-focused careers. Thus, DeVry launched its AI Lab focused on ensuring our programs and curriculum are preparing learners for a world shaped by AI.

AI as a supplement to learning.

As AI continues its rapid advancement, students expect their learning experiences to keep up. Personalized and customized content is the new norm. AI-powered software can empower learning experiences due to its ability to analyze huge amounts of data to gain insights into how students learn best and what teaching methods are most effective.

AI-powered platforms offer adaptive learning, tailored lesson plans and coursework to individual students based on their strengths, weaknesses, and preferred learning styles, while also tracking their progress, engagement, and performance.

Similarly, AI-powered virtual assistants can provide instant answers to many frequently asked questions thus leaving more time for students and faculty to focus on higher value-added interactions and learning. Through its AI Lab, DeVry is experimenting with emerging AI technologies such as Retrieval-Augmented Generative (RAG) conversational AI solutions to enable a personalized learning experience.

The future of AI-assisted education

AI-powered learning systems are beneficial to not only students but also the outcomes that higher education wants to achieve. This is because, as Domoscio notes, “Learners feel valued and motivated when they are placed at the center of their own learning journey.”

As AI continues to evolve, colleges and universities that implement artificial intelligence thoughtfully and responsibly will be poised to deliver learning experiences that are truly tailored to students’ needs. The future of higher education will rely on a harmonious partnership between human insight and AI.

If you liked this article, check out How Technology Can Facilitate Early-Stage Education. 

Featured image: Tzido. 

The post Higher Education: Using AI to Meet Student Needs appeared first on eLearningInside News.

BENGALURU, INDIA – The world’s largest education technology unicorn, BJYU’s, has launched its new innovation hub, BJYU’s Lab. The company, known best for its online learning platform BJYU’s Future School, launched the product on November 9th, in its continued effort for global market expansion. This innovation hub, based out of the UK, the US, and India, makes use of EdTech’s newest and most sought-after technologies, from augmented reality and artificial intelligence (AI), to computer vision capabilities and gamification.

Dev Roy, Chief Innovation and Learning Officer of BYJU’S said, “The role of online learning is not just to replicate offline classes in digital space but to make it more interactive, engaging, and personalized.

Roy continues: “By combining the ability of computing, technology, and data, we at BYJU’S Lab, want to explore the power of information and technology to create more personalized, enhanced, and democratized learning. As a global company, we are looking to harness a global talent pool to build innovative tools and leverage new technologies to positively impact the learning experiences of children across the world. As we continue to grow and experiment, we will operate at the intersection of business and technology to make innovation real and relevant for our end customers. We are looking at strengthening our team and look forward to working with bright and curious minds to transform the way children learn,” he added.

BJYU has amassed over 100 million online students, 6.5 million of which are paid subscribers, across its learning products.

It’s most popular of which, BJYU’s Future School and BJUY’s Exam Prep have found users from Indonesia to Mexico. BJYU’s products cover a range of educational topics and modes of learning, from classes in coding and maths to vocational exam preparation in banking and law. With an already strong education base, the launch of BJYU’s LAB will see the company incorporate the use of new technology into its learning products.

BJYU’s is currently valued at $18 billion, recently securing $1.2 billion via a term loan from the overseas market, raising much more than its projected $700 million. The company’s buying portfolio has attributed to much of its growing success. BJYU’s acquired AR-focused EdTech company Osmo for $120 million in 2019, as well as the online reading platform Epic for $500 million. From partnering with European and US investors, and securing the $1.2 billion in funding, BJYU’s is looking to expand through further acquisitions. The innovation lab is an effort to cement its reach in the overseas EdTech market.

BJYU’s is also shifting its focus to tech engineers and industry professionals. For BJYU’s Lab, the company is looking to hire machine learning and AI experts from the UK, US, and India. This ensemble of new professionals will work, according to BJYU’s, “to make technology transparent for the user and harness it in a way that tech-enabled education can reach the largest number of people.”

Featured Image: Julia M Cameron, Pexels. 

The post BJYU’s, The World’s Largest EdTech Unicorn, Launches New Innovation Hub, ‘BJYU’s Lab’ appeared first on eLearningInside News.

In the wake of numerous high profile school shootings this year, the tech industry has responded with new software that seeks to identify potential incidents, connect troubled students with aid, and mitigate risk. This week, the Austin-based company OneSeventeen Media released a new product–the ThinkingApp–which targets elementary students in PreK-2nd grade.

In response to the May shooting at Santa Fe High School in a district south of Houston, the Texas legislature passed a new law intended to prevent incidents in the future. One of the measures of the legislation prohibits behavioral expulsion in grades PreK-2.

Reaching Troubled Students Early with the ThinkingApp

Commissioned by the Austin Independent School District, OneSeventeen Media created the ThinkingApp. The software consists of interactive ebook-style stories. Unbeknownst to distressed young learners, however, it also actively assesses their mental state and seeks to de-escalate their behavior using an AI framework. Educators and parents, meanwhile, receive real-time reports from the app based on how the learner responds.

These techniques are based on “trauma-informed, restorative and social-emotional learning (SEL) principles to provide real-time “emotional digital triage”™ for upset students before they escalate damaging behaviors, engendering a safer learning environment for all students,” according to a release.

These findings come from third-party research which found that the techniques provided a “statistically significant reduction in students’ emotional distress.” One school in which the intervention was tested reported a 77% reduction alternative school transfers.

Using AI to Identify Potential Risks with iNotify

Meanwhile, a computer science major at UT Dallas was inspired to create an AI-powered warning system following the knife attack at UT Austin last year. Ashlesha Nesarikar’s algorithm scans security camera footage to identify weapons and potential threats.

“We can add this extra level of context to, in real time, recognize whether someone is wielding a weapon and posing a threat to people in the community,” Nesarikar told a local NBC affiliate.

“The call to 911 didn’t happen until about five minutes after the start of the [UT Austin] attack, so you had five minutes where people were being hurt and no one could help essentially,” said Nesarikar.

Nesarikar’s technology, iNotify, can be programmed to alert both police and school security when it detects a potential threat.

“It, in real time, recognizes these weapons and then can actually determine the meaning of what’s going on rather than just saying, you know, this is what I think it is and then send out, based on that, still in real time, a notification to law enforcement, emergency responders and anyone who may be in harm’s way as a result of the weapon being detected,” Nesarikar said.

The product is still in development, but it’s scheduled to be ready by the end of the year.

Addressing School Shootings Where Gun Control Is Out of the Question

At least in Texas, the state has by and large rejected gun control as a method of reducing the risk of mass school shootings. Over 1.2 million Texans are licensed to carry guns in public. If that doesn’t make gun control a non-starter itself, the state has been firmly controlled by the Republican Party for over 20 years.

As CBS reports, gun control isn’t popular even among Santa Fe High School students. In contrast, there was wide support and action for the measure among students of Marjory Stoneman Douglas High School in Parkland, Florida, the site of the deadliest mass shooting in recent years.

It remains to be seen how effective these AI-based tech interventions will be in future incidents, but they do have the benefit of being non-partisan efforts for the most part. If shown to work, they may present the most realistic course of action in the current political climate.

Cover Image: Ryan Wallace, Unsplash.

The post Texans Look to AI and EdTech to Mitigate School Shooting Risk appeared first on eLearningInside News.

On Wednesday, SelfStudy announced they have received seed round funding to the tune of $3 million led by the International Anesthesiology Research Society (IARS). The AI-powered cloud platform has an ambitious goal. With its algorithm, it hopes to personalize learning in professional fields by partnering with industry leaders and content providers. Its product is officially available for commercial licensing.

The algorithm used by SelfStudy was initially a project of leaders at MIT and the IARS. In numerous—if not all—medical fields, research and new sets of best practices tend to develop at a lively pace. It isn’t easy for practicing professionals to both keep abreast of these developments while doing their job.

Delivering Personalized Training with an Artificially Intelligent Platform

Using machine learning and item response theory, SelfStudy constantly reevaluates a given field, assesses the importance of professional development content, tracks learners’ progress, and matches them with the most relevant material.

“We built SelfStudy360 to transform the way organizations deliver their content and formal learning programs,” said SelfStudy CEO Brenda McLaughlin. “Our mission is to accelerate the mastery of new knowledge through personalized learning. To achieve that goal we use proven education methodologies and the most advanced technology available so professionals can always have the knowledge they need to be the best at what they do.”

The company recently premiered their product at the IARS Annual Meeting along with the Digital Now conference. Reactions were positive in both venues. The IARS has officially adopted the platform for ongoing training to its members.

“Some users expressed interest in seeing even more material available through IARS360; in particular, articles from outside journals not specific to anesthesiology but to related interests, such as neurosurgery,” McLaughlin said. 

“Education program managers were impressed that SelfStudy360 could provide such a powerful experience without requiring further development or tagging of files. SelfStudy360’s compatibility with an existing LMS and other systems already in place was also a hit.”

Where SelfStudy Is Headed

McLaughlin and CTO Cart Reed have also seen some interest in using their platform in high school, university, and with language learning.

“We will continue developing to our product road map, and expanding our sales and marketing efforts. We are also looking to build our client base across different disciplines,” McLaughlin said.

“On the product side, we are improving the curation workflow for our customers, in particular by simplifying question creation by auto-generating questions from text and videos. We’re also adding new tools to provide early warning systems for teachers and curators using statistical analysis and user feedback.” 

“We’re also in early development of a new discovery tool that displays what the system thinks the user is thinking about. This display changes from second to second as a user opens new items, favorites articles or takes questions. As such, it presents what is at the top of someone’s mind at the moment — along with the complexity and difficulty of activities that engage them. It gives teachers insight into an individual or a group of students’ interests, engagement, learning path, and performance to inform their decisions about what to present next.”

Cover Image: Marcelo Leal, Unsplash.

The post SelfStudy Raises $3 Million in Seed Round Led by the IARS appeared first on eLearningInside News.

K-12 classrooms are no strangers to personalized learning. AI algorithms, furthermore, have been applied to several elearning initiatives in the effort to more effectively match learners with the knowledge they seek. On Thursday, however, a new machine learning-powered platform emerged that goes above and beyond what has previously been made available for professional re-skilling. SelfStudy is a platform that uses machine learning algorithms to keep professionals up-to-date and in the know in their respective fields with personalized learning. On Saturday, they will make their first public demonstration at the annual International Anesthesiology Research Society (IARS) meeting.

The platform was funded by the IARS and, so far, it has been used and tested primarily in medical fields. But according to CEO Brenda McLaughlin, SelfStudy can be put to use in virtually any professional sector.

“We started in [medicine] where people are managing their own education while they’re also managing their family and jobs,” McLaughlin said. “And really–who isn’t? This is something we’re all dealing with. It used to be only some professionals who had to deal with continuous upskilling. But today, technological advances are changing all of our work. Not only do we sometimes just want to learn something—like a new language—but we all need to be continuously upskilling. We need the tools to be able to do that effectively, efficiently, and accessibly.”

How SelfStudy Works

The platform populates a learner’s ‘course work’ with educational content from any entity willing to partner. It might be from academic journals, universities, media publications, special interest groups, government bodies—anyone who provides rigorous, vetted, up-to-date material. On the learner’s end, professionals begin with a basic, more traditional assessment to determine where they’re at in their respective fields and where they want to go. SelfStudy’s algorithm then determines what educational content is most relevant and matches them accordingly.

“Taking the algorithms and machine learning we’ve developed that focuses on education mastery, continuous assessment, (which also opens badging for certifications for those who want to offer them), we’ve applied those to discovery,” McLaughlin said.

In a basic sense, the goal of SelfStudy is to make the most relevant educational material as easily accessible as possible. In other words, they’re a personalized learning platform for professionals.

“We think the tools we’re offering continues the revolution of MOOCs. MOOCs made education accessible and distributed (mostly) traditional educational opportunities to anybody who had a computer,” McLaughlin said. “Now we want to take the power of computers and create personalized experiences. Because we all know from face-to-face interactions with teachers that personalized learning yields results.”

The Merits of Constant, Real-Time Reassessment in Personalized Learning

Personalized learning—by and large a widely popular pedagogy—has taken a few hits in 2018, even from within its own ranks. SelfStudy describes itself as a kind of GPS for learners showing them which way to travel on their educational journey. The criticism of personalized learning, however generally states that 1) it’s incredibly difficult to assess where learners are on their ‘map’ and 2) it’s very difficult to know what direction to point them in. Cart Reed, CTO of SelfStudy believes his team has overcome these obstacles.

“You could argue that if you don’t do assessment right, it doesn’t matter what else you do,” Reed said. “The assessment we use is not a mechanical system. I think most [personalized learning] efforts you see are rule-based. They’re basically like ‘if you see this, do this.’ The concept is that content is structured and you can figure out what the structure is. You can also figure out the structure of what a person’s understanding is. And if you put those two together, it works.”

“To me, that’s like making an argument that the human brain is like a steam engine. It’s far more complex than that. People’s behavior changes minute to minute. Their capabilities are higher and lower on a daily basis, on an hourly basis.”

SelfStudy, however, continually reassesses both the relevance of the educational material and the capabilities of its learners in real time.

“The issue with all systems that I’m aware of on the commercial market is that they don’t reassess,” Reed said. “Because if you know the behavior of a learner changes rapidly, and you don’t change with it, you’re bound to get it wrong. Your assessment of where they were 30 minutes ago isn’t going to match anymore. Maybe they just were on a phone call and got some bad news. Maybe they were asleep. The assessment model you provide can’t keep a trail of data behind it. We don’t care about anything that happened a week ago. Even week-old data—if the learner is using the platform on a daily basis—isn’t really useable. When it comes to assessment you can’t make assumptions without testing them constantly.”

Reed and McLaughlin also believe that this constant reassessment safeguards against any issues with algorithmic bias that might crop up.

“Our data is based on people engaging in a series of staged presentations based on an assessment of where people are,” Reed said. “It’s based on their own data. We’re not testing them based on a community or against other individuals. The goal is for the system to be self-correcting. This isn’t a one-size-fits-all model.”

According to McLaughlin, the constant reassessment kills many birds with one stone. “There are tests that show that giving people results changes and improves performance,” McLaughlin said. “So we’re helping people improve but we’re also watching their performance because we can see, from that data, if there’s something wrong. If somehow our assessment does have some kind of bias in it and someone’s not progressing, we will notice.”

The post SelfStudy Hopes to Continue the MOOC Revolution with AI-Powered Personalized Learning appeared first on eLearningInside News.

On Friday the 13^th this month, Ray Kurzweil took the stage at TED 2018 in Vancouver to talk about his latest work at Google. Their new service, Talk to Books, allows you to, well, talk to books. And not just a few books. More like the 100,000+ volumes available in Google Books.

Here’s how it works. An interested or curious reader can type in a question, a statement, a sentence, a topic—anything really—much as they would speak it in a conversation. Talk to Books then scans all the titles in Google’s library (in roughly half a second) and produces several short segments of books that likely relate to your search.

Semantic Search in Talk to Books

That’s definitely cool, but I’m also kind of burying the lead. Talk to Books does not use a keyword-based search, as does its search engine and nearly every other online library and database. Instead, it uses what Kurzweil calls ‘semantic search.’

“Semantic search,” writes Kurzweil in a recent blog post, “is based on searching meaning, rather than on keywords or phrases. Developed with machine learning, it uses “natural language understanding” of words and phrases.”

Talk to Books is part of a larger project at Google implementing AI-powered semantic recognition. It also features word association games to help test (or train?) their algorithms along with a growing library of end-to-end models to be used by developers.

Quartz reports that Kurzweil does not intend semantic search to replace keyword search. They do not, however, provide a direct quote and we have a tendency to respond by asking, ‘are you sure?’

Keyword searches are generally unintuitive applications. Let’s take, for example, JSTOR, one of the most popular academic online databases. If I wanted to search for articles authored by Lawrence Lessig, I would need to navigate to the advanced search menu, toggle to the category of ‘author,’ and then type in ‘Lessig, Lawrence.’ If I accidentally typed ‘Lessig, Laurence,’ I would miss out on all relevant results. In some databases, you need to know particular search syntax. (On JSTOR, the above search would look like (au:”Lessig, Lawrence”).)

In the online worlds of research, marketing, journalism, legal matters, personal directories, social media, virtual communities, and countless others, users navigate primarily via search. That search function will be like JSTOR’s at best, and much more basic at worst. The fact of the matter is that in our current environment of hypertext and abundance of information, it can be very difficult to find what we’re looking for.

Talk to Books, and Kurzweil’s team’s research on semantic search, seems poised to revolutionize how we navigate the internet in general.

Machine Learning Algorithms Have Issues of Their Own

Still, deep learning algorithms do not come without their shortcomings. To paint in broad strokes, the semantic search algorithm seeks to understand and recreate (sort of) human language by learning it from other humans. And other humans have biases. As Kurzweil reiterates in a separate post, “In Talk to Books, while we can’t manually vet each sentence of 100,000 volumes, we use a popularity measure which increases the proportion of volumes that are published by professional publishing houses. There are additional measures that could be taken. For example, a toxicity classifier or sensitive topics classifier could determine when the input or the output is something that may be objectionable or party to an unwanted association. We recommend taking bias-impact mitigation steps when crafting end-user applications built with these models.”

The systems are mainly trained using white faces and male voices. This “…can lead to misperceptions of black faces or female voices, which can lead to the AI making negative judgments about [other folks].” https://t.co/GBho5WBKpv

— chris g (@hypervisible) April 22, 2018

When it comes to digital redlining, that’s really just the tip of the iceberg. As a society, we’ve already begun to experience serious growing pains with AI algorithms that have inadvertently already displayed prejudice in IRL situations.

For a TL;DR, Kurzweil’s team have not taken additional measures with their semantic search function to protect against bias. Taking a hard look at the ethics of semantic search would be a great next step. Its potential for online education and navigation of the internet in general is huge.  But for now, in a social sense, it is only as good as the humans who use it.

Cover Image: Ed Schipul, Flickr.

The post Will Google’s Semantic Search in ‘Talk to Books’ Supplant Keywords? appeared first on eLearningInside News.

Developments in artificial intelligence (AI) technology have already begun to revolutionize countless fields. Education is no exception.

Tom Vander Ark recently authored a report, “Ask About AI: The Future of Work and Learning” and released it via Getting Smart, the digital consulting firm he started.

“You’ve seen the warning on your rear-view mirror,” Ark writes, “’Objects in the mirror are closer than they appear.’ Only now it’s true for stuff in the windshield, too—exponential technology means the future is approaching more rapidly than it used to.”

The following mark five important takeaways on how AI will change the face, skeleton, and inner organs of education.

When it Comes to AI, Education Is Behind

Compared to other industries where advanced deep learning algorithms operate to perform numerous tasks, education has yet to implement AI to the same degree. There are several reasons for this.

First, education marks a diverse and varied field. One size will not fit all. Within a given school district, different institutions and levels of education will likely have different learning management systems (LMS), different online resources, and different technology in each classroom.

So far, AI has proven to be an effective grader of tests. Algorithms have been used to evaluate written responses and even grade essays to the same effect as human teachers.

In the field of tutoring, AI is expected to make huge advances in the short-term future. AI bots have proven effective in teaching young learners elementary math. Some even predict AI bots will replace tutors altogether.

Some districts have begun to streamline their LMS in meaningful ways. The state of Utah, for example, employs the same LMS for all public schools K-12. In Wyoming, they use one LMS for all public education K-20.

Platforms Are Here to Stay

While many technological developments have been difficult or costly to use in a classroom setting, digital, online (probably cloud-based) platforms have proven to be effective tools to aid in instruction in several different ways.

Ark quotes Sangeet Choudary, who co-wrote Platform Revolution: “A platform is a business based on enabling value-creating interactions between external producers and consumers.” According to Choudary, platforms are indispensable in the personalization of learning.

They excel in creating matches and connections between learners and instructors. AI technology promises to streamline these interactions even further. The more students use them, the more the AI algorithms will learn about student behavior, and this knowledge will help them address learner’s needs going forward.

According to the authors of Platform Revolution, platforms tend to be effective aids in any fragmented, yet information-intensive fields. In other words, “Education is perhaps the prime example of a major industry that is ripe for platform disruption.”

AI Will Change Pedagogies and Learning Strategies

As bots enter the classroom, both teachers and learners will have to reflect on their uses and outcomes. They will need to adopt an awareness of AI’s presence. Teachers must recognize AI’s short comings, such as inherently developing biases and its inability to process human emotions.

Going further, as various fields and technology continues to develop, students will need to accept that learning is a lifelong process. The subdivided lifestyle—where learners go to school as children and young adults, and obtain static employment based on their education—will not be an option in the AI-dominated workscape of the future.

Teachers Must Shift Their Energies to Material Which AI Cannot Teach

While AI will become indispensable in teaching black and white subjects, mostly in STEM fields, most believe that they will never be able to replace some aspects of what humans learn from other humans. This includes much of the humanities, although AI will probably integrate into these fields as well. But more importantly, teachers will need to focus on a curriculum with greater amounts social and emotional instruction. As the task of AI bots becomes cheaper, the value of human judgment and skills will greatly increase.

Social and emotional learning is defined as “a combination of self-management, self- and social awareness, relationship skills and responsible decision-making.”

The Future Is Exciting; The Future Is Scary

The attempt to understand the changes that AI will bring about is difficult enough. But according to Tim Urban, of Wait But Why writes that “in order to think about the future correctly, you need to imagine things moving at a much faster rate than they’re moving now.” In other words, there are known knowns and unknown unknowns. The latter may well far exceed the former.

The post Five Takeaways from the Latest Getting Smart Report on AI appeared first on eLearningInside News.

ELearning initiatives have begun to take over the world of industry and corporate training. In recent weeks, we’ve reported on the success of such programs among European telecommunications companies and microlearning in general.

This week, Tenneco Inc., a global automotive manufacturer, announced they will significantly expand their eLearning training program.

Educating a global workforce

ELearning and automotive training doesn’t, at the outset, sound like the most holy union. But in Tenneco’s case and others’, it actually makes a lot of sense.

Tenneco creates automotive products that produce lower emissions, operate with less volume, and increase safety. With 31,000 employees around the world, ensuring that all staff are on the same page, know their products sufficiently, and provide a standard of service can be fairly difficult.

The company also invests a significant amount of resources in educating their clients on their products and helping them find useful implementations for their new technology.

The new courses will include modules focused on vehicle inspection, customer communication skills, and diagnostic techniques. What’s more, where most online teaching takes place in English the content will also be available in French, and Spanish.

“Service Solutions takes a holistic approach to helping Tenneco customers increase their ride control and other service volume over the long-term,” said the company’s aftermarket training manager Ethan Bregger, according to Ratchet and Wrench.

“We have found that this approach is far more effective than individual training events, which will often produce only a temporary increase in business. Our eLearning modules help employees contribute to a sustained improvement in the way their shops approach ride control replacement and other service opportunities.”

The Services Solutions platform, Tenneco’s eLearning initiative, first launched in 2016.

“Our channel partners and thousands of vehicle service businesses have long relied on Tenneco for a comprehensive package of tools designed to help drive their success,” explained Vice President Jeff Koviak at the time, according to Tire Review.

Other automotive eLearning initiatives

Based on the unique nature of the automotive industry, especially when it comes to mechanical solutions, one might expect Tenneco to be the sole company experimenting with alternative training methods.

But Tenneco is not alone. Axalta Coating Systems, a vehicle coating company, also launched an eLearning initiative in August.

Axalta’s varies somewhat in that it trains employees primarily to apply the coatings the company sells.

With their Master Certification program, refinish technicians in training tune in to an interactive video stream of a lecture. In the afternoon, they apply the skills they’ve learned on a project. After capturing the process on video, they send it to their instructors to get their feedback.

“Our learning and development programs are carefully designed with the participant’s experience in mind,” said Axalta’s director of customer experience Patrice Marcil, according to Body Shop Business.

Axalta also still conducts a significant amount of training in person as well. The curriculum in both forms is nearly identical.

“From a virtual course, to a program at our world-class destination like the Customer Experience Center, we are deeply committed to providing the content, delivery methods and experience that exceed the expectations of our customers.”

There’s good reason to believe that, soon, eLearning training will be a standard in the automotive industry, especially as self-driving cars begin to gain popularity.

When it comes to AI design, and implementing new, green technology. A recent Technavio market research report found that the global mechatronics market is forecast to grow by CAGR of over 15%, boosted largely by developments in the automotive industry.

Mechatronics and robotics workshops are also growing in popularity.

“The workshops are generally instructor-led and emphasize heavily the importance of experiential learning,” said Jhansi Mary, a lead analyst at Technavio for K-12 and higher education, according to Business Wire.

“The workshops are divided into two parts; the first part consists of presentations and delivery of theoretical knowledge, whereas the second part generally consists of hands-on learning and the students are made to apply theoretical knowledge by designing their own robots.”

That sounds a whole lot like the training method at Axalta. It’s become clear that eLearning applications can go far beyond the world of tech. If Tenneco and Axalta can educate remotely, others can too.

The post Tenneco and Axalta Tinker with Automotive ELearning appeared first on eLearningInside News.